Following eight months of close collaboration with 麻豆原创, DACHSER has reached a major milestone on this journey: the successful migration of human capital management (HCM) to 麻豆原创 S/4HANA via .

Nearly a century has passed since Thomas Dachser founded the company in 1930 with a single truck, transporting cheese from the Allg盲u region to the Rhineland and returning with steel. Yet, logistics and warehousing remain the core business of the transport logistics company, which is headquartered in the town of Kempten in south-west Germany. “Our core business is what we call our road business, meaning everything transported by road, across both dry goods and food segments,” says Herbert Egner, head of the IT Products Finance/HR division at DACHSER, who has nearly 40 years of experience in software development at the company.

Currently, DACHSER operates globally with approximately 427 company-owned branches across 43 countries. Out of its roughly 37,500 employees worldwide, 19,000 are based in Germany. Total revenue in 2025 reached 鈧�8.3 billion. “On one hand, we are a deeply tradition-conscious family business, now managed by the third and fourth generations. On the other hand, we place a massive emphasis on innovation鈥攁nd not just at the executive level,” Egner notes. “Every single employee should have the opportunity to contribute here.”

In terms of digitization, the company is currently replacing a multitude of small, manual processes with IT-based solutions. Following DACHSER鈥檚 licensing of the 麻豆原创 Business Technology Platform (麻豆原创 BTP) in 2024, employees can now leverage its low-code tools to build apps for their own workflows. For instance, instead of using physical clipboards and paper checklists to document damage to transport vehicles, DACHSER inspectors now use low-code applications to capture that information digitally.

麻豆原创 BTP and the 麻豆原创 Integration Suite also played a vital role in helping DACHSER move HCM to the cloud鈥攚hich, alongside the license conversion to 麻豆原创 S/4HANA, marks one of DACHSER鈥檚 most significant IT upgrades in recent years. “While we are a long-standing 麻豆原创 customer, we are certainly not your typical 麻豆原创 user,” Egner explains. “For transport and warehouse management, we still rely on our proprietary systems, which we began developing back in the 1980s. At the time, 麻豆原创 did not yet offer the specific system depth we required for our logistics processes.”

Finance software from 麻豆原创 has been in use at DACHSER since 2009, with journal entries transferred from the company’s internal systems to 麻豆原创 via an interface. In October 2024, the finance solution was migrated from an on-premise environment under 麻豆原创 ERP Central Component (麻豆原创 ECC) and 麻豆原创 HANA to the Microsoft Azure cloud. As part of RISE with 麻豆原创, DACHSER then successfully migrated its HCM payroll and time management modules for its 19,000 employees in Germany to the cloud in June 2026. This intensive eight-month collaboration between 麻豆原创 and DACHSER successfully established a cornerstone of the company鈥檚 global HCM transformation.

“For HCM, we chose RISE with 麻豆原创. However, when we decided to move to the cloud three years ago, it wasn’t yet mature enough to meet our specific needs,” Egner says. “Once our three-year contract with Azure expires, RISE with 麻豆原创 could become a viable model for our finance environment as well.”

The go-live was flawless: the very first payroll run for all employees in Germany in July 2026 went off without a hitch, and all payments were distributed on time. The system then entered a four-week hypercare phase, during which the project team closely monitored ongoing operations before regular support took over in August. With this step, DACHSER has established the necessary future-proof 麻豆原创 architecture for its HR operations. This opens up new possibilities for the company, allowing it to focus heavily on implementing new features within the 麻豆原创 SuccessFactors HCM Suite.

麻豆原创 S/4HANA transformation

“When we say we want to be the world’s most digitally integrated logistics service provider by 2030, this applies not only to digitizing our processes but also to integrating our acquisitions, which bring their own 麻豆原创 systems with them,” Egner says. “Under our ‘麻豆原创 First’ strategy, we roll out finance and HCM in these countries before deploying our proprietary transport and warehouse management systems.” This approach was recently executed in Italy and is currently planned for several acquired companies in the Iberia region.

DACHSER鈥檚 goal is to integrate the 麻豆原创 licenses of acquired companies into a global enterprise agreement with 麻豆原创, regardless of the country in which the systems are running. In the future, this will be handled via a semi-automated workflow. “When it comes to licensing in particular, it is crucial for us to have a unified agreement moving forward on how to manage these assets, ensuring that neither side faces these administrative overheads anymore,” Egner explains.

In connection with the license conversion from 麻豆原创 ECC to 麻豆原创 S/4HANA, both companies sat down once again to realign on their future path to mutual success. “Here at DACHSER, we are noticing a new openness from 麻豆原创, as well as a deeper understanding of us as a customer,” says Egner. “This has been received very positively on our end. People are working on both sides, and we want to shape this partnership in a way that allows both parties to benefit based on mutual respect.”

With the 2H 2026 release and throughout the remainder of the year, we’re taking the next step toward Autonomous HCM, bringing together agentic AI, trusted workforce data, and HR applications to help deliver the outcomes that matter most to organizations. At its core are three pillars: automate the HR function to release capacity from administrative work, redesign how tasks, workflows, roles, and teams are structured across people and AI, and reinvent how organizations recruit, develop, move, and reward their people.

This vision comes to life through working together across 麻豆原创 applications to help carry out end-to-end HR processes and help people make better decisions, faster, all within a single workspace: . This is what it looks like when AI works across an organization鈥檚 data, applications, and processes: not more AI for the sake of AI, but AI that delivers impact you can measure.

Building on the 麻豆原创 investments organizations have already made, the innovations we鈥檙e delivering throughout the second half of 2026 help automate, redesign, and reinvent work to realize the full promise of Autonomous HCM.

These innovations span the full employee lifecycle:

Plan & hire

Finding, hiring, and onboarding the right talent gets easier and faster, with every step aligned to business needs.

• As AI drives up application volumes, recruiters risk spending more time clearing a queue than assessing if a hire works for the business. can address this with repeatable, configurable screening that helps narrow large applicant pools to a focused shortlist. builds on that, with results now fully reportable in Report Builder, giving recruiters visibility into the reasoning behind AI-assisted decisions. Together, they help free up the time and attention to do what the business actually needs鈥攁pply their judgement to identify and engage the candidates most likely to succeed.

• helps put agentic capability directly inside the recruiter workflow so hiring never loses momentum, with monitoring pipelines and booking interviews through agentic scheduling, Winston Interview delivering a conversational AI-led screening experience, and the Interview Summary Agent automatically capturing and posting a structured summary to the candidate profile.

• Helping new hires get up to speed and start contributing faster, the equips HR teams to deliver personalized, timely onboarding at scale, with intelligent prioritization, simplified onboarding task creation, and automated custom form conversion.

Manage & pay

These innovations help organizations work more efficiently and stay compliant while giving employees fast, seamless support to reduce the routine inquiry burden on HR teams.

• The helps build trust in payroll so employees can have confidence in every paycheck. Administrators can quickly identify anomalies, resolve issues, and stay ahead of compliance, while employees can get direct access to clear, confident answers about their pay without raising a support ticket.

• The can reduce manual effort, prevent bottlenecks, and keep HR processes moving, proactively resolving workforce and payroll data issues, automating employee and job changes, and streamlining position management. It can also detect approval bottlenecks, nudge approvers, and recommend next steps.

• The can give HR administrators a smarter way to manage day-to-day system operations鈥攆rom audit readiness and compliance tracking to time and benefits configurations鈥攔educing routine maintenance and helping HR teams drive continuous improvement and innovation.

Develop & grow

These innovations connect skill-building, learning, and career development into a more intentional experience designed for continuous growth.

• The helps move organizations to proactive workforce readiness, connecting compliance monitoring, upskilling, and development in one experience. It can guide the right learning actions at the right time for employees, managers, and admins, from flagging compliance deadlines to identifying skill gaps and recommending targeted learning.

• People perform at their best when they know their employer is invested in their development. The helps employees close skill gaps, build personalized development plans, and set meaningful goals. For leaders, conversational talent discovery through Joule helps surface internal candidates, successors, and experts with a clear explanation of what shaped each result, helping organizations match the right talent to opportunities and grow people from within.

The next step toward Autonomous HCM

These are not standalone capabilities. Together, they are Autonomous HCM in action: AI working with trusted data and HR processes to remove friction, surface insight, and give people the space to focus on outcomes that matter. The organizations building that way today are the ones that will lead tomorrow.

Discover what鈥檚 new in the 麻豆原创 SuccessFactors 2H 2026 release with the or .

Rebecca Carr is president of HCM Products for 麻豆原创 SuccessFactors and CEO for SmartRecruiters.

鈥淚t’s time to show you the Autonomous Enterprise in action underpinned by great customer stories,鈥� 麻豆原创 CEO Christian Klein told his keynote audience at the start of the event.  

Klein reminded the audience that 麻豆原创 introduced the Autonomous Enterprise at its 麻豆原创 Sapphire conference in May 2026 as 鈥渢he beginning of better.鈥� Since then, he said, 麻豆原创 has worked with hundreds of customers to implement Joule Work as the AI engagement layer for the Autonomous Enterprise. 

A new UI for AI 

鈥淭his month, we are rolling out Joule Work for all customers,鈥� Klein said, describing it as a new UI for AI. He noted that for decades, users had to learn how 麻豆原创 worked, but with Joule Work, 麻豆原创 learns how people work. 鈥淔rom now on, the more than 400 million 麻豆原创 users can talk in their own language to 麻豆原创, and Joule Work gets the job done.鈥� 

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Klein explained that Joule Work is based on three pillars: conversations, where users ask questions and delegate tasks to agents; spaces, which display content, insights, and shared work; and Joule Studio, where customers extend Joule or build agents tailored to their own processes.   

He called 麻豆原创鈥檚 deep business and data context its 鈥渟ecret sauce.鈥� That context includes 麻豆原创 Knowledge Graph, which maps more than 7 million data fields, 50 million tables, more than 50,000 public and private APIs, 400 data products, and extensive process knowledge. 鈥淭hat’s why Joule doesn’t guess,鈥� he said. 

麻豆原创鈥檚 110,000 employees are already using Joule to perform hundreds of thousands of tasks every day, he shared: 鈥淲e are already seeing productivity gains in central functions like HR, finance, and procurement of over 20% and even bigger gains in more complex analytical and planning tasks.鈥� 

麻豆原创 Autonomous Suite 

Klein then turned his attention to the 麻豆原创 Autonomous Suite, the second layer in the Autonomous Enterprise. The suite initially covers five domains: finance, procurement, supply chain, human resources, and customer experience. 麻豆原创 Autonomous Suite is designed for work where a good answer is insufficient and 鈥渢he right answer鈥� is required every time, he said.  

鈥淟LMs are probabilistic and only give you the most likely answer,鈥� Klein said. He contrasted that probabilistic approach with 麻豆原创’s embedded agents. Because the agents operate within deterministic application workflows, they use the same data, follow the same rules, and leave the same audit trail as the applications themselves. Customers can choose the level of autonomy appropriate to each process, retaining human approval where risk is high and allowing greater automation for routine work. 

Since 麻豆原创 Sapphire, Klein said 麻豆原创 has created more than 20 Joule Assistants and over 200 Joule Agents, and is aiming for more than 400 agents by year-end. 鈥淏ut the real story isn鈥檛 the number of agents. It鈥檚 the business outcomes they deliver,鈥� he said. 

麻豆原创 Business AI Platform 

鈥淭hese agents can only understand your business so well because of the 麻豆原创 Business AI Platform,鈥� Klein said. 鈥淭he platform gives customers the best frontier model for every agentic use case, the deepest out-of-the-box business context and 麻豆原创-managed governance.鈥�  

Building on Klein鈥檚 remarks, Manoj Swaminathan, president and chief product officer of 麻豆原创 Autonomous Suite, described the 麻豆原创 Business AI Platform as the infrastructure that enables the Autonomous Enterprise. The platform is organized around three capabilities: building agents, contextualizing them with business data, and governing how they operate. 

Swaminathan explained how the context layer makes agents more accurate. Joule Studio spans no-code and professional development and offers access to more than 70 models, a strategy he said reduces lock-in and controls token costs.  

鈥淛oule Studio is natively integrated with our context layer,鈥� he said. 鈥淪o, the agents you build are more accurate, faster to deploy, and more efficient to run. Our knowledge graph is the map with the processes, data flows, and business tools. The agents find the right processes among thousands and the right information among over 7 million feeds. 麻豆原创 Business Data Cloud brings that understanding to all your data, one consistent view, the processes, policies, and logic to make it meaningful.鈥� 

Swaminathan said no AI can compensate for a broken data model. To help agents understand customers鈥� business rules, 麻豆原创 Domain Models are trained on 麻豆原创鈥檚 code. For predictions, 麻豆原创 provides two engines grounded in how a customer’s business operates: 麻豆原创-RPT, 麻豆原创’s model family trained on its business data, and the Prior Labs tabular AI model.

Jerseys from Jersey 

During his section of the keynote, Jan Gilg, global president of Customer Success & Americas, used an imaginary startup 鈥� 鈥淛erseys from Jersey鈥� 鈥� to invite a handful of customers to the stage to answer his questions and validate aspects of 麻豆原创鈥檚 Autonomous Enterprise strategy.  

The customers included Novartis, which is piloting Joule sourcing agents for bid analysis and negotiation support; Morgan Foods, which described a supply-chain transformation built on 麻豆原创 S/4HANA and 麻豆原创 Integrated Business Planning; Nestl茅, which emphasized the importance of a unified digital core; and 麻豆原创 customer and partner PwC, which spoke about the value of the Industry AI portfolio from 麻豆原创. 

Summing up their comments, Gilg noted that the elements of the 麻豆原创 Autonomous Suite 鈥渁re more than a collection of functional components. It鈥檚 one system working together like connective tissue that provides connectivity, context, and control.鈥�

Gilg also made several product announcements, including the launch of 麻豆原创 Pay, an embedded payments service that can automatically execute and reconcile supplier payments once an invoice is approved. He also announced 麻豆原创鈥檚 planned acquisition of TechWolf, a Belgian workforce-intelligence startup designed to help close skills gaps. 

Security and governance 

In the closing section of the keynote, 麻豆原创 Chief Security Officer Marielle Ehrmann focused on trust and governance. She noted that ransomware handovers that once took eight hours now take 22 seconds with AI, and while 83% of enterprises use AI daily, only 13% have real visibility into it.  

鈥淭he biggest threat to companies is not malicious AI; it鈥檚 unmanaged AI,鈥� Ehrmann said. To counter that threat, she said every agent should have a verified owner, a risk tier, and scoped access rights, supported by zero-trust checks on identity, purpose, and data sensitivity as well as human oversight. 

She emphasized that 麻豆原创 Business AI Platform incorporates regulatory and localization requirements, applies user authorizations, keeps customer data from being used to train foundation models, and supports three levels of oversight: human-in-the-loop approval, human-on-the-loop monitoring, and human-in-command override authority. 鈥淭he more autonomously an agent operates, the tighter the oversight applied,鈥� Ehrmann said, calling the principle 鈥渇reedom within boundaries.鈥� 

A clear shift among customers 

Wrapping up the keynote, Klein emphasized that trust is key to everything 麻豆原创 does and has been for over 50 years. 鈥淲e are delivering the most trusted and governed AI in the industry,鈥� he said, but added, 鈥淎I also requires significant change management to ensure it delivers the desired outcomes for your business.鈥� 

That is where 麻豆原创鈥檚 business transformation solutions come in, he said. 麻豆原创 Signavio measures process value before and after a change to help justify token spending; 麻豆原创 LeanIX discovers and tracks AI agents; and 麻豆原创 WalkMe supports user adoption and trust. Klein also highlighted an agent-led migration toolchain. Together, he said, these capabilities mean that the days of multi-million-dollar migration spend are gone.

鈥淭his is no longer the start of something better. This is better,鈥� Klein told the audience. He described a clear shift among 麻豆原创 customers: 鈥淔rom manual steps to connected workflows, from reactive decision-making to predictive insights, from humans in spreadsheets to humans in and on the loop–all powered by our AI platform to keep AI accurate, governed, and extensible.鈥�

And, most importantly, Klein said, 鈥淚ts ready for you today鈥� This is the Autonomous Enterprise.鈥� 

According to research from the , 72% of executives believe organizations claiming to transform work with AI are primarily automating existing processes rather than fundamentally redesigning how work gets done. Yet, 88% say redesigning work and roles creates significant enterprise value. And HR is ranked as the No. 1 owner of that work. As a result, HR and business leaders are looking at how technology can support their need to continuously align people, skills, and work with evolving business priorities.

This is the journey to . Autonomous HCM is the future of human capital management, where AI automates end-to-end processes, drives context-aware decisions, and optimizes workforce operations at scale.

As we think about Autonomous HCM, we have defined three pillars:

1. Automate the HR function to release capacity from administrative work: HR teams currently spend a significant share of their time on operational activities such as payroll, service delivery, recruiting administration, and workforce management. AI can reduce much of that burden, creating capacity for more strategic work. But automation is not the destination. It’s the foundation. The true value comes from what organizations do with the time and resources they regain.
2. Redesign how tasks, workflows, roles, and teams are structured throughout the enterprise, across both people and AI: For decades, companies optimized around jobs, functions, and fixed processes. AI challenges many of those assumptions. The opportunity is no longer simply to make existing work more efficient. It is to rethink work itself. This is not just a technology initiative. It is one of the most important business transformation challenges organizations face today.
3. Reinvent how organizations recruit, develop, move, and reward their people: Most talent processes were built for a world characterized by stable jobs and predictable career paths, but that world is rapidly changing. Organizations that succeed will create talent ecosystems that can adapt as quickly as the business itself.

These three pillars are all interconnected: automation releases capacity, work redesign determines how value is created, and talent-system reinvention makes the new model sustainable.

What makes this possible is 麻豆原创鈥檚 unique ability to bring together trusted workforce data, connected business processes, ontology, and AI within a single business context. Together, this context enables organizations to move beyond isolated HR activities and make strategic workforce decisions that drive the most urgent business outcomes. This context is what matters.

During 麻豆原创 Connect, 麻豆原创 announced that it has entered into an agreement for 麻豆原创 to acquire TechWolf. TechWolf provides a leading AI work intelligence platform, which helps organizations understand the work their people do and the skills they have, giving them the right context and the right grounding. Once the transaction closes, TechWolf is expected to power workforce and talent strategies across the 麻豆原创 SuccessFactors portfolio, bringing skills mapping, workforce planning, and organizational redesign informed by context from across the Autonomous Enterprise to guide decisions about development, deployment, and workforce transformation.

New Innovations to 麻豆原创 SuccessFactors HCM Suite

While Autonomous HCM is our vision for the future, we have several new innovations spanning the entire 麻豆原创 SuccessFactors HCM suite, available this month, including:

A growing portfolio of AI assistants

New AI assistants orchestrate work end-to-end and support decisions in real time. Many of the agents that we announced at 麻豆原创 Sapphire are available this month, including assistants for payroll, HR service, learning, recruiting, onboarding, and career and development. We have more agents coming soon, including the new Workforce Planning Assistant to support customers using . It is powered by connected workforce, contingent labor, and financial data from 麻豆原创 SuccessFactors, , and , to help business and HR leaders forecast workforce needs and create plans for the most effective mix of hiring, reskilling, redeployment, and external talent to address changing workforce demands.

Significant updates to our global benefits solutions

Benefits are among the most important decisions employees make, and they can also be some of the most complex for HR teams to support. To help make benefits administration more efficient for HR and benefits decisions more personalized for employees, 麻豆原创 announced two new innovations built natively into 麻豆原创 SuccessFactors Employee Central. The new agentic admin console for U.S. benefits provides HR administrators with a centralized view of benefits enrollment activity and exceptions, helping them quickly identify and resolve issues with built-in monitoring and natural language support. By reducing time investigating enrollment issues and navigating reports, organizations can improve oversight and manage complex enrollment periods more efficiently. Additionally, the new benefits decision support tool uses employee data already in the system to recommend coverage aligned to individual needs and budgets, resulting in a more personalized and intelligent enrollment experience for employees. 

New integration of WalkMe Learning Arc with

Creating and deploying learning content can often take weeks, making it difficult for organizations to respond quickly to changing business needs. With this new integration, learning teams can describe learning requirements in natural language, and AI generates courses and quizzes while maintaining author control. Learning experiences can then be created and deployed directly within 麻豆原创 SuccessFactors Learning in hours rather than weeks.

Shaping Autonomous HCM with our customers

As we look forward, we know that what has worked in the past will not take us to the future. The goal is not simply to showcase technology, but to prove how connected AI can help organizations translate strategic decisions into measurable workforce and business results faster and more effectively. Rather than organizing our innovation around individual products or modules, we are focusing our innovation around the most important outcomes our customers are trying to achieve鈥攁nd in doing so, leaning into 麻豆原创鈥檚 strength in connecting data, workflows, and processes across the entire 麻豆原创 portfolio. We will co-innovate with select customers to define, validate, and measure outcome-driven approaches that connect workforce decisions directly to business value, proving the value of our innovations in real time.

The journey starts now

We are at a defining moment for HR leaders. The future of work will not be shaped solely by technology. It will be shaped by the leaders who can translate transformation into meaningful outcomes for their organizations and their people.

Autonomous HCM is the future of HCM. But it does not start tomorrow. The journey starts today.

To learn more about the latest 麻豆原创 SuccessFactors innovations and how 麻豆原创 is helping organizations advance their journey toward Autonomous HCM, .

Siva Sundaresan is general manager and chief product officer for 麻豆原创 SuccessFactors.

Many of the futures we have explored are no longer hypothetical. They are showing up in how work is organized and experienced today. The fundamental question now is whether organizations are shaping those changes deliberately or simply reacting as they unfold.

combines monitoring of more than 500 business, academic, government, and economic resources with original global mixed methods research involving 2,718 employees, 500 C-suite leaders, 60 HR executives, and founders of AI-native companies. It points to a fundamental concern: organizations may be optimizing the future of work for efficiency when they should be designing it for value.

The productivity trap

In October 2025, we explored 10 predictions for work, workforces, and work practices, each with two possible futures. A year later, the evidence is strongest for what we call the “AI Upgrade” future, in which AI鈥檚 value is measured through efficiency, productivity gains, and time savings. Signals of broader work transformation are emerging, but they remain less established.

The emphasis on productivity is understandable because time savings, output, and cost reductions are relatively easy to measure. The harder question is what organizations do with the capacity AI can create. They can ask employees to produce more of the same work, or they can redesign work, roles, teams, and talent systems around what people and AI can achieve together.

Work transformation needs a north star

Related research from our found that 88% of employees said their jobs have changed because of AI, yet half of those changes occurred without meaningful guidance from managers or their organizations. Employees are using AI to simultaneously offload tasks and expand the scope of their work, often without a shared playbook or a clear view of the intended outcome. 

Before organizations can transform work intentionally, they need a clear north star for what work should become. Yet between 55% and 70% of employees said they had received no clear organizational guidance on the work shifts they are expected to navigate. At the same time, 72% of C-suite leaders said that most organizations claiming to transform work with AI are really automating existing jobs faster. Without a shared vision for work transformation, organizations risk defaulting to isolated experimentation and efficiency-first use cases, creating uneven outcomes and limiting the combined potential of people and AI.

Six shifts to guide better work design

We endorse six shifts in work and organizational design that are both enabled by AI and associated with work-enriching characteristics well established in organizational psychology as leading to increased employee motivation, effort, performance, and retention:

• From specialist to generalist: Apply core expertise across a broader range of problems and tasks.
• From static jobs to dynamic roles: Organize work around flexible responsibilities and outcomes that evolve with business needs.
• From pyramid to diamond organizational design: Reduce coordination layers and concentrate more people closer to where core work happens, enabling them to own end-to-end delivery.
• From output to impact: Evaluate work by the value it creates, not simply by activity or deliverables.
• From centralized authority to decentralized decision-making: Move decisions closer to the people and teams with the context to act.
• From people management to self-leadership: Give employees greater ownership of their direction, performance, and growth.

Through an experimental study, we validated how all six shifts can enrich work. For example, employees perceived 77% greater autonomy under decentralized decision-making, while dynamic roles were perceived as 49% more challenging than static jobs. The full report examines these effects across all six shifts, compares where organizations are today with where employees believe they need to be, and offers a prioritized path for leaders to get started.

Work transformation requires HR transformation

If work shifts this substantially, the function responsible for the people agenda cannot assume its own role and structure will remain the same. HR was built for fixed jobs, predictable career paths, established hierarchies, and talent systems designed for consistency. AI challenges each assumption.

With this context, we see HR鈥檚 new mandate as focused on three interconnected pillars:

• Automate: Use automation and intelligent systems to release capacity from administrative work and create space for more strategic contribution. C-suite leaders estimate that 49% of HR work will be fully automated within five years, compared with 35% of enterprise work overall.
• Redesign: Lead enterprise work redesign by determining how tasks, workflows, roles, and teams are structured across people and AI. Executives ranked work redesign as the transformation pillar that will create the greatest enterprise value over the next five years and identified HR as its leading owner.
• Reinvent: Overhaul recruitment, development, mobility, performance, and rewards to support how work now gets done and who succeeds in the new way of working. Seventy-five percent of executives agree that organizations can succeed in the AI era only if they reinvent how they measure, reward, and grow people.

In the full report, we also explore four plausible futures for how these pillars might come together to shape HR鈥檚 strategic contribution, depending on where leaders believe the people agenda can create the greatest value.

The future of work is a choice

The future of work is already being built. The opportunity now is to build it intentionally, creating better work for people and greater value for organizations. 

Explore how our 10 predictions from 2025 are tracking, the evidence behind six work shifts for better employee and business outcomes, and four possible futures for how HR can create strategic value in an AI-enabled enterprise. .

Dr. Autumn D. Krauss is chief scientist of the Future of Work Research Lab for 麻豆原创 SuccessFactors.

TechWolf gives enterprises a continuously updated view of the work their people do and the skills they have, using its proprietary data model called context graph for work. The acquisition will bring this context graph, along with TechWolf’s AI models and applied AI research team, into 麻豆原创, establishing work intelligence as a strategic 麻豆原创 asset. The deal is expected to close in Q4 2026, subject to usual closing conditions, including regulatory approval. Terms of the deal were not disclosed. 

TechWolf works from existing HR and business systems that customers connect. It builds its model of the organization at three levels: the work itself, down to the tasks inside a job; the skills people have and apply; and the external labor market. It maps that against the customer鈥檚 business strategy, so the leaders responsible for hiring, reskilling and redeployment are working from better information.

TechWolf is expected to become an intelligent core of the 麻豆原创 SuccessFactors portfolio, supporting the company鈥檚 talent and work intelligence strategy. TechWolf will power workforce and talent strategies across 麻豆原创 SuccessFactors, bringing skills mapping, workforce planning and organizational redesign informed by context from across the Autonomous Enterprise. Once the transaction closes, TechWolf and 麻豆原创 will unify skills and work data to inform HR and business leaders to guide decisions about development, deployment and workforce transformation.

鈥淭echWolf鈥檚 proprietary context graph for skills and work provides an excellent grounding layer for agent queries regarding work and skills planning and talent management,鈥� said Manoj Swaminathan, president and chief product officer for 麻豆原创 Autonomous Suite and member of the Extended Board of 麻豆原创 SE. 鈥淭his grounding layer perfectly matches our strategy. It makes token usage more efficient, lowers the cost of deploying workforce agents and will make Joule more intelligent in AI-driven HR scenarios such as skills-based hiring, workforce planning and role redesign.鈥�

Joint 麻豆原创 and TechWolf customers using the technology are seeing measurable results from the partnership the two companies have had. Building on that foundation, 麻豆原创 and TechWolf will jointly co-innovate a concrete set of new AI-powered workforce and skills optimization products to be designed and developed post-close. 麻豆原创 plans to integrate TechWolf鈥檚 solutions to a greater degree, offering customers even better insights and work intelligence to help organizations plan reskilling, internal mobility and hiring.

“Organizations everywhere are trying to figure out how AI is reshaping work, and what their workforce needs to look like because of it,” said Andreas De Neve, CEO and co-founder of TechWolf. “We have spent eight years building the evidence layer to answer those questions. It’s always been our mission to connect skills, tasks and work to help employers solve AI transformation, and joining 麻豆原创 will allow us to extend that mission across a broader set of business context and larger scale. In this next chapter, we plan to build a world-class AI company.鈥�

Subject to closing and required consultation, 麻豆原创鈥檚 current plans are for TechWolf to remain as an independent entity under CEO Andreas De Neve in its Ghent headquarters, with offices in London, New York and San Francisco, and for its platform to remain available to both 麻豆原创 and non-麻豆原创 customers. J.P. Morgan served as exclusive financial advisor to TechWolf.

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About TechWolf

TechWolf is a leading applied AI company that helps large enterprises understand how AI is transforming work and what that means for their workforce. Its platform brings together skills, work, and market intelligence, into a single ; Its open-source models have been downloaded more than two million times.听 TechWolf co-exists with systems enterprises already use, including 麻豆原创 SuccessFactors and non-麻豆原创 applications, and connects with AI tools and agents. Customers include HSBC, Atlas Copco Group, GSK, Ericsson, AMD, MetLife, PayPal and Booking.com. The company offers EU and US data-residency, standard encryption, access controls and certifications including ISO/IEC 42001 and ISO/IEC 27001 that support EU AI Act governance and security. Learn more at .

About 麻豆原创

As鈥痑 global leader in enterprise applications and business AI, 麻豆原创 (NYSE: 麻豆原创)鈥痵tands at the鈥痭exus鈥痮f business and technology. For over 50 years, organizations have trusted 麻豆原创鈥痶o bring out their best by uniting business-critical鈥痮perations spanning finance, procurement, HR, supply chain, and customer experience. For more information, visit鈥�.

Note to editors:
To preview and download broadcast-standard stock footage and press photos digitally, please visit . On this platform, you can find high resolution material for your media channels.

For customers interested in learning more about 麻豆原创 products:
Global Customer Center: +49 180 534-34-24
United States Only: 1 (800) 872-1麻豆原创 (1-800-872-1727)

For more information, press only:
Aim茅e Leabon, +1 (212) 653-9600, aimee.leabon@sap.com, EDT
Marcus Winkler, +49 151 571 18 691, marcus.winkler@sap.com, CEST
Daniel Reinhardt, +49 151 168 10 157, , CEST
Hanna Heine, +49 152 552 36 605, hanna.heine@sap.com, CEST
麻豆原创 麻豆原创 Room; press@sap.com
Reinhard De Milt, TechWolf, +32 498 495781, reinhard.demilt@techwolf.ai, CEST

This press release was created with the assistance of artificial intelligence and has been reviewed by the editorial team.

This document contains forward-looking statements, which are predictions, projections, or other statements about future events. These statements are based on current expectations, forecasts, and assumptions that are subject to risks and uncertainties that could cause actual results and outcomes to materially differ. Additional information regarding these risks and uncertainties may be found in our filings with the Securities and Exchange Commission, including but not limited to the risk factors section of 麻豆原创鈥檚 2025 Annual Report on Form 20-F.
漏 2026 麻豆原创 SE. All rights reserved.
麻豆原创 and other 麻豆原创 products and services mentioned herein as well as their respective logos are trademarks or registered trademarks of 麻豆原创 SE in Germany and other countries. Please see for additional trademark information and notices.

Joule Work, Joule Assistants and 麻豆原创 Business AI Platform help organizations turn business AI into trusted outcomes across every core function.

LAS VEGAS 鈥� (NYSE: 麻豆原创) today showcased the Autonomous Enterprise in action at 麻豆原创 Connect, demonstrating how Joule Work and Joule Assistants generate value for customers across every line of business.

“This is a breakthrough moment for business AI,” said Christian Klein, CEO of 麻豆原创 SE. “The Autonomous Enterprise has arrived. With Joule and 麻豆原创 Autonomous Suite, built on 麻豆原创 Business AI Platform, we’re helping organizations like Novartis, Morgan Foods, Nestl茅 and PwC connect intelligence across every function to deliver trusted business outcomes.”

At 麻豆原创 Connect, these customers shared how the Autonomous Enterprise is already driving measurable value across their businesses:

• 鈥淲e’ve co-developed and recently launched a pilot of 麻豆原创’s Joule Sourcing Assistant,鈥� said Christoph Buerki, Head of Procurement, Novartis. 鈥淥ur vision is for AI agents to handle the manual heavy lifting, enabling sourcing professionals to focus on strategy, supplier engagement and value creation.鈥�
• 鈥淎t Morgan Foods, we鈥檙e already putting the pieces in place for agentic adoption, especially through our technical foundation. The biggest shift will be moving from reactive to predictive, where agents can connect demand signals, inventory levels and supplier status faster than ever before,鈥� said Steve Hankins, Chief Financial Officer, Morgan Foods, 鈥淥ur superpower will come from people on top of agents. Our approximately 1,000 employees are what make our supply chains work鈥攖he technology helps make them even better.鈥�
• 鈥淥ur 麻豆原创 S/4HANA transformation across 140 countries is creating a connected digital core with consistent processes, trusted data and greater visibility across markets and functions. With that foundation, Joule and the Accounts Receivable Assistant can automatically prioritize collections work based on risk and business context, recommend the next best action and help our finance teams respond faster to change,鈥� said Luca Dell’Orletta, Global Head IT Innovation & Enterprise Architecture, Nestl茅.
• 鈥淚n professional services, billing can be one of the more error-prone processes, with accuracy playing an important role in the client experience. 麻豆原创鈥檚 Billing Assistant brings greater intelligence to this critical process, helping identify potential issues earlier so our people can deliver better client outcomes and build stronger relationships,鈥� said Jill Notz, Chief Accounting Officer, Controller, Business Services Leader, PwC. Building on the success of the Billing Assistant, PwC and 麻豆原创 are into new areas of joint AI innovation.

麻豆原创’s Autonomous Enterprise Scales Up

Joule Work is beginning its customer rollout as a new AI user interface that lets employees interact with 麻豆原创 solutions in their own language and complete work across 麻豆原创 and third-party data. Grounded in business context from 麻豆原创 Knowledge Graph, which maps more than 7 million data fields, Joule provides information users can rely on. At 麻豆原创, Joule Work is already live with 110,000 employees, with the company seeing 20% productivity gains across finance, HR and procurement. A select group of customers also is using Joule Work in their business environments.

• 鈥淧artnering within the Early Adopter Program for Joule Work Desktop has delivered more momentum in just a few months than we saw in all the years before,鈥� said Peter Wied, Director of Complexity Management at Reinhausen. 鈥淲e see huge potential in making access to our 麻豆原创 S/4HANA data significantly easier and faster through natural language. This has the potential to permanently transform how our teams interact with business data.鈥�
• 鈥淭he dedicated team has been phenomenal. Their proactive communication, focus on accelerating architecture activation, rapid remediation of defects and overall support have enabled us to become Joule ready much sooner than would have been possible had we needed to navigate these challenges on our own,鈥� said Keith Smith, 麻豆原创 Platform Architect, CONA Services. 鈥淭he CONA team is excited about the progress made to date and looks forward to exploring and testing Joule’s capabilities in greater depth over the coming months as we continue our adoption journey.鈥�

When a query is not enough, Joule Assistants execute operational work directly within business workflows, using established data, authorizations and audit trails. Customers control the level of autonomy. 麻豆原创’s approach is also open: through the Agent2Agent protocol, Joule can connect with third-party AI and agents, bringing governed business context into broader AI workflows.

At 麻豆原创 Connect, 麻豆原创 showcased how these capabilities generate outcomes across 麻豆原创 Autonomous Suite:

• In finance, controllers can automate revenue recognition, disclosures and trade compliance, with early deployments of the International Trade Assistant reducing trade classification effort by up to 50%.  
• In supply chain, planners can turn multi-hour disruptions into one-click resolutions across planning, manufacturing and logistics.
• In HR, leaders can determine the best way to close workforce gaps, while employees can make smarter benefits choices tailored to their needs.
• In procurement, decision-makers can identify savings opportunities against peer benchmarks and manage the full contingent workforce life cycle.
• In customer experience, organizations can turn customer engagement into sales opportunities with AI-powered campaigns, quoting and customer workflows.
• Across industries, 麻豆原创 is collaborating with customers to apply AI to specialized industry processes, helping organizations in manufacturing, retail, commodity trading and asset-intensive industries improve decision-making, automate routine actions and build more resilient operations.

The Platform Powering Business AI You Can Trust

麻豆原创 Business AI Platform gives organizations one place to build, contextualize and govern AI across 麻豆原创 and third-party environments. With Joule Studio, business users and developers can build and extend skills and agents from no-code to pro-code workflows, choosing from more than 70 AI models. 麻豆原创 Business Data Cloud and 麻豆原创 Knowledge Graph ground those agents in trusted business data and context, helping organizations select the right model for each use case and better manage AI value and consumption.

麻豆原创-managed governance helps organizations scale AI with transparency, accountability and control. 麻豆原创 AI Agent Hub in 麻豆原创 LeanIX solutions provides a central inventory of enterprise agents, while 麻豆原创鈥檚 independently ISO/IEC 42001-certified governance architecture supports regulatory requirements, established authorizations and auditable AI operations.

To help organizations adopt AI at scale, 麻豆原创’s Business Transformation Management portfolio, including 麻豆原创 Signavio, 麻豆原创 LeanIX and 麻豆原创 WalkMe solutions, provides the toolchain to analyze processes, govern applications and agents, and drive adoption across the enterprise.

麻豆原创 Brings Embedded Payments to Cloud ERP

麻豆原创 also announced that it is entering the payments market with 麻豆原创 Pay, powered by Tereina, an 麻豆原创 company. Embedded directly in 麻豆原创 Cloud ERP, 麻豆原创 Pay executes and reconciles payments within the same workflow when an invoice is due, reducing manual file handling and external processing dependencies, while giving customers greater control.

Partners Expand the Reach of Autonomous Business

麻豆原创 is extending the Autonomous Enterprise beyond 麻豆原创’s own application portfolio through new partnerships that bring specialized intelligence directly into 麻豆原创 workflows.

A new partnership between 麻豆原创 and Moody鈥檚 Corporation is designed to embed Moody鈥檚 supplier risk monitoring data into 麻豆原创 Ariba Supplier Lifecycle and Performance. This gives procurement teams continuously updated insights into supplier financial health, operational risk and regulatory status at the point of decision. Organizations will be able to move from periodic risk reviews toward continuous monitoring, enabling Joule Agents to flag supplier risk signals and surface alternatives before disruption affects the business.

An expanded partnership with ORO Labs brings procurement orchestration to 麻豆原创 customers as a solution extension. 麻豆原创 Ariba Procurement Orchestration by ORO Labs is a purpose-built orchestration layer that connects procurement workflows end to end across heterogeneous enterprise environments, giving business users a seamless experience for intake, actions and visibility.

Visit the . Get 麻豆原创 news via  and .

About 麻豆原创

As鈥痑 global leader in enterprise applications and business AI, 麻豆原创 (NYSE: 麻豆原创)鈥痵tands at the鈥痭exus鈥痮f business and technology. For over 50 years, organizations have trusted 麻豆原创鈥痶o bring out their best by uniting business-critical鈥痮perations spanning finance, procurement, HR, supply chain, and customer experience. For more information, visit鈥�.

Note to editors:
To preview and download broadcast-standard stock footage and press photos digitally, please visit . On this platform, you can find high resolution material for your media channels.

For customers interested in learning more about 麻豆原创 products:
Global Customer Center: +49 180 534-34-24
United States Only: 1 (800) 872-1麻豆原创 (1-800-872-1727)

For more information, press only:
Aim茅e Leabon, +1 (212) 653-9600, aimee.leabon@sap.com, EDT
麻豆原创 麻豆原创 Room; press@sap.com

This press release was created with the assistance of artificial intelligence and has been reviewed by the editorial team.

This document contains forward-looking statements, which are predictions, projections, or other statements about future events. These statements are based on current expectations, forecasts, and assumptions that are subject to risks and uncertainties that could cause actual results and outcomes to materially differ. Additional information regarding these risks and uncertainties may be found in our filings with the Securities and Exchange Commission, including but not limited to the risk factors section of 麻豆原创鈥檚 2024 Annual Report on Form 20-F.
漏 2026 麻豆原创 SE. All rights reserved.
麻豆原创 and other 麻豆原创 products and services mentioned herein as well as their respective logos are trademarks or registered trademarks of 麻豆原创 SE in Germany and other countries. Please see  for additional trademark information and notices.
Please consider our . If you received this press release in your e-mail and you wish to unsubscribe to our mailing list please contact press@sap.com and write Unsubscribe in the subject line.鈥�

That’s why we’re proud that 麻豆原创 has been recognized as a Leader in the inaugural Gartner庐 Magic Quadrant™ for Workforce Management Technology.

We believe this recognition reflects 麻豆原创’s commitment to helping organizations connect workforce operations, workforce intelligence, and business outcomes through a unified human capital management (HCM) platform.听

Workforce management in the era of Autonomous HCM听

As organizations prepare for the next era of work, leaders need more than scheduling tools and time systems.听They need a connected understanding of their workforce.听

Who is available? What skills are needed? Where are emerging labor gaps? How can workforce decisions better support business priorities?听

These questions sit at the intersection of workforce management and workforce strategy.听

That’s听why workforce management plays听an important role听in 麻豆原创’s vision for听.听At听its core, Autonomous HCM is about helping organizations move more quickly from workforce insight to action.

Workforce management plays a critical role in that vision by providing the operational data and workforce visibility needed to make more informed decisions. 

By bringing workforce management together with core HR, payroll, talent management, and workforce planning, 麻豆原创 SuccessFactors solutions help organizations gain a more connected view of their workforce, streamline operations, and make more informed workforce decisions. 

Advancing workforce management 

麻豆原创 continues to invest in capabilities that help organizations connect scheduling, absence management, time and attendance, workforce planning, and workforce decision-making. Recent innovations include the general availability of , helping manufacturing and production organizations align labor demand, workforce availability, employee skills, and compliance requirements within a more connected scheduling experience. 

We also recently introduced a new , which helps employees and managers complete common workforce management tasks鈥攍ike automatically pre-filling time sheets, validating entries against compliance requirements in real time, and answering policy questions鈥攃utting employee time sheet completion effort by up to 40% and HR service tickets by up to 20%. 

For professional services organizations, this focus on streamlining time extends further. The new consolidated timesheet experience across 麻豆原创 S/4HANA Cloud Public Edition and 麻豆原创 SuccessFactors Time Tracking helps unify project time and HR attendance in a single flow from resource planning to revenue recognition.  

From frontline workers on the production floor to project professionals, these capabilities reflect 麻豆原创’s commitment to industry-specific depth in workforce management. 

Beyond workforce operations, 麻豆原创 recently introduced new workforce planning capabilities within , helping leaders connect workforce decisions directly to HR, business, and financial priorities through a unified planning foundation.  

In addition, AI-enabled organizational modeling capabilities can support scenario planning and impact analysis, enabling business and HR leaders to evaluate organizational changes and workforce decisions before they are implemented. 

Together, these innovations help organizations connect workforce operations, workforce planning, and workforce decisions in new ways, supporting 麻豆原创’s broader vision for Autonomous HCM. 

Delivering meaningful outcomes 

Organizations across听more than听126听countries and 29听industries are using 麻豆原创 SuccessFactors workforce management solutions to help improve workforce visibility, streamline time and scheduling processes, strengthen compliance, and create better experiences for employees and managers.听

 deployed 麻豆原创 SuccessFactors Time Tracking to comply with new labor regulations requiring detailed workforce scheduling and time management. The organization achieved 99% clock-in and clock-out compliance, reduced neglected clock-outs by 44%, and decreased data-uploading errors by 25%, helping improve workforce visibility, compliance, and operational efficiency.  

 implemented 麻豆原创 SuccessFactors Time Tracking, 麻豆原创 SuccessFactors Employee Central, and payroll solutions to support a global workforce of 10,000 employees. By automating time management, overtime calculations, and payroll processes, the company achieved 40% operational savings, improved compliance, and delivered greater flexibility across HR and workforce operations. 

These examples illustrate how workforce management is becoming a strategic capability that helps organizations connect workforce operations with broader business priorities. 

Looking ahead听

We believe our recognition as a Leader听in听the Gartner庐 Magic Quadrant™ for Workforce Management Technology reflects 麻豆原创’s continued investment in helping organizations build more connected, agile, and resilient workforces鈥攁nd the trust of our customers, partners, and teams whose collaboration and innovation help shape what’s next.听

With many organizations actively reviewing their workforce management technology,听there’s听never been a better time to see what 麻豆原创 can offer.听

Discover why 麻豆原创 is recognized as a Leader in  and learn more about .

Gartner, Magic Quadrant for Workforce Management (WFM) Technology, By听,听,听,听, 14 September 2026
Gartner does not endorse any company, vendor, product or service depicted in its publications, and does not advise technology users to select only those vendors with the highest ratings or other designation. Gartner publications consist of the opinions of Gartner鈥檚 business and technology insights organization and should not be construed as statements of fact. Gartner disclaims all warranties, expressed or implied, with respect to this publication, including any warranties of merchantability or fitness for a particular purpose.
Gartner and Magic Quadrant are trademarks of Gartner, Inc., and/or its affiliates.

As AI reshapes the way organizations attract, develop, and support talent, leaders need more than systems of record. They need intelligent solutions that help them understand what’s happening across their workforce, anticipate what’s next, and take action with confidence.

We believe this recognition reflects 麻豆原创’s continued investment in AI-powered innovation across 麻豆原创 SuccessFactors solutions and our commitment to helping organizations build a more connected, intelligent, and proactive approach to workforce management.

鈥淎I is rapidly expanding what HCM platforms can do, but buyers need providers that combine innovation with real operational depth and consistent execution,鈥� said David Wilson, CEO and founder of Fosway Group. “麻豆原创 SuccessFactors has accelerated its rollout of AI features across HCM and expanded its integration with AI agents, offering more options to HR leaders. It is a Strategic Leader in the 2026 Fosway 9-Grid™ for Cloud HR, and 麻豆原创鈥檚 Excelling Trajectory in 2026 reflects its increased market performance and customer advocacy as well as continued innovation in both AI and core capabilities.”

Building the foundation for Autonomous HCM

This recognition comes at a pivotal moment for HR.

As AI continues to reshape work, organizations are moving beyond questions of efficiency and automation and focusing on a broader challenge: how to build more agile, adaptable, and resilient workforces.

The next era of HCM will be defined not by automating processes, but also by helping organizations make better decisions. That’s why we introduced our vision for Autonomous HCM earlier this year at 麻豆原创 Sapphire.

As part of 麻豆原创’s broader vision for the Autonomous Enterprise, Autonomous HCM brings together trusted workforce and business data, embedded AI, and HR processes to help organizations connect workforce decisions more closely to business outcomes.

As skills requirements evolve and business priorities shift, leaders need more than workforce data. They need the ability to understand implications, evaluate options, and act quickly.

At its core, Autonomous HCM is about closing the gap between knowing and doing. By bringing together workforce data, business context, and AI, organizations can move from understanding workforce challenges to taking action on them.

Traditionally, organizations have relied on reports, dashboards, and manual processes to identify workforce issues and determine next steps. While these tools provide valuable insights, they often leave leaders to interpret information and coordinate actions across disconnected systems and processes.

Autonomous HCM envisions a different approach. By combining AI, workforce intelligence, and business context, organizations can surface recommendations, automate routine work, and help employees, managers, and HR teams take action directly within the flow of work.

Whether identifying emerging skills gaps, recommending learning opportunities, supporting hiring decisions, streamlining employee support, or helping managers respond to workforce trends, AI can help organizations move more quickly from insight to action and achieve better outcomes.

Turning AI into action

Over the past year, 麻豆原创 has continued to invest in innovations that help organizations connect workforce insights with better decisions and outcomes, including:

• , helping employees, managers, and HR teams get work done more efficiently
• , bringing workforce and business data together to support better decision-making
• , helping streamline HR service delivery and employee support
• The acquisition of SmartRecruiters, extending our connected HCM approach to talent acquisition by linking hiring decisions more closely to workforce planning, skills intelligence, and the broader employee lifecycle

Next month at , we’ll share new innovations and customer stories that demonstrate how organizations are using our solutions to adapt more quickly to change, create more agile workforces, and move toward the vision of Autonomous HCM.

Delivering meaningful outcomes

The journey toward Autonomous HCM is already underway for many organizations.

is using 麻豆原创 SuccessFactors solutions and Joule to transform payroll and employee support experiences. By implementing AI capabilities, such as Explain Pay, the company has reduced payroll processing time by 90%, from five days to four hours, and expects to reduce payroll support costs by 80% while delivering faster, more personalized assistance to employees.

is embracing AI as part of its broader workforce transformation strategy. Through 麻豆原创 SuccessFactors solutions and Joule, the company is using AI to support talent acquisition, skills development, and employee growth while creating a more personalized and accessible employee experience. The company is also advancing its journey toward becoming a skills-based organization, using AI to help connect people with learning and development opportunities.

These examples highlight how organizations are using AI not just to automate work, but to improve decision-making, enhance employee experiences, and create measurable business value. They also demonstrate how the journey toward Autonomous HCM is already taking shape across organizations today.

Looking ahead

AI is creating new opportunities for organizations to rethink how work gets done and how people can thrive.

Our focus remains on helping organizations connect workforce insight with action through trusted data, embedded AI, and end-to-end HR processes. By bringing together workforce and business data in a unified foundation, 麻豆原创 SuccessFactors solutions help organizations build toward Autonomous HCM and create better outcomes for employees and the business.

We are grateful to our customers whose trust, partnership, and innovation make recognitions like this possible.

听and how 麻豆原创 SuccessFactors solutions are helping organizations build the foundation for Autonomous HCM and the future of work.听

About the Fosway 9-Grid™
Fosway Group is Europe鈥檚 #1 HR industry analyst. The Fosway 9-Grid™ is a five-dimensional market analysis model that helps organisations compare solutions based on Performance, Potential, Market Presence, Total Cost of Ownership and Trajectory.
The Fosway 9-Grid™ for Cloud HR provides a unique assessment of the principal Cloud HR options available to organizations in EMEA. The analysis is based on extensive independent research and insights from Fosway鈥檚 Corporate Research Network of over 250 organizations, including BP, HSBC, PwC, Sanofi, Shell, and Vodafone.
Visit the Fosway website at .

The deployment听brings together听core听human resources (HR)听processes听on听a听flexible听cloud foundation designed to听simplify听HR听operations, enhance employee experience and听support听a听global workforce.听

A leader in aerospace, defense and advanced technology solutions, Lockheed Martin is modernizing its听HR听landscape by moving from legacy systems to a unified platform. The new environment provides a more connected experience for employees and managers听while supporting听greater consistency and operational efficiency听across the enterprise.听听

With听almost听60%听of听its听123,000 employees听being听engineers, scientists and technologists,听attracting, developing and retaining highly skilled talent听at scale听is听critical to Lockheed Martin鈥檚听continued success.听By creating a single source of truth for workforce data, Lockheed Martin is听gaining clearer insight into its workforce, enabling听more informed听talent decisions.听

This transformation听allows Lockheed Martin听to accelerate its robust applied AI strategy across the workforce听to help听employees and managers access information more efficiently and unlock new insights across the employee life cycle.听

鈥淟ockheed Martin is advancing an听enterprise-wide听transformation of exceptional scale and complexity,听while meeting the rigorous demands of a highly regulated industry,鈥� said听Thomas Saueressig, Member of the Executive Board and Chief Customer Officer听of 麻豆原创 SE.听鈥淭his milestone reflects Lockheed Martin’s commitment to modernizing workforce operations and investing in technologies that support employees, strengthen organizational agility and position the company for future innovation.鈥�

Visit the听. Get 麻豆原创 news via听听and听.

Media Contact:
Victoria Dixon, +1 (703) 288-6020, victoria.dixon@sap.com, ET
麻豆原创 麻豆原创 Room; press@sap.com

Top image courtesy Lockheed Martin

This document contains forward-looking statements, which are predictions, projections, or other statements about future events. These statements are based on current expectations, forecasts, and assumptions that are subject to risks and uncertainties that could cause actual results and outcomes to materially differ.鈥� Additional information regarding these risks and uncertainties may be found in our filings with the Securities and Exchange Commission, including but not limited to the risk factors section of 麻豆原创鈥檚 2025 Annual Report on Form 20-F. 
漏 2026 麻豆原创 SE. All rights reserved.  
麻豆原创 and other 麻豆原创 products and services mentioned herein as well as their respective logos are trademarks or registered trademarks of 麻豆原创 SE in Germany and other countries. Please see  for additional trademark information and notices.  

Payroll presents a unique paradox. It鈥檚 one of the business functions most suited to AI and automation because it鈥檚 highly structured, data-intensive, and compliance-driven. At the same time, it鈥檚 one of the most trust-sensitive functions in the enterprise because even small errors can have immediate consequences for employees’ financial well-being and confidence in their employer.

Payroll professionals often joke that nobody notices payroll when it goes right, and everyone notices when it goes wrong. Behind that observation is an important reality: every payroll run becomes a moment of trust between employer and employee. That trust has measurable consequences. According to new research* by 麻豆原创鈥檚 , 38% of employees worldwide have experienced a payroll error. These employees are significantly less likely to trust both their organization (13% lower trust) and their payroll function (17% lower trust). Trust declines even further with each additional payroll error experienced.

As National Payroll Week takes place across both the and the , we have an opportunity to recognize the payroll professionals who earn and maintain that trust every day, while reflecting on the transformation taking place across the payroll function itself.

As payroll teams navigate growing complexity, they’re being asked to do more with less while maintaining the accuracy, compliance, and reliability employees depend on. Employees increasingly expect faster, more flexible payroll experiences, including more frequent pay cycles and greater visibility into earnings and deductions, while tax laws, wage rules, leave requirements, and reporting obligations continue to evolve across countries, states, and local jurisdictions. At the same time, today’s workforce is more dynamic than ever, with employees changing roles, locations, schedules, and compensation arrangements in ways that can create downstream payroll impacts. Managing these changes manually is becoming increasingly difficult and raising the risk of errors, delays, and compliance gaps, positioning payroll not simply as an administrative process, but as strategic infrastructure supporting employee experience, compliance, finance, and business operations.

This combination of rising complexity and rising expectations is driving the next evolution of payroll: autonomous payroll.

Scaling trust in an era of complexity

Autonomous payroll is designed to help organizations navigate growing payroll complexity while maintaining accuracy, compliance, and confidence at scale. By combining AI, intelligent automation, integrated data, and real-time payroll monitoring, organizations can move beyond reactive payroll operations and proactively identify issues before they affect employees.

The goal isn’t to remove people from payroll, but to enable them to focus on higher-value activities by reducing manual effort and increasing visibility. Our global research suggests that employees do not see AI and human involvement as mutually exclusive. In fact, nearly half (49%) say they would trust AI in payroll more if they still had access to a human when AI fails. Additionally, 43% of employees say that the ability to request a human review of AI-generated outcomes would increase their trust in the use of AI in payroll. Trust is built not only through accuracy and efficiency, but also through the confidence that employees can escalate concerns, seek clarification, and access human support when needed.

Emerging capabilities such as AI-powered payroll agents and continuous payroll are helping organizations move from processing payroll to actively managing it. These capabilities can assess payroll readiness, detect anomalies, validate changes, and monitor workforce events across HR, payroll, and time data. By identifying how changes in roles, locations, schedules, compensation, or leave may affect payroll outcomes, organizations can anticipate impacts and resolve exceptions before they become costly errors. The result is improved reliability, stronger compliance, and greater trust across the workforce.

The shift is significant. Rather than finding errors at the end of a payroll cycle, organizations can increasingly investigate and resolve them throughout the cycle. But technology alone isn’t enough. As payroll becomes more autonomous, organizations must ensure intelligent systems operate with appropriate oversight, transparency, and accountability.

Automation requires accountability

As AI becomes more embedded in payroll operations, the conversation shifts from adoption to accountability. Trust becomes paramount, raising important questions about where AI can operate autonomously, where human review adds value, and where human accountability must remain visible.

Our global research shows that employee comfort with AI varies by payroll task. Employees are most comfortable with AI supporting calculation-heavy activities such as payroll calculations and anomaly detection, while they prefer human involvement for tasks requiring judgment, investigation, or employee interaction. Final decisions on payroll disputes remain the area where employees most strongly prefer a human. These findings reinforce an important point: the goal is not to replace human expertise, but to apply AI where it adds the most value while preserving human oversight where trust and judgment matter most.

The most successful applications of AI in payroll won’t simply automate tasks. They’ll strengthen trust by improving consistency, reliability, transparency, and the overall payroll experience employees depend on.

In other words, the future of payroll isn’t human or AI. It’s human expertise amplified by AI.

Building the foundation for Autonomous HCM

The implications of autonomous payroll extend well beyond payroll operations.

At 麻豆原创, we believe autonomous payroll is a key enabler of Autonomous HCM. Trusted AI experiences depend on trusted data, connected processes, and embedded intelligence, and payroll plays a critical role in making that vision possible.

Every hiring decision, compensation adjustment, promotion, workforce change, or organizational initiative ultimately affects payroll. As a result, payroll remains one of the most trusted and comprehensive sources of workforce data across the enterprise.

Realizing the full potential of autonomous payroll requires a unified foundation across HR, payroll, and time data. When organizations establish a single source of truth, they can reduce complexity, improve payroll accuracy, strengthen compliance, and enable AI to deliver more meaningful insights and recommendations.

This foundation is essential because AI cannot solve payroll challenges if it鈥檚 simply layered on top of fragmented systems and disconnected processes. Instead, organizations need connected data and integrated workflows that allow intelligence to operate across the entire workforce lifecycle.

When payroll, HR, and time data come together on that foundation, organizations can create more intelligent workforce experiences, make better decisions, and increase organizational agility.

Looking ahead

National Payroll Week is an opportunity to celebrate the professionals who keep one of the most important business functions running every day. It’s also an opportunity to recognize how dramatically that function is evolving.

For decades, payroll was viewed primarily as an administrative necessity. Today, it is increasingly recognized as a strategic capability that influences employee experience, compliance, operational resilience, and organizational trust.

The organizations that lead in the years ahead won’t simply process payroll more efficiently. They’ll create payroll operations that are more intelligent, more connected, and better positioned to support both employees and the business.

As payroll continues its evolution from a transactional function to a strategic business capability, the opportunity is not simply to automate existing processes. It’s to build payroll operations that can scale trust, resilience, and confidence in an increasingly complex world.

Because when payroll works, it does more than deliver pay. It helps build confidence in the organization behind it.

Discover how helps organizations simplify payroll, reduce complexity, and accelerate their journey to autonomous payroll.

*Data from a global survey of 1,576 full-time employees in July 2026.

We believe this recognition reflects our ongoing commitment to helping organizations navigate an increasingly complex world of work through innovation, global scale, and AI that helps connect workforce decisions to business outcomes. 

A new era of HCM 

Organizations today face unprecedented workforce challenges.

Skills requirements are evolving rapidly. Workforces are becoming increasingly distributed. Business priorities shift faster than traditional planning cycles can accommodate. At the same time, leaders are being asked to make workforce decisions with greater speed, precision, and confidence. As these pressures increase, the role of HR and HCM technology is fundamentally changing.

Organizations no longer need systems that simply record workforce data or automate HR processes. They need connected, intelligent systems that can help anticipate workforce needs, surface recommendations, remove friction from everyday work, and help people make better decisions. This is why we announced our vision for Autonomous HCM at 麻豆原创 Sapphire in May.

As part of 麻豆原创’s broader vision for the Autonomous Enterprise, Autonomous HCM brings together trusted workforce and business data, embedded intelligence, AI, and HR processes to help organizations respond more effectively to changing workforce needs. The goal is not simply to automate more tasks. It’s to help organizations understand what’s happening, determine what to do next, and execute with greater speed and confidence. Achieving this requires trusted workforce and business data working together to provide the context needed for better decisions and better outcomes. 

Bringing Autonomous HCM to life

Over the past year, 麻豆原创 has continued to invest in capabilities designed to help organizations move more seamlessly from workforce insight to workforce action. From new Joule and AI agents to and , these capabilities help connect workforce intelligence, decision-making, and execution across HR processes. Our acquisition of SmartRecruiters extends this approach to talent acquisition, helping connect hiring decisions to workforce planning, skills intelligence, and the broader employee lifecycle. Next month at at 麻豆原创 Connect, we’ll share new innovations and customer stories that further demonstrate how 麻豆原创 SuccessFactors can help organizations automate work, adapt more quickly to change, and drive better workforce outcomes, ultimately moving towards Autonomous HCM.

Creating measurable impact

Organizations around the world are already working towards this reality.

has embedded AI capabilities within 麻豆原创 SuccessFactors solutions to support employee development, goal setting, recruiting, and career conversations. By giving employees and managers access to AI-assisted tools and insights, Timken is simplifying HR processes, improving employee development conversations, and enabling more informed workforce decisions.

is demonstrating how AI can help organizations move from workforce insight to workforce action. With 麻豆原创 SuccessFactors solutions, the company has streamlined recruiting processes across more than a dozen industries, reducing recruitment duration by 75% and improving hiring efficiency fourfold. AI-generated job descriptions, competency-based interview questions, and workforce insights are helping create a more efficient, consistent, and skills-based approach to talent management.

These examples demonstrate an important shift. AI is no longer limited to providing information. It’s helping employees, managers, and HR teams make better decisions and take action more quickly and effectively.

Looking ahead

We are grateful to our customers whose continued trust and innovation make this recognition possible.

As we look ahead, our focus remains on helping organizations connect workforce insight with action, enabling leaders to make better decisions, respond more quickly to change, and create better outcomes for employees and the business. about our position in the 2026 Gartner庐 Magic Quadrant™ for HCM Suites for 1,000+ Employee Enterprises.

Gartner, Magic Quadrant for HCM Suites for 1,000+ Employee Enterprises, By , , , , , , 31 August 2026 
Gartner does not endorse any company, vendor, product or service depicted in its publications, and does not advise technology users to select only those vendors with the highest ratings or other designation. Gartner publications consist of the opinions of Gartner鈥檚 business and technology insights organization and should not be construed as statements of fact. Gartner disclaims all warranties, expressed or implied, with respect to this publication, including any warranties of merchantability or fitness for a particular purpose. 
Gartner and Magic Quadrant are trademarks of Gartner, Inc., and/or its affiliates. 

As a result,听people听analytics is evolving from a reporting function into a strategic capability. By connecting workforce, skills, talent, and business data, organizations can gain a deeper understanding of their workforce and anticipate future talent needs.听听

This听evolution is helping lay the foundation for听Autonomous HCM,听where connected data and AI-powered intelligence help organizations make more informed workforce decisions.听

People analytics: a cornerstone of Autonomous HCM 

The future of HR isn’t simply about automating processes. It’s about providing leaders with the workforce intelligence needed to align talent strategies with business priorities. Industry research, including the , points to growing demand for solutions that bring together people analytics, workforce planning, performance data, and AI-powered insights. Together, these capabilities can help organizations move from reactive decision-making to a more proactive and strategic approach to workforce management. For HR leaders, that means spending less time gathering and reconciling information and more time focusing on actions that improve workforce performance, organizational agility, and business results. 

Connecting workforce insights to business outcomes 

At 麻豆原创, our vision for Autonomous HCM starts with connecting workforce and business data to create a shared understanding of people, skills, and organizational priorities.听Through听, organizations can bring together workforce, skills, talent, operational, and business data to gain a more complete view of their workforce,听identify听emerging opportunities and risks,听anticipate听future talent needs, and make decisions with greater context.听听

This outcomes-based approach helps organizations answer critical questions like:听What capabilities exist across the workforce today, and where are critical gaps听emerging?听What skills will be needed to support future business goals?听How can talent be aligned more effectively to strategic priorities? Where are emerging workforce and retention risks? What actions can help improve workforce and business performance?听

From workforce intelligence to workforce action 

麻豆原创 is transforming its own approach to people analytics through People Intelligence. By bringing workforce and business information together, leaders can move beyond static reporting and better understand workforce trends, skills needs, and organizational priorities.  

Traditionally, acting on workforce insights has often been a manual and fragmented process. HR teams听identify听an issue, such as a skills gap or retention risk, and then coordinate across recruiting, learning, workforce planning, and business leaders to听determine听and execute the听appropriate response. While analytics can help surface the problem, turning insight into action frequently requires significant time, effort, and cross-functional collaboration.听

The听next evolution is connecting intelligence directly to action.听As AI becomes more deeply embedded in workforce processes, organizations can move beyond听identifying听a workforce challenge to听exploring听potential responses and acting on approved decisions. For example, workforce intelligence could听identify听an emerging skills gap, help leaders evaluate different ways听to address it, and connect those decisions to actions across hiring, learning, internal mobility, or workforce听planning.听

Over听time, AI agents will help accelerate this shift听by connecting workforce intelligence with the actions needed to address it, helping organizations move more seamlessly from insight and decision to听execution.听

The path forward for Autonomous HCM 

People analytics helps organizations understand what is happening. Workforce intelligence helps them decide what to do next. Autonomous HCM helps them act by connecting insights, decisions, and execution. 

The future of workforce management is not just about understanding workforce dynamics, but about helping organizations respond with greater speed, confidence, and precision. By connecting听people听analytics, workforce intelligence, and AI-powered execution, Autonomous HCM enables organizations to move听beyond insight to action, creating a more adaptive, resilient, and business-aligned workforce.听

Learn more 

Explore the  to learn more about the trends shaping the future of workforce intelligence, planning, and decision-making, and why 麻豆原创 was recognized as a Leader. 

NTT DATA is a $30+ billion global leader in AI, digital business and technology services, serving 75% of the Fortune Global 100.

The 麻豆原创 solutions will help NTT DATA replace multiple legacy HR systems with one unified platform for people data and processes, strengthening decision-making, employee experience and workforce planning. 麻豆原创 SuccessFactors solutions will serve as the system of record for people and talent data, working alongside NTT DATA’s existing employee service platform and specialist workforce planning tools. 麻豆原创 Business Data Cloud will connect this data with insights across other business functions.

鈥淭he initiative reflects NTT DATA’s view of talent as a strategic differentiator and AI as a capability that should be embedded across enterprise organizations,鈥� said Stijn Nauwelaerts, Chief People Officer, NTT DATA, Inc. 鈥淯ltimately, this is about creating an environment where our people feel empowered to do their best work, wherever they are in the world.鈥�

The deployment builds on a strategic partnership between 麻豆原创 and NTT DATA spanning more than 36 years, during which NTT DATA has collaborated as an 麻豆原创 platinum partner, global service partner and global reseller for 麻豆原创. In 2025, NTT DATA adopted 麻豆原创 Cloud ERP Private solutions to modernize its core systems.

麻豆原创 SuccessFactors solutions will now be deployed internally at NTT DATA over a 12-month period, with the company applying its own 麻豆原创 expertise to design and roll out the platform. This will create a single, authoritative source of HR data and processes, laying the foundation for faster, more consistent HR services across the organization. Leading its own implementation will also strengthen NTT DATA’s ability to guide clients through AI-driven HR transformation, with firsthand experience of the solutions it delivers.

鈥淣TT DATA is demonstrating how AI and cloud technology can redefine the employee experience,鈥� said Thomas Saueressig, Chief Customer Officer and Member of the Executive Board of 麻豆原创 SE. 鈥淲ith a unified, intelligent HR platform, the company will unlock new levels of productivity and scale a people strategy that supports a connected workforce worldwide.鈥�

Visit the . Get 麻豆原创 news via  and .

Media Contacts:
Lawrie Benfield,听lawrie.benfield@sap.com,听+44 7776 515259, GMT
Sonya Domanski,听sonya.domanski@sap.com, +44 734 546 5928, GMT
麻豆原创 麻豆原创 Room; press@sap.com

This document contains forward-looking statements, which are predictions, projections, or other statements about future events. These statements are based on current expectations, forecasts, and assumptions that are subject to risks and uncertainties that could cause actual results and outcomes to materially differ. Additional information regarding these risks and uncertainties may be found in our filings with the Securities and Exchange Commission, including but not limited to the risk factors section of 麻豆原创鈥檚 2024 Annual Report on Form 20-F.
漏 2026 麻豆原创 SE. All rights reserved.
麻豆原创 and other 麻豆原创 products and services mentioned herein as well as their respective logos are trademarks or registered trademarks of 麻豆原创 SE in Germany and other countries. Please see for additional trademark information and notices.

Operating within a complex landscape that spans all aspects of ERP, including HR with 麻豆原创 SuccessFactors HCM, 麻豆原创’s People Analytics team faced growing demand for HR data and insights鈥攆rom HR, as well as Sales, Finance, and Operations. What started as a challenge soon became an opportunity for a more governed, self-service approach.

Centralized dashboards hit their ceiling

For years, 麻豆原创’s People Analytics function operated from a centralized model focused on the consumption layer: building, maintaining, and optimizing dashboards tailored to specific business requirements. The MyTeam Dashboard鈥攁 360-degree view of workforce data available to every people manager at 麻豆原创, covering upcoming birthdays, salary, and performance information鈥攂ecame the company’s single most used report. That success was a testament to how much the business valued easy access and visibility into key HR data.

But it also revealed the limits of the model. As demand grew, the analytics team found itself permanently on the defensive, saying 鈥渘o鈥� far more than 鈥測es,鈥� managing backlogs of individual KPI additions, and negotiating timelines for incremental changes. Furthermore, data management, maintenance, and governance proved to be a challenge. The centralized dashboard approach could not scale to meet the breadth of data needs across an organization of 麻豆原创’s size and complexity.

The solution: using data products with People Intelligence in 麻豆原创 Business Data Cloud

麻豆原创 IT made a strategic decision to shift the center of gravity in its analytics architecture, moving to govern and open up the data layer beneath the consumption layer. At the heart of this change is the data product, a managed asset that ingests data from systems, transforms it, and exposes it in a governed, reusable form so downstream analytics can rely on consistent, trusted building blocks.

Data products fall into two categories: primary data products, which are sourced directly from transactional systems, such as a job structure data product from 麻豆原创 SuccessFactors HCM, and derived data products, which combine these primaries to answer broader questions. An example of this is a total employee and external workforce data product that fuses multiple sources into a single, harmonized view.

This is where in 麻豆原创 Business Data Cloud became transformative for 麻豆原创鈥檚 People Analytics team. Rather than building all foundational HR data products from scratch, People Intelligence delivers a catalog of pre-built, 麻豆原创-tested data products and derived insights directly on top of 麻豆原创 SuccessFactors HCM. Workforce composition insights alone include , encoding hundreds of joins, tested and documented by 麻豆原创 product teams, which is complexity that even AI-assisted modeling tools cannot yet reliably replicate without extensive testing and governance work.

麻豆原创 IT’s approach is deliberate: adopt 麻豆原创-delivered data products out of the box, build differentiating derived products on top, and free IT capacity for what actually differentiates and optimizes 麻豆原创’s HR processes.

Data sensitivity is also top of mind for the 麻豆原创 team. With People Intelligence, the same data product is made available in multiple “flavors”鈥攁 full PII (personally identifiable information) view and a mini view with common company-visible information鈥攈elping to ensure the right data reaches the right consumer in the right format. This is especially useful with regards to Works Council鈥檚 sensitivity requirements of PII data. This data governance can help humans and agents work with the data in a compliant way.

鈥淭here is a meaningful difference between data you can trust and data sourced informally,鈥� Oliver Huth, head of Platform, Corporate Functions, & Analytics at 麻豆原创, states. 鈥淏uilding that trust at scale is what the shift to data products鈥攑owered by People Intelligence in 麻豆原创 Business Data Cloud鈥攊s making possible for our teams at 麻豆原创.鈥�

What鈥檚 changed and what鈥檚 coming

The outcome for both IT and the business is clear. 麻豆原创 IT populated its internal data product catalog rapidly, reaching the critical mass needed for broad adoption. HR data that was previously locked behind dashboard requests now powers use cases across functions. For 麻豆原创鈥檚 business teams, the outcome is faster time to insight. Pre-built intelligent content in People Intelligence serves as an 80% starting point for business conversations, replacing blank-sheet requirement gathering with focused discussions. Leaders and managers can also access personalized KPI views through MyMetrics, choosing a KPI, seeing an overview and AI summary, and jumping to the dashboard if additional information is needed. Users can also turn to Joule to ask questions in natural language and get replies with visualized charts. This pre-built, self-service approach has significantly reduced the volume of HR data inquiries and dashboard requests

麻豆原创鈥檚 next steps for People Intelligence include recreating the MyTeam Dashboard by composing it from the readily available data products.

In addition, 麻豆原创 IT is very excited to adopt AI agents that can operate directly on top of governed data products, querying a variety of data including employee, salary, and skills. As Huth notes, “Investing in a data product strategy is the essential first step. It is what enables governed data access and produces AI-ready models as a result.” 麻豆原创’s standard development teams are currently building Joule Assistants and Joule Agents, including a People Intelligence Assistant to be released in November 2026

Learning from 麻豆原创鈥檚 experience

For HR and people analytics teams facing growing data demand, fragmented access, and the pressure to deliver more with less, 麻豆原创 IT’s experience offers a clear road map: adopt People Intelligence in 麻豆原创 Business Data Cloud, use 麻豆原创-delivered data products out of the box, invest now in a governed data product architecture, and treat intelligent content as a starting point. This can improve analytics delivery today and is the infrastructure that will make AI agents trustworthy tomorrow.

.

Fewer opportunities for early talent 

The job marketplace has contracted significantly for those with less than five years of professional experience. Research published by 麻豆原创 shows that openings in the 10 most common entry-level job titles declined by 35% in just one year, from 2024 to 2025.*

Budget constraints, hiring freezes, and uncertainty around the ROI of early talent as AI increasingly takes on routine and manual tasks are among the reasons cited by HR leaders today.  

Applications skyrocket  

AI is also having a major impact on the recruitment process. With such limited opportunities available, more than half of early talent candidates use AI to help them land a job鈥攁 process that now takes eight months on average and involves more than 300 job applications.*

HR is feeling the pressure managing the candidate pipeline, with听the number of applicants per early talent job opening doubling since 2021.听A听high volume of candidates听are听submitting听AI-generated r茅sum茅s and applications, and it鈥檚 becoming much harder to detect high-fidelity signals around skills, fit, and potential.听

It鈥檚听a painful听scenario for everyone involved. Fragile and unsustainable. And the听implications听will be听profound for enterprises that听don鈥檛听act quickly.听听

HR leaders voice concerns  

Playing out the current听trajectory听to its natural conclusion, what happens when all the听fresh talent eventually dries up? Already,听HR leaders听are alarmed by this risk.听鈥淯ltimately, if we stop investing in early talent, we will wind up eliminating our talent pipeline,鈥� one听global head of early talent听programs at a high-tech organization听told researchers.*

A senior HR director at a high-tech organization commented: 鈥淚f we continue down this path and don鈥檛 provide a way for early talent to get started, it鈥檚 going to lead to massive skill shortages in the future.鈥� 

Widespread reductions in early talent hiring will lead to skills gaps that听will听prove expensive to remedy. Organizations will struggle to build company capabilities,听retain听knowledge, and develop future leaders.听听

But by far the most common concern from leaders was around not seeing early talent as AI-native. If the AI capabilities of this cohort are overlooked, companies may miss out on a key opportunity to scale AI innovation and adoption across the business.  

What鈥檚 the answer?  

Today,听there鈥檚听an opportunity for HR leaders to be more intentional听and strategic, to reimagine听their approach听to early talent from the ground up. With the right early talent strategy, organizations can gain a competitive advantage.

Here are three steps to consider. 

Step 1: Rethink entry-level roles 

Traditionally, junior employees have mainly been given routine, repetitive tasks. Combined with frustratingly slow career progression, the result is eroding morale and commitment.  

This听approach must evolve.听The nature of work is changing rapidly,听and early talent no longer need to take on those routine tasks. These employees need the opportunity to develop at speed and to be supported in performing听work that听meaningfully addresses听business challenges.听听

HR has the chance to reshape entry-level positions,听to provide support, guidance, and tools to enable听junior staff听to contribute听in听more听impactful听ways. This may involve them听working听with proper guidance听to support听more critical听projects, interacting with customers,听and听even听owning some tasks end to end.听

This approach not only enables early talent to contribute more positively to the business at an earlier stage, but when combined with clear goals, regular feedback loops, and occasional coaching, it also fosters greater engagement and commitment. 

Step 2: Support your strategy with technology 

Hiring and developing early talent have become more complex鈥攆rom deciphering AI-generated applications, to redesigning roles and meeting their aspirations in a fast-changing business context. And with the nature of early talent work shifting, leaders need tools to help understand the new capabilities that will predict long-term success and demonstrate the value of early talent initiatives.  

Here鈥檚 where technology can help. During the hiring process,听technology听can help听employers听see beyond the听noise of听AI听applications听and rediscover the听meaningful听signals听they听need to create candidate shortlists and strengthen hiring decisions. Meanwhile, technology can also help to maintain engagement with other high-potential听candidates听who applied鈥攆or when the next opportunities arise.听听

Once early talent begin work, today鈥檚 technology can help you track their participation in early talent programs and progression towards their goals. It also helps facilitate individualized learning opportunities and demonstrate the ROI of your early talent investments. For research-based recommendations on the role of technology in early talent selection and development, check out this . 

Step 3: Reframe the business case for early talent 

As the nature of early talent work is changing alongside the technology used to support them, HR leaders agree that the old business case for early talent investments needs to be reimagined. Many organizations are focused on mitigating critical skill gaps and engaging in large-scale AI transformations. While early talent lack experience, they are eager to engage in continuous learning and understand how to work effectively alongside AI. 

Research also reveals that鈥攁s they work alongside modern tools and technologies鈥攅arly talent can contribute to high-value, meaningful work much faster than in the past.  

A modern early talent business case is one that involves focusing on faster time to meaningful work, reducing critical skill gaps, and leveraging the AI-native capabilities of today鈥檚 entry-level workers.  

Build your early talent strategy 

Will HR leaders watch on as a generation of AI-savvy talent remains underused, or act now and build the skills pipelines necessary for a future-ready workforce? 

Get further insights on this topic by reading our report, 鈥�.鈥�&苍产蝉辫;痴颈蝉颈迟&苍产蝉辫;辞耻谤&苍产蝉辫; to stay tuned for when phase two of this research gets published later this year. 

Dr. Autumn D. Krauss is chief scientist at 麻豆原创 SuccessFactors.

*, 麻豆原创, 2026. 

This recognition reflects 麻豆原创鈥檚 broader vision for AI-driven, skills-based workforce orchestration, where hiring is no longer a standalone process but part of a continuous, intelligent system connecting people, skills, and business outcomes. With innovations across 麻豆原创 SuccessFactors solutions and the addition of SmartRecruiters to the portfolio in September 2025, 麻豆原创 is enabling organizations to move beyond transactional recruiting toward agentic, autonomous talent strategies that continuously adapt to change.

SmartRecruiters for 麻豆原创 SuccessFactors: AI at the center of hiring

combines a modern, AI鈥憂ative recruiting platform with 麻豆原创鈥檚 core HCM to help create a more connected and intelligent hiring experience at global scale. Hiring becomes part of an integrated flow of workforce decisions鈥攍inked directly to skills, planning, mobility, and long-term business strategy.

With embedded AI across the hiring lifecycle, organizations can:

• Deliver intuitive, consumer鈥慻rade candidate experiences at scale, from first interaction through new hire onboarding.
• Empower recruiters and hiring managers with AI鈥慹nabled insights and automation directly within daily workflows.
• Strengthen hiring decisions by connecting recruiting data to skills, roles, and workforce plans.
• Scale globally with confidence, balancing centralized governance with local market flexibility.

SmartRecruiters鈥� AI hiring companion, Winston, works alongside to help automate repetitive tasks, surface top candidates, and explain recommendations transparently, which allows recruiters to focus on higher鈥憊alue decision鈥憁aking while moving faster and with greater confidence.

New capabilities, including agentic interviewing and real鈥憈ime candidate engagement, are helping organizations accelerate hiring while improving candidate experience at scale. For example, early adopters of AI鈥慸riven screening have seen up to a in time鈥憈o鈥慸ecision, demonstrating how AI can streamline evaluation without sacrificing quality.

At the same time, innovations like agentic CRM are helping organizations activate existing talent pools鈥攕urfacing, ranking, and re鈥慹ngaging candidates automatically鈥攖urning recruiting from a reactive process into a continuous, dynamic pipeline.

From recruiting to Autonomous HCM

SmartRecruiters plays a key role in 麻豆原创鈥檚 broader shift toward Autonomous HCM鈥攚here AI-driven agents can continuously orchestrate workforce decisions across hiring, planning, development, and mobility.

Rather than treating hiring as an isolated function, 麻豆原创 is embedding AI across 麻豆原创 SuccessFactors solutions to create a unified, skills-based system of action. Workforce planning, learning, and talent acquisition are directly connected, enabling organizations to align skills with business and financial priorities in real time.

At , this vision came to life through innovations that increase agility and responsiveness. Intelligent agents can identify skill gaps, recommend hiring or redeployment strategies, and take action鈥攖urning talent management into a dynamic, continuously optimized system.

Within this model, hiring becomes one of several coordinated levers in an adaptive workforce strategy, ensuring every decision is guided by real-time data, skills intelligence, and evolving business needs.

Customer impact: AI鈥慸riven hiring in action

Organizations across industries are already seeing the impact of AI鈥慸riven, connected hiring.

Retailer selected SmartRecruiters to improve the candidate experience and reduce drop-off in a high-volume hiring environment. Today, the company processes 50,000 applications each month, reducing the application processing time from 28 days to just four and cutting time-to-fill from 56 days to just 20鈥攄emonstrating how speed and experience directly improve hiring outcomes.

Global real estate services firm implemented SmartRecruiters to increase visibility into recruitment activity and create a more consistent experience across its EMEA business. As a result, Colliers achieved a direct hiring rate above 80%, reduced agency reliance to roughly 7% of hires, and improved first鈥憏ear retention by 25%, showing how connected hiring can lower costs while strengthening long鈥憈erm talent outcomes.

and discover how AI鈥慸riven, connected hiring can help turn talent acquisition into a true strategic advantage.

About the Fosway 9-Grid™
Fosway Group is Europe鈥檚 #1 HR industry analyst. The Fosway 9-Grid™ provides a unique assessment of the principal talent supply options available to organizations in EMEA. The analysis is based on extensive independent research and insights from Fosway鈥檚 Corporate Research Network of over 250 organizations, including BP, HSBC, PwC, Sanofi, Shell, and Vodafone. Visit the Fosway website at www.fosway.com for more information on Fosway Group鈥檚 research and services.

As one of the听industry鈥檚 most trusted independent听peer review听platforms,听TrustRadius听is known for its rigorous verification process and commitment to unbiased, customer鈥憀ed insights. These听awards are based听on real听user experiences,听making听them听especially meaningful.

This recognition reinforces a clear message: organizations are turning to听麻豆原创 SuccessFactors solutions not just to manage HR but to modernize it. As companies move towards more autonomous, AI-driven ways of working, they need HCM solutions that bring together data, insights, and action.听That鈥檚听exactly what the 麻豆原创 SuccessFactors portfolio can deliver.

Momentum across the portfolio

This year鈥檚听results highlight strong and growing momentum.

麻豆原创 SuccessFactors听increased from听12听Top Rated awards听in 2025听to 19听in 2026, reflecting听deeper customer satisfaction across听the HCM landscape.

Recognized categories include:

• HR Management
• Workforce Analytics
• Talent Management
• Compensation Management
• Workforce Management
• Applicant Tracking
• Talent Intelligence
• Corporate Learning Management
• Payroll
• International Payroll
• Pay Equity
• Recruiting Automation
• Employee Performance Management
• HR Compliance
• HR Service Delivery
• Employee Onboarding
• Succession Planning
• Diversity, Equity, and Inclusion (DEI)

This breadth reflects the strength of 麻豆原创 SuccessFactors solutions as a unified suite鈥攃onnecting people, processes, and data across the workforce. 麻豆原创听SuccessFactors听solutions can provide听the foundation to turn those connections into real-time insight and action.

What听our听customers are听saying

Across听thousands听of听verified听reviews,听customers听consistently听point to one thing: impact.听From operational efficiency to better decision-making and improved employee experiences, 麻豆原创 SuccessFactors solutions are helping organizations move faster and work smarter.

• 鈥淲ith 麻豆原创 SuccessFactors HCM AI, we get helpful, actionable insights to make the best decisions. For instance, the insights we gain help us streamline HR operations, especially when it comes to managing our payroll.鈥� 鈥斕�

• 鈥溌槎乖� SuccessFactors is our core platform and supports our finance and HR processes. We use every module for recruiting, compensation, and learning. It supports our HR transformation and lays the foundation for our data.鈥� 鈥斕�

• 鈥溌槎乖� SuccessFactors HCM stands out among other human capital management solutions due to its comprehensive suite of听cloud鈥慴ased听tools, strong global compliance capabilities, and seamless integration with other 麻豆原创 systems.鈥� 鈥斕�

• 鈥淔or enhancing employee experience, AI offers personalized recommendations for their learning and development, which increases their productivity and engagement.鈥� 鈥斕�

• 鈥溌槎乖� SuccessFactors HCM is considered a 鈥榖est of breed鈥� for a reason. The fact that it does allow for听in鈥慸epth听customization, and its ability to be tailored not only to individual business needs, but also it allows for best practice听follow鈥憉p听while ensuring organizations remain compliant with several legal requirements.鈥� 鈥斕�

• 鈥淲e听leverage听听(ECP)听for our payroll engine and for our payroll calculations.听Having ECP makes everyone’s life easier鈥� the payroll control center will simulate the payroll before you run the actual payroll. That gives you a lot of analytics and KPIs to analyze results or potential issues well in advance.鈥� 鈥斕�

• “In our organization, we mainly use Joule in 麻豆原创 SuccessFactors to automate and complete tasks through natural conversation, which听eliminates听manual steps. [It] plays听a big role in eliminating the constant back and forth and guesswork involved in finding accurate information, as well as completing routine tasks, for example, workforce insights, budget and planning, document retrieval, etc. Additionally, it makes navigating [麻豆原创听SuccessFactors] seamless.鈥� 鈥斕�

Looking听ahead

We鈥檙e听incredibly grateful to the customers that shared their experiences on听TrustRadius听with insights that continue to guide our innovation.

Building on听the听introduction of听Autonomous HCM at 麻豆原创 Sapphire,听our focus is clear: helping HR听move beyond managing听processes to听orchestrating work. By听bringing听together AI, data, and workflows, 麻豆原创 SuccessFactors solutions enable organizations to听operate听with greater speed, clarity, and confidence, so they can not only adapt to change but actively shape what comes next.

Learn more about the impact customers are seeing with听.

Lara Albert is chief marketing officer for 麻豆原创 SuccessFactors.

鈥淟ast year, we were in the process of planning the optimization of our talent discovery tech stack and then something happened,鈥� Eric Goldstein, global head of Talent Discovery for 麻豆原创, said. 鈥淲e acquired SmartRecruiters in September, so we had to pivot in an agile way.鈥�

SmartRecruiters for 麻豆原创 SuccessFactors enables enterprises to manage the entire hiring lifecycle, from sourcing to onboarding, with AI-enabled recruiting capabilities that can result in faster time-to-hire, improved candidate experiences, and deeper analytics for workforce planning.

For 麻豆原创, this means adding much-needed rigor and precision to its global talent acquisition operations. This will not only elevate the quality of hires but also the candidate experience, which Goldstein identified as the 鈥渂iggest game changer.鈥�

Building a more intelligent hiring process

SmartRecruiters for 麻豆原创 SuccessFactors helps optimize processes, increasing transparency and personalization. This means improved experiences and processes for candidates, hiring managers, and recruiters. 鈥淲e have been through a time where we focused solely on the recruiter experience. Then it was fashionable to focus only on the candidates. Now we really see that with SmartRecruiters, it really is an enhanced experience for all stakeholders that are involved in the recruiting process,鈥� Ilka Sagner-David, global head of Talent Discovery Solutions and Innovations at 麻豆原创, said.

Candidate perspective

Seventy percent of candidates that apply for jobs are mindful to take their valuable time to do so, Goldstein shared, reiterating that it is important for companies to match that commitment when shaping and delivering the candidate experience. With SmartRecruiters for 麻豆原创 SuccessFactors as the foundation, it becomes possible for every pre-qualified applicant to interview, receive personalized and constructive feedback post-interview, and maintain 24×7 interaction with agentic AI built into SmartRecruiters.

鈥淚n our opinion, only responding with polite, automated rejection notes is not enough. [Candidates] need to be provided with some constructive, actionable feedback鈥攁nd that鈥檚 what we [at 麻豆原创] are going to be able to do,鈥� Goldstein said.

Hiring manager perspective

SmartRecruiters for 麻豆原创 SuccessFactors can give hiring managers a more precise and consistent way to identify strong candidates, helping to reduce time-to-hire while improving hiring quality. AI-prompted interview questions focused on skills can support more relevant and structured conversations while greater transparency across interview panelists can create better alignment throughout the evaluation process. In addition, AI-supported feedback collection can make it easier for interviewers at 麻豆原创 to capture timely, consistent insights, enabling its hiring teams to make more informed decisions with greater confidence. 

Recruiter perspective

Recruiters are often bogged down by manual tasks, such as outreach, prospect identification, and candidate screening, making it nearly impossible for them to step into the role of a trusted advisor. With SmartRecruiters for 麻豆原创 SuccessFactors, recruiters can experience automated internal and external prospect identification, personalized outreach and prioritization of candidates, and, therefore, the ability to focus on higher value-add advisory and relationship management.

鈥淚t鈥檚 going to allow the recruiters to focus on relationship management with candidates and hiring managers, really challenging the feedback of how well the interview panel measures skills proficiency,鈥� Goldstein said.

Bringing AI into the candidate journey

A key to the successful delivery of these benefits is SmartRecruiters Winston for 麻豆原创 SuccessFactors, an AI-driven, candidate-facing agentic experience. At 麻豆原创 Sapphire Orlando, Karl Baert, global head of People Solutions for 麻豆原创, demonstrated how Winston can facilitate the application experience for candidates.

In the demo, he acted as a candidate applying for an open position at 麻豆原创, showing how through a natural language conversation with Winston, he completed his application by uploading his CV and verifying some personal details with Winston. 鈥淎ll that information is very, very quickly brought together so with just a few questions my application is done,鈥� Baert said, adding that 鈥渢here鈥檚 also a few checks happening along the way because we want to make sure the data we are collecting is the right quality.鈥�

Winston also collects feedback from the applicant. 鈥淢easuring the quality of your agent and what鈥檚 happening with it is important. It鈥檚 something that really needs to be actively monitored just to ensure that the information provided by the agent is accurate,鈥� Baert said.

鈥淭he implementation of SmartRecruiters is the foundation for infusing AI into our processes,鈥� Sagner-David said. But, she added, 鈥渨e shouldn鈥檛 just plan to transfer everything tomorrow, but ensure we鈥檙e liberating AI when it makes sense.鈥�

The next step

Currently, SmartRecruiters for 麻豆原创 SuccessFactors is being implemented into 麻豆原创鈥檚 HR systems for two phases of user acceptance testing, with the global go-live expected in September.

麻豆原创 bringing SmartRecruiters for 麻豆原创 SuccessFactors to life across its own organization is more than a technology rollout, it鈥檚 a glimpse into the future of hiring at scale: more intelligent, more human, and more connected. By combining AI, better experiences, and real-word enterprise rigor, 麻豆原创 is not only transforming how it hires but also helping to define what modern hiring can look like for companies everywhere.

Now, the countdown is on. By June 7, all 27 EU member states are expected to adopt the directive into national law, marking what many HR leaders are calling 鈥淒ay One鈥� of a new era in workplace transparency.  

But while the deadline is fast-approaching, many organizations are still far from operationally ready. Even though employers will be required to share pay information with both employees and candidates during the recruiting process, current practices suggest a significant gap. For example, across Europe, salary disclosure in job postings remains inconsistent and often limited, according to .

For HR leaders, the challenge is no longer understanding the directive鈥攊t鈥檚 executing on it with confidence.

The barrier to execution 

For many organizations, the challenge often starts with the state of their HR and compensation data. In multinational organizations, compensation data often spans multiple systems, payroll providers, spreadsheets, and local processes. Job classifications vary across countries, salary bands are not consistently defined, and workforce data remains siloed across regions. 

As a result, many organizations struggle to produce consistent pay comparisons, define standardized salary ranges, explain compensation decisions clearly, and generate accurate reporting across multiple countries.听

Without a connected and reliable workforce data foundation, pay transparency becomes difficult to operationalize at scale. 

Building a foundation for continuous transparency听听

The organizations making the most progress are focusing first on data consistency, workforce visibility, and connected HR processes. 

This is where technology is becoming critical. AI can help organizations move beyond manual reporting by identifying pay anomalies, surfacing unexplained pay variance, and accelerating workforce equity analysis across large, complex data sets. 

With pay transparency insights (generally available on June 5),  a capability within the  package in , organizations can unify compensation and workforce data across systems while applying AI-assisted analysis to help identify inconsistencies, support explainable pay decisions, and improve reporting readiness. 

Instead of relying on fragmented systems and disconnected reporting processes, organizations can move toward a more consistent and scalable approach to transparency. 

Three areas HR teams need to execute now 

With the right data foundation in place, organizations are better positioned to address the directive鈥檚 three major operational requirements. 

1. Enabling employee pay transparency 

Under the directive, employees have the right to request information about average pay levels by gender for comparable work. For many organizations, this听immediately exposes data consistency issues. Comparable roles may be classified differently across countries or听business units, while compensation data听often lives in disconnected systems that were never designed to work together.听

听helps organizations provide employees with pay transparency statements through听听while supporting more consistent comparisons across worker groups.听These statements can give clear insight into the employee鈥檚 annual pay and the average pay of the same worker听category听broken down by gender.听听

2. Preparing for candidate pay transparency 

The directive also requires employers to disclose salary ranges in job postings or before interviews and prohibits asking candidates about salary history. While this may sound straightforward, many organizations are discovering they lack standardized pay ranges, consistent job architecture, or alignment between recruiting and compensation systems. 

 allows organizations to display salary ranges directly within job postings and support more transparent hiring experiences. AI-driven recommendations can also help organizations establish more consistent pay ranges aligned to internal equity, external benchmarks, and evolving workforce needs. 

3. Meeting gender pay gap reporting obligations 

Mandatory gender pay gap reporting represents one of the directive鈥檚 most operationally demanding requirements. Annual reporting obligations begin in 2027 based on 2026 workforce data, meaning organizations need to prepare now.  

For many HR teams, the challenge is turning complex, multi-country workforce data into accurate and defensible reporting. With听, organizations can use AI-assisted analysis to听identify听potential drivers behind pay gaps, surface workforce equity insights more quickly, and support more proactive decision-making听before reporting deadlines arrive.听听

What HR should do now 

The EU Pay Transparency Directive is not just introducing a new compliance requirement. It鈥檚 accelerating a broader shift toward continuous transparency in how organizations manage compensation, hiring, and workforce equity. 

The organizations best prepared for this shift are taking action now to: 

• Unify workforce and compensation data听
• Standardize job and pay structures听
• Improve reporting readiness听
• Build more consistent, explainable compensation processes across the business

As transparency expectations continue to grow among employees, candidates, regulators, and business leaders, pay equity can no longer operate as a periodic reporting exercise. It is becoming an ongoing operational capability. 

Watch the  to learn how to move from policy to execution and prepare your organization for EU Pay Transparency requirements at scale.  

Maryann Abbajay is chief revenue officer for 麻豆原创 SuccessFactors.

The conversation has moved beyond what AI can do into how it should be applied, placing HR at the center of decisions that will shape people, culture, and business outcomes for years to come.

While we have often talked about the 鈥渇uture of work,鈥� the simple fact is that future is already here. The question is whether organizations are ready to operate differently.

AI requires a fundamental rethinking of how work gets done, grounded in the data, systems, and processes that run today鈥檚 organizations. And getting it right starts with one clear principle: humans must remain firmly at the center鈥攏ot as operators of process, but as leaders of judgement, strategy, and change.

What Autonomous HCM means for HR leaders

At 麻豆原创, this is the foundation of our vision for the Autonomous Enterprise, announced at in Orlando, where AI assistants can run core HR processes end-to-end, so people are empowered to focus on their most meaningful work while staying firmly in control of outcomes.

brings together agentic AI, HR applications, and real business context鈥攇rounded in deep process expertise and enterprise-grade governance鈥攖o help organizations anticipate workforce needs and respond with greater precision as business priorities change.

With the new HCM innovations announced at 麻豆原创 Sapphire, we are building on the existing breadth and depth of 麻豆原创 SuccessFactors with new AI-native functionality that amplifies how HR can help shape the business and elevate what employees are capable of.

Automate work with Joule Assistants

The first shift is automation; not as task replacement, but as a new way of working. A new generation of , delivered through Joule as 麻豆原创鈥檚 AI engagement layer, bring this to life by orchestrating agents to execute work end-to-end and support decisions in real-time.

These assistants are not just automating tasks; they are guided by employees to reduce manual effort and support a growing range of HR scenarios:

• Payroll becomes proactive, not reactive: The coordinates multiple to prepare payroll runs, identify issues early, and guide administrators to faster resolution, shifting payroll from reactive process to proactive execution. Working alongside the Core HR Assistant and , it helps organizations manage employee data, track time and attendance, and pay employees with greater accuracy and less manual work.
• Talent acquisition flows more seamlessly end-to-end: The helps keep hiring moving from intelligent matching to interview coordination, providing real-time guidance to recruiters and hiring managers. Once a candidate accepts, the takes over to support a smooth transition for new employees. These new Joule Assistants connect talent acquisition processes between and the broader 麻豆原创 SuccessFactors HCM suite.
• HR services become faster and more intuitive: The helps administrators resolve common HR questions instantly, directing employees to the right next step and reducing service center volume while improving the overall employee experience.

Reimagine the workforce with AI-driven planning

As AI becomes part of how work gets done, organizations must rethink workforce planning as a continuous leadership discipline, not a periodic exercise. Today, 62% of C鈥憇uite executives say they are dissatisfied with how well people data connects to business performance, according to , making it harder to turn strategy into action. The new workforce planning capability within 麻豆原创 Enterprise Planning supports a shift toward strategic work redesign, inclusive of both agents and people, by helping leaders link workforce decisions directly to HR, business, and financial needs.

This workforce planning capability connects data from , , and 麻豆原创 SuccessFactors, creating a unified foundation for workforce decision鈥憁aking across employees and contingent labor. Together, this moves workforce planning beyond static models. Leaders gain clear scenario insight and the ability to combine human judgment with AI to align workforce and investment decisions.

At a more granular level, constant change means business and HR leaders are often dealing with organizational changes. The new AI鈥慹nabled organizational modeling for replaces slow, disconnected modeling approaches with an integrated experience that supports scenario planning and impact analysis, enabling leaders to evaluate organizational choices with greater accuracy and alignment. With this approach, leaders can quickly explore alternative organizational structures and understand implications before changes are implemented. Whether adjusting roles, teams, or reporting lines, organizational modeling becomes a practical leadership tool, supporting thoughtful change while maintaining data integrity and minimizing disruption. The result is a clearer, more proactive approach that helps organizations make smarter workforce decisions in a constantly evolving business landscape.

Elevate people through continuous upskilling

When it comes to skills, the rise of generative AI has once again accelerated the pace of change. New jobs are emerging, new skills are required, and processes that have worked for decades are being completely reimagined.  The new Workforce Upskilling Assistant delivers personalized, AI-driven learning directly where work happens, in collaboration tools, mobile, desktop and 麻豆原创 SuccessFactors鈥攈elping organizations keep skills aligned with where the business is headed. By orchestrating multiple Joule Agents, it supports content creation and generation, adaptive micro-learning, and reinforcement, enabling leaders and managers to identify critical skill gaps and accelerate upskilling, particularly in fast-moving areas such as AI.

By delivering learning in the tools and channels employees already use, the Workforce Upskilling Assistant turns workforce and business data into timely, bite鈥憇ized learning moments. Rather than relying on scheduled courses or standalone systems, HR learning teams can quickly convert existing content to deliver learning to the right person at the right time.

A new standard for human-centered Autonomous HCM

麻豆原创鈥檚 Autonomous Enterprise vision sets a new standard for how HR leads in an AI-driven world, one where AI assistants and agents take on the work of coordination, so people can focus on leading and shaping outcomes. As AI becomes embedded into how work runs, HR is uniquely positioned to guide what matters most, moving from coordinating processes to guiding decisions, building resilient teams, strengthening trust, and ensuring the workforce is ready for what鈥檚 ahead.

That is the promise of an Autonomous HCM platform: human expertise elevated by AI, delivering meaningful impact for both people and the business.

Learn more about how 麻豆原创 is delivering Autonomous HCM by catching the replay of the HCM Innovation .

Dan Beck is general manager and chief product officer for 麻豆原创 SuccessFactors.

In his kickoff keynote at 麻豆原创 Sapphire Orlando, Florida, Klein and other 麻豆原创 Board members detailed how 麻豆原创 plans to bring agentic AI to the world’s most critical business workflows so that humans and AI can meet the accelerating demands of global business profitably, strategically, and safely.

鈥淭oday I鈥檓 super proud to launch our new 麻豆原创 Business AI Platform, which forms the basis for our vision of the future of business: the Autonomous Enterprise, where agents run the business and you can focus on what truly matters,鈥� Klein said.

Enterprise AI is at an inflection point, Klein told his 30,000-strong in-person and virtual keynote audience, and 麻豆原创 is in a unique position to deliver what customers need to turn their businesses into autonomous enterprises.

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The business AI imperative

Across industries, organizations are investing heavily in artificial intelligence, yet many still struggle to translate that investment into meaningful business value. At 麻豆原创 Sapphire, the message was clear: This isn鈥檛 a technology problem; it鈥檚 a context and execution problem.

While 80% accuracy may be sufficient for consumer AI applications, Klein said, 鈥淓ighty percent is just not good enough when you run the world鈥檚 most business-critical businesses. They [LLMs] should not guess; they should deliver accurate, compliant, and secure outcomes.鈥� 

Klein acknowledged that while adoption of AI has become near-universal, tangible business value remains elusive. Citing a recent Stanford AI survey, he noted that almost every company is now using AI, but seeing only limited return.

The reason, he argued, lies in a structural gap. Above the waterline of enterprise AI, LLMs continue to improve at tasks trained on publicly available data, while below it lies what enterprises truly need: AI that understands mission-critical business data, end-to-end processes, and operates within security, compliance, and governance frameworks.

ERP as the foundation for business AI

麻豆原创鈥檚 answer to this challenge begins with what Klein described as 鈥渢he brain of every company: its ERP system.鈥� For over 50 years, 麻豆原创 has had solutions with incredibly deep process and data domain know-how alongside the governance requirements, compliance controls, and company-specific configurations that define how businesses actually run.

Now, as part of the company鈥檚 new vision, 麻豆原创 plans to infuse this institutional knowledge into AI agents, enabling them to navigate thousands of business processes, select from more than 7 million data fields, and verify identity and access authorizations before returning any output.

鈥淲e鈥檙e bringing together LLMs with 50 years of business know-how stored in our ERP. But to do this, we had to do nothing less than completely reinvent our company,鈥� he told the audience. 鈥淭oday we are very excited to show you the new 麻豆原创 and our vision for the Autonomous Enterprise.鈥�

麻豆原创 Business AI Platform

To bring this vision to life, 麻豆原创 executives on stage announced a series of important innovations, beginning with the launch of the new 麻豆原创 Business AI Platform, a unified architecture bringing together 麻豆原创 Business Technology Platform, 麻豆原创 Business Data Cloud, and AI Foundation under a single roof.

鈥淭he heart of this new platform is the rich context layer,鈥� said Klein. 鈥淗ere, we infuse the deep ERP business domain know-how into the AI agents. Through our knowledge graphs, our AI agents have now a compass, a map, to find the right process and data in your ERP universe. And to provide the agents even more context, we are also introducing our new 麻豆原创 Domain Models. They have been trained on 麻豆原创’s code to even better understand the business logic of your company.鈥�

But, he said, 麻豆原创 is going further: 鈥淏ecause you run your business not only with 麻豆原创 solutions, our AI agents have to also understand non-麻豆原创 data. That’s why we included our 麻豆原创 Business Data Cloud in the context layer to build a single semantical data layer across 麻豆原创 and non-麻豆原创. No more silos, no spaghetti data sprawl鈥攂ecause no AI agent can compensate for a broken data model.鈥�

Echoing Klein, 麻豆原创 CTO Philipp Herzig, who presented the platform in detail, said it has been designed to close the agent adoption gap in the enterprise by delivering outcome, speed, enterprise-readiness, and context. 鈥淚t’s the place where you build, contextualize, reason, and govern AI,鈥� he said.

Herzig explained that the platform is structured around three layers: the context layer which Klein referenced, the build layer, and the governance layer. 鈥淎gents are only as powerful as the context they operate on,鈥� he said. 鈥淟acking context is the number one reason why enterprise AI projects fail to deliver value.鈥�

Within the build layer of the new platform, the new Joule Studio is designed to understand a company鈥檚 business challenges and enables the building of new AI agents quickly and easily.

The third tier is the governance layer, anchored by the new 麻豆原创 AI Agent Hub built on 麻豆原创 LeanIX. This provides a single command center to discover, manage, and govern all AI agents鈥斅槎乖� and non-麻豆原创. It will be generally available in Q3 and included in 麻豆原创 Business AI Platform at no additional charge.

Underscoring the changing AI marketplace, Herzig was joined on stage by KPMG Global Head of Advisory Rob Fisher, who told the audience: 鈥淲hat I鈥檓 hearing from clients is a clear shift; they鈥檙e moving from AI pilots to embedding integrated AI and agents into how work gets done. Where we see leaders really separating from the pack is in the execution and the organizational adaptability.鈥�

麻豆原创 Autonomous Suite

Building on the platform, 麻豆原创 Executive Board Member Muhammad Alam, 麻豆原创 Product & Engineering, announced the transformation of 麻豆原创鈥檚 SaaS application portfolio into the 麻豆原创 Autonomous Suite, described as the most significant evolution of 麻豆原创鈥檚 applications business in the company鈥檚 history.

The suite spans five domains: Autonomous Finance, Autonomous Spend, Autonomous Supply Chain Management, Autonomous HCM, and Autonomous CX, with more than 200 agents and over 50 assistants available in the coming months. Each assistant is mapped to core business roles and carries defined KPIs tracked through 麻豆原创 AI Agent Hub.

鈥溌槎乖� Autonomous Suite brings together the depth of our process expertise, semantically rich data, and built-in governance and compliance,鈥� said Alam. 鈥淭hese agents are designed with outcomes as a core objective. Each assistant has a defined set of ROI KPIs that you can expect it to deliver.鈥� 

鈥淯nderpinning the autonomous suite are out-of-the-box agents鈥攈undreds of agents cutting across all core business processes,鈥� he shared. 鈥淭hese agents come together into what we call assistants, or Joule Assistants. We’ve mapped these assistants to roles across the core processes of an organization, because we know that the first step 
in realizing value from AI is to empower your people to do more, do it better, or do things that just weren’t possible to be done before.鈥�

Turning to Joule itself, Muhammad said 麻豆原创 is fundamentally reimagining how users will interact with 麻豆原创 applications in the future.

鈥淲e call this Joule spaces and along with the familiar Joule conversations experience and Joule Studio 2.0, it is now part of what we call Joule Work,鈥� he explained.

鈥淛oule Work represents a massive step forward in super-charging the capabilities of Joule as we know it today,鈥� Alam said. 鈥淲ith Joule Work, we’re bringing a claw-based agentic harness to Joule along with computer and file access, better support for open standards such as MCP and A2A, access to a more complete knowledge base, and, of course, amazing visualizations on the fly.鈥�

Industry AI: H&M and Sector-Specific Transformation

During the keynote, 麻豆原创 Chief Operating Officer Sebastian Steinhaeuser introduced the Industry AI initiative, delivering AI-powered solutions built on decades of sector-specific expertise across 26 industries. In life sciences, he highlighted how 麻豆原创 customer Takeda is achieving up to 10% productivity gains, up to 25% reduction in revenue loss from stock-outs, and up to five percent reduction in safety stock through Autonomous Regulated Manufacturing.

He was also joined on stage by H&M Group CDIO Ellen Svanstr枚m, who discussed how the fashion retailer is embedding AI across its value chain. Built on RISE with 麻豆原创, 麻豆原创 Business Data Cloud, 麻豆原创 Commerce Cloud, and 麻豆原创 SuccessFactors solutions, H&M has developed a Store Intelligence Agent that processes real-time signals to generate actionable recommendations for store managers. Svanstrom also demonstrated the AI-powered InStore Concierge, a customer-facing agent that bridges digital and physical retail through personalized outfit recommendations and real-time availability.

RISE with 麻豆原创 and 麻豆原创 GROW: Path to the Autonomous Enterprise

Returning to the keynote stage, Klein emphasized that technology adoption alone does not create business value. Simply plugging AI agents into your system landscape will drive zero value, he said. 鈥淢oving to the Autonomous Enterprise requires serious change management. Adoption of AI goes hand-in-hand with business process change and end user enablement.鈥�

To support customers on this journey, 麻豆原创 announced a comprehensive reset of its RISE with 麻豆原创 and 麻豆原创 GROW offerings. RISE with 麻豆原创 customers will receive contractual commitment to activate three Joule Assistants within the first year, with the Max Success Plan extending adoption across the full enterprise.  

麻豆原创 GROW customers will receive more than 20 AI assistants from day one, with an AI-enabled toolchain designed to support go-live in weeks. New partnerships with Palantir and Accenture will support the most complex migration scenarios.

Closing: The Autonomous Enterprise

Klein closed the keynote by asking Joule to summarize the key takeaways and noting that 麻豆原创 is evolving from being a software company to becoming a business AI company.

鈥淲e showed how to turn the promise of business AI into reality with 麻豆原创 Business AI Platform, which provides the data processes and governance AI need to deliver accurate and secure outcomes at scale; we introduced the 麻豆原创 Autonomous Suite, where applications reason, decide, and act for you; and we showed how to manage change management with RISE with 麻豆原创. Together with customers and partners, we showed how 麻豆原创 is helping companies realize the vision of the Autonomous Enterprise.鈥�

鈥淲e鈥檝e been reinventing how businesses run for over 50 years, and now by infusing 麻豆原创鈥檚 ERP brain into the new 麻豆原创 Business AI Platform, we鈥檙e solving one of the biggest challenges businesses are facing today: how to turn AI into business value,鈥� he said. 鈥淚t鈥檚 the end of long negotiations, supply chain disruptions, financial blind spots, and the beginning of better: Welcome to the Autonomous Enterprise.鈥�

The company introduces a unified 麻豆原创 Business AI Platform, deepening partnerships with Anthropic, Amazon Web Services, Google Cloud, Microsoft, NVIDIA and Palantir

ORLANDO听鈥� At 麻豆原创 Sapphire in 2026, (NYSE: 麻豆原创) introduced the to help enhance the world’s most critical business workflows, so that humans and AI work together to meet the accelerating demands of global business profitably, strategically and safely.

鈥淔or the mission-critical processes of our customers, ‘almost right’ just isn鈥檛 good enough,鈥� said Christian Klein, CEO of 麻豆原创 SE. 鈥淏y uniting 麻豆原创 Business AI Platform with 麻豆原创 Autonomous Suite, we anchor AI agents in the business processes, data and governance so they can deliver accurate, compliant and secure outcomes, unlocking new sources of revenue and meaningful cost savings.鈥�

The Autonomous Enterprise includes a unified AI platform for building, contextualizing and governing agents, an autonomous suite that executes core business operations and a new user experience that redefines how people work with enterprise software.

Introducing 麻豆原创 Business AI Platform

麻豆原创 Business AI Platform is a new foundation for building and deploying enterprise AI grounded in real business context. 麻豆原创 Business AI Platform now unifies 麻豆原创 Business Technology Platform, 麻豆原创 Business Data Cloud and 麻豆原创 Business AI into a single, governed environment.

At its core is the 麻豆原创 Knowledge Graph solution, which gives AI agents a structured map of business entities, processes and relationships across a customer’s 麻豆原创 landscape. Joule Studio is 麻豆原创’s AI-first solution for building enterprise agents, applications and agentic workflows. Developers can build using the no-code, pro-code and AI frameworks of their choice on 麻豆原创-managed infrastructure that is secure, scalable and optimized for enterprise AI.

Deploying 麻豆原创 Autonomous Suite Across Every Business Function and Industry

Building on this foundation, 麻豆原创 also introduced 麻豆原创 Autonomous Suite, which enables 麻豆原创’s existing business applications with AI agents capable of running processes from start-to-finish.

The suite will deploy more than 50 domain-specific Joule Assistants across finance, supply chain, procurement, human capital management and customer experience. These assistants will automate end-to-end processes by orchestrating a subset of over 200 specialized agents to execute precise tasks. For example, the new Autonomous Close Assistant can compress the financial close process from weeks to days by automating journal entries, reconciliation and error resolution across the entire process.

麻豆原创 also launched Industry AI, expanding its deep industry portfolio through seven autonomous solutions that will enable start-to-finish industry processes and embed sector-specific process logic, data models and regulatory requirements. At 麻豆原创 Sapphire, 麻豆原创 showcased its work with European energy giant RWE to leverage Industry AI, helping reduce unplanned downtime across its offshore wind turbines. With 麻豆原创’s Autonomous Asset Management scenario, AI agents are designed to analyze data from thousands of past incidents, identify the likely root cause and generate pre-filled work orders with the right tools and proven fixes from other sites.

Designing the Autonomous User Experience

The company also revealed Joule Work, redefining how users engage with 麻豆原创 software. Instead of navigating individual applications and entering data across several screens, users will now interact primarily with Joule. By describing a desired business outcome, Joule will orchestrate the right combination of workflows, data and agents to get it done.

Joule Work goes beyond conversation, proactively surfacing relevant insights and automating routine tasks behind the scenes so work moves forward even when humans aren’t actively steering it. It will be available on desktop, mobile and voice across 麻豆原创 and non-麻豆原创 systems.

Accelerating the Customer Journey Toward Autonomy with 鈧�100 Million Infusion

麻豆原创 evolved its customer and partner programs to help accelerate the organization’s journey to the Autonomous Enterprise. To catalyze adoption, the company has launched a 鈧�100 million fund for 麻豆原创 partners to help customers deploy 麻豆原创-built AI assistants and agents. The fund is also available to partners that extend or build new partner agents on the new 麻豆原创 Business AI Platform using Joule Studio.

麻豆原创 has enhanced its RISE with 麻豆原创 and 麻豆原创 GROW offerings to accelerate AI adoption. Both include access to the Joule Assistants portfolio; RISE with 麻豆原创 customers will have three assistants activated within their first year, while 麻豆原创 GROW customers receive full portfolio access at onboarding. 麻豆原创 S/4HANA on-premises and 麻豆原创 ERP Central Component (麻豆原创 ECC) customers are not excluded: those that commit to transitioning the majority of their current landscape to 麻豆原创 Cloud ERP gain access to select AI scenarios, bridging the gap between their current landscape and their cloud destination

麻豆原创 also introduced new agent-led transformation tooling that can reduce ERP migration efforts by more than 35 percent, driving faster and more predictable projects by automating system analysis, code remediation, configuration and testing at scale.

Lastly, 麻豆原创 announced a full slate of strategic partnerships across each category:

• Platform and suite partnerships include Anthropic, with Claude among the foundation models 麻豆原创鈥檚 AI platform will leverage to power Joule agents across HR, procurement and supply chain; Amazon Web Services, bringing zero-copy data integration between 麻豆原创 Business Data Cloud and Amazon Athena; Google Cloud and Microsoft, enabling bidirectional agent-to-agent interoperability between Joule and external agent frameworks; Mistral AI and Cohere, delivering sovereign model options on 麻豆原创’s cloud infrastructure; , providing visual AI workflow orchestration inside Joule Studio; NVIDIA, whose OpenShell provides the trusted secure runtime for Joule Studio; and , bringing AI agents into 麻豆原创 Service Cloud to handle customer interactions with full access to business data and service processes.
• Implementation partnerships include Palantir and Accenture, partnering on complex data migration scenarios, and for AI-powered cloud ERP migrations.

.

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About 麻豆原创

As鈥痑 global leader in enterprise applications and business AI, 麻豆原创 (NYSE: 麻豆原创)鈥痵tands at the鈥痭exus鈥痮f business and technology. For over 50 years, organizations have trusted 麻豆原创鈥痶o bring out their best by uniting business-critical鈥痮perations spanning finance, procurement, HR, supply chain, and customer experience. For more information, visit鈥�.

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Across many enterprises, HR, time, and payroll systems have evolved through years of growth, acquisitions, and regional customization. The result is a patchwork of disconnected tools, duplicated data, and manual handoffs that quietly slow decision-making and increase operational risk. These systems may still 鈥渨ork,鈥� but they carry a hidden cost on productivity, accuracy, and confidence, as expectations on HR continue to rise and AI becomes central to how work gets done.

Fragmentation is the hidden bottleneck behind 鈥渟low鈥� decisions

The impact of fragmentation isn鈥檛 always visible, but it shows up clearly in how decisions get made.

When decisions stall, leaders often point to approvals, governance, or external constraints. In reality, much of the friction happens earlier, when teams reconcile data across systems before decisions can even begin.

According to the research, organizations with unified HR foundations gained faster access to trusted workforce information, generating insights 60% faster and creating new position listings 53% faster. Rather than adding tools, these organizations removed friction by eliminating manual validation, shadow spreadsheets, and repeated checks to confirm data accuracy.

As organizations look to AI to accelerate workforce planning, surface risks, and guide decisions, this foundation becomes even more critical. AI is only as effective as the data it can access and trust. In disconnected environments, AI inherits the same inconsistencies, delays, and gaps, limiting its ability to generate reliable insights and recommendations.

Consider a simple workforce planning decision like headcount approval. In a fragmented environment, HR pulls data from one system, finance validates it in another, and managers reconcile discrepancies in spreadsheets. What should take hours stretches into days鈥攏ot because the decision is complex, but because the data is.

With real-time, consistent workforce information, leaders can act faster and with greater confidence in their decisions. More importantly, unified data allows AI to move beyond reactive reporting to deliver proactive, decision-ready intelligence.

Most payroll errors aren鈥檛 human鈥攖hey鈥檙e structural

Disconnected systems don鈥檛 just slow work; they also increase errors.

When employee data, time records, and payroll information live in different places, every handoff becomes an opportunity for mistakes. Manual reconciliation and corrective actions become routine, especially during high-pressure cycles like payroll close.

Organizations with unified platforms see a clear shift. Payroll error rates drop by 64% and payroll cycles are completed 44% faster by eliminating data gaps and automating validation across connected processes.

This is where AI begins to shift from reactive to preventative. With unified data, AI can identify anomalies before payroll runs, flag potential compliance risks, and continuously learn from patterns across the organization. Instead of fixing errors after the fact, HR and payroll teams can prevent them altogether.

That structural shift changes the nature of work for HR and payroll teams. Payroll teams saw a 21% productivity increase, while HR teams improved productivity by 14%, as time previously spent tracking down discrepancies, correcting entries, and responding to escalations was redirected toward oversight, compliance, and continuous improvement.

Fragmentation quietly erodes trust and limits AI adoption

When systems are fragmented, trust erodes quietly. Employees lose confidence when pay errors occur or self-service tools don鈥檛 reflect their reality. Managers hesitate to act when dashboards conflict. HR teams become intermediaries between systems rather than strategic partners to the business.

Integrated HR, time, and payroll systems reverse this dynamic. Employees gain easier access to self-service tools, with 28% more employees able to directly access HR and time entry platforms. Managers benefit from real-time visibility into approvals and team data. And HR teams regain credibility as the source of accurate, timely workforce information.

Over time, this trust compounds. When people trust the system, they use it. Increased usage improves data quality, and better data strengthens decision-making.

This foundation becomes even more important as organizations scale AI across HR. Employees and managers are far more likely to rely on AI-driven recommendations鈥攚hether for career growth, scheduling, or compensation鈥攚hen they trust the underlying data. Without that trust, even the most advanced AI capabilities remain underutilized.

Fragmentation doesn鈥檛 just slow execution鈥攊t narrows what leaders believe is possible, forcing decisions to be shaped by system constraints rather than business needs.

The cost of standing still

The cost of fragmentation isn鈥檛 just operational; it鈥檚 financial, and it compounds over time.

Across organizations studied, the average annual quantified benefit totaled US$649,400 per 1,000 employees supported, driven by productivity gains, reduced errors, faster cycles, and better business decisions. Over three years,organizations achieved a 284% return on investment, with a payback period of approximately 15 months.

Beyond these quantified gains, there is a growing competitive gap. Organizations operating on unified platforms are not only more efficient, but they are also better positioned to embed AI across the entire employee lifecycle, from hiring and onboarding to development and workforce planning. Those still operating with disconnected systems risk falling behind鈥攏ot just operationally, but strategically.

The real risk isn鈥檛 innovation

Innovation draws attention because it鈥檚 new, visible, and often disruptive. Fragmentation, by contrast, builds quietly in the background until it starts to limit how the organization operates. But as organizations ask HR to deliver more鈥攂etter insights, faster planning, stronger compliance, and improved employee experiences鈥攖he limits of disconnected systems become harder to ignore.

Modern HR outcomes don鈥檛 come from layering new tools on top of outdated foundations. They come from reducing complexity, unifying data, and creating consistency across the most essential people processes. This is where platforms like 麻豆原创 SuccessFactors are evolving鈥攏ot just to unify core HR, time, and payroll, but to embed AI directly into the flow of work. By combining a trusted data foundation with AI-driven insights and automation, organizations can move from reactive operations to predictive, insight-led workforce management.

The question isn鈥檛 whether organizations can afford to modernize HR. It鈥檚 whether they can afford to limit the impact of AI by building on fragmented foundations.

AI doesn鈥檛 transform HR on its own; it amplifies what鈥檚 already there. And without a unified, trusted core, even the most advanced AI will struggle to deliver on its promise.

Learn how leading organizations are reducing fragmentation and building a strong foundation for AI by unifying core HR, time, and payroll with .

*

Lara Albert is chief marketing officer for 麻豆原创 SuccessFactors.

With the听听1H鈥�2026 release,听we鈥檙e听deepening those connections across the HR lifecycle. This release focuses on听four听core priorities:听connected,听suite-wide听AI; unified experiences that adapt to how organizations work;听processes designed for clarity, accuracy, and compliance; and stronger foundations for skills and long-term growth.听Together, these innovations help organizations听anticipate听needs earlier, reduce friction in daily work, and move forward with greater confidence.听

Connected AI that works across HCM

AI in HR delivers the greatest impact when it works continuously across the entire workforce lifecycle鈥攏ot as isolated features, but as connected capabilities that share context and insight.

The 1H鈥�2026 release expands听suite-wide听agentic AI听across 麻豆原创 SuccessFactors solutions, helping听employees听get clearer answers, act sooner, and keep听work moving听across roles and responsibilities.听A connected network of听听now supports areas such as recruiting, workforce administration, payroll, learning, performance, and talent development鈥攚orking together behind the scenes to help听anticipate听next steps and surface relevant guidance.

This release also introduces a growing听workforce knowledge network, bringing trusted external expertise and research directly into the flow of work through Joule.听Teams can now access expert-backed global employment guidance and听research-driven听insights without leaving their workflows鈥攕upporting听faster, more听confident decisions.

To听further听support learning in the flow of work,听intelligent Q&A in听听now helps employees find information more easily. AI听can deliver instant,听context-aware听responses drawn directly from an organization鈥檚 learning content,听along with relevant links and resources,听so employees can get answers quickly without searching through courses or documentation.听

Unified experiences that adapt to how work gets done听

As HR听tasks听become more embedded in听day-to-day work, experiences need to feel intuitive, connected, and responsive听wherever work happens. In the 1H 2026 release,听麻豆原创 SuccessFactors solutions continue to unify experiences across the suite, giving employees, managers, and HR teams what they need听in听the moment.听

• Connected recruiting and onboarding:听Native integration between听 solutions, , and听听can bring AI-enabled听recruiting, core HR, and onboarding together into a single, continuous experience, helping hiring teams move faster while听maintaining听consistency from candidate through new hire.听

• Tailored experiences,听built faster:听The new听extensibility wizard听can provide guided, step-by-step support for creating custom extensions on听听(麻豆原创 BTP) directly within听麻豆原创听SuccessFactors solutions, making it easier to adapt experiences to unique business needs while preserving governance.听
• Simpler, clearer employee moments:听A redesigned, configurable 401(k) experience听in听听for U.S.听employees helps simplify enrollment and management by clearly explaining employer contributions and guiding deferrals and beneficiary setup, helping employees make informed decisions with confidence.听

Processes designed for clarity, accuracy, and compliance听

In the 1H鈥�2026 release, 麻豆原创 SuccessFactors introduces new capabilities that help organizations bring greater clarity and rigor to pay practices.

With听pay听transparency insights听in the , organizations can analyze compensation patterns and potential pay gaps, supporting transparent, data-driven pay practices in-line with evolving regulatory expectations,听including in the EU.听

Skills governance听for sustainable growth听

Preparing for听what鈥檚听next requires trusted, consistent skills data that organizations can rely on across HR, talent, and workforce planning.

In the 1H鈥�2026 release,听we are听strengthening听the听听with enhanced听skills governance, providing a centralized interface to help manage skills, apply governance standards, and ensure alignment across 麻豆原创 SuccessFactors solutions and partner applications. This helps organizations improve听skills听data quality, maintain consistency at scale, and make more confident,听skills-based听decisions.听

A connected foundation for the future 

This听release听reinforces听麻豆原创鈥檚 continued focus on an intelligent, connected HCM听foundation鈥攐ne designed to evolve with your organization and support confident decisions at every stage of work. By bringing together data, AI, and experiences across the HR lifecycle, these听enhancements help organizations reduce friction today while听laying听the groundwork for听tomorrow.

To explore what鈥檚 included in this release, check out the or watch the overview .

Bianka Woelke is group vice president and head of Application Product Management for 麻豆原创 SuccessFactors.

But new research from 麻豆原创 and Wakefield* suggests a different reality is emerging. AI isn鈥檛 making early talent irrelevant. Instead, it鈥檚 accelerating how quickly they become productive, reshaping the earliest stages of work, and raising expectations far earlier in the employee lifecycle.

According to the findings, 88% of CHROs say AI is making early-career talent role-ready faster. This acceleration raises the stakes on both sides. While organizations benefit from faster productivity and earlier impact, early鈥慶areer employees are entering roles with heightened expectations and fewer traditional learning buffers鈥攆orcing leaders to rethink how success is defined and supported from day one.

AI as an accelerator of readiness

Entry-level roles have long relied on repetitive, lower-stakes tasks that helped new employees learn how work gets done. Today, AI automates much of that foundational execution.

This shift is increasingly common: 79% of surveyed CHROs report that their early-career talent receives enterprise AI tools within their first month on the job. Additionally, 87% expect new hires to be comfortable with AI on day one or learn the tools immediately after joining.

With AI absorbing traditional tasks, early-career talent is stepping into meaningful work sooner鈥攁nd CHROs are already seeing the impact, with 56% reporting improved confidence and 55% citing increased productivity among those using AI.

This acceleration reflects themes we first explored in the 2025 麻豆原创 SuccessFactors Future of Work Predictions , where we examined how AI might reshape entry鈥憀evel roles. As foundational tasks continue to be absorbed by AI, the question becomes not whether early鈥慶areer roles will exist, but how organizations can redesign them to build capability in new ways.

When productivity accelerates, expectations follow

As early talent ramps faster, the expectations placed on them are rising just as quickly. Several structural factors are contributing to this shift: organizations are hiring fewer early-career talent, and those who do join are expected to take on more complex work earlier in their tenure. Our upcoming research from our makes this clear, as one research participant summarized, 鈥淓ntry level roles used to be focused on mundane tasks鈥攚hat should they do now? They bring an incredibly unique perspective; we want to hire early talent to challenge our norms and help us find better ways of working.鈥�

But with AI removing the mundane work, it may also remove many of the gradual, hands-on learning moments that once helped new hires build experience over time.

With these rising expectations, it鈥檚 easy to see how the cognitive load of entry level roles could increase substantially. CHROs report heightened performance pressure and increased mental effort as new hires try to keep pace with AI-accelerated work. Some researchers refer to this dynamic as 鈥�,鈥� the cognitive strain that comes from managing rapid, AI-driven workflow.

Together, these shifts create several risks for both employees and organizations:

• Shadow AI use rises: 56%of CHROs say early-career talent turns to unsanctioned AI tools when formal guidance is unclear. This behavior may reflect entry-level hires trying to keep pace rather than intentionally breaking policy.
• Inconsistent enablement creates talent risk: 44% of CHROs say uneven access to AI tools increases attrition risk, especially for early talent who may feel unable to live up to new performance expectations without tools to automate routine tasks.
• Foundational skills may erode: Even as AI boosts productivity, 38%of leaders worry early-career talent are not building long-term skills like communication, critical thinking, judgment, and collaboration. That concern is echoed in qualitative feedback from HR leaders as well. As one noted, 鈥淲e鈥檝e observed gaps in professionalism in business settings for entry鈥憀evel talent, from collaboration and stakeholder management [to] ownership and accountability.鈥�

Rethinking the first step into work

As traditional early鈥慶areer learning pathways narrow, organizations must now redesign how those learning moments happen. Our research points to several areas where HR leaders can intentionally strengthen the early-career ramp:

1. Build foundational skill development intentionally.

As repetitive tasks disappear, organizations have the opportunity to deliberately create new ways for early talent to build communication, collaboration, critical thinking, and decision-making skills. This can include structured, project-based experiences, clearer decision-making frameworks, and more frequent coaching that focuses on judgement and prioritization, not just task completion.

2. Design entry-level roles around higher-value work.

Early-career employees are capable of contributing more strategically when roles are designed with the right balance of scope and support. Redesigning entry鈥憀evel positions to include clear ownership鈥攕upported by explicit expectations, mentoring, and well鈥慸efined guidance for decisions and escalation鈥攈elps early鈥慶areer talent build confidence while managing risk.

3. Establish AI governance from day one.

Without clear guidance, early talent may struggle to understand how to use AI responsibly. Introducing AI expectations during onboarding, reinforcing role-specific best practices, and normalizing manager-led conversations about AI use can reduce shadow AI and build trust in new technologies early on.

4. Ensure equitable AI access across teams and managers.

As expectations rise, uneven access to AI tools can quietly increase workload pressure and stress for early-career employees. Providing consistent access, training, and enablement helps ensure new hires are equipped to meet accelerated demands without increasing burnout or attrition.

The bottom line

AI isn鈥檛 eliminating early-career talent from the workforce; it鈥檚 reshaping the path they take to become effective and increasing the value of the work they contribute. While entry-level roles may be fewer, expectations for impact are higher, placing greater importance on pairing AI fluency with strong human skills. For new graduates, developing both will not only help them land a job but also enable them to contribute quickly and build lasting capabilities.

When early鈥慶areer talent becomes productive sooner, companies can move faster, innovate earlier, and operate more efficiently, but only if that speed is matched with structure, coaching, and intentional development. Organizations that navigate this transition successfully will ensure early talent doesn鈥檛 just ramp up faster, but also builds the judgment, collaboration, and critical鈥憈hinking skills that AI can鈥檛 replace.

To stay on top of more upcoming research on the impact of AI on entry-level roles, visit our .

Lara Albert is chief marketing officer for 麻豆原创 SuccessFactors.

*The 麻豆原创 AI Talent Survey was conducted by Wakefield Research (www.wakefieldresearch.com) among 100 US CHROs (or CPO equivalent) at organizations with a minimum annual revenue of $500m where employees are using AI-enabled tools in their day-to-day responsibilities, between February 19th and March 2nd, 2026, using an email invitation and an online survey.

鈥淲hen we give, we gain鈥� is this year鈥檚 , and in the workplace, giving can take many forms: mentoring, advocacy, visibility, resources, and transparency.

For organizations, pay transparency is one of the most tangible ways to 鈥済ive鈥� in service of gender equality. When employees better understand their compensation, historically underrepresented groups gain clarity and fairness. And when organizations commit to equitable practices, the benefits ripple across the business鈥攆rom greater trust and engagement to stronger talent outcomes and overall performance.

Transparency starts with accountability

Many organizations are still early听in听their pay transparency journey.听At 麻豆原创,听this has been a听multi-year听effort听grounded in data, accountability, and action.听Each year, we conduct global internal pay equity analyses听comparing听employees in comparable roles, levels, and听geographies听to ensure compensation is fair, market-aligned, and internally听consistent. When outliers are听identified, centrally funded adjustments bring听pay听in-line.

This reflects 麻豆原创鈥檚 fair pay philosophy: equitable compensation that is transparent and free from bias, forming the foundation for performance-based differentiation.

Technology is central to this approach. 麻豆原创 operationalizes fair pay through听听and听, embedding听pay analysis, job architecture, and range guidance, so managers can consistently apply structured, explainable decisions during hiring and annual cycles.

Today,听over 99% of 麻豆原创 employees worldwide have transparency into their pay听range through听a compensation assistant听tool built on (麻豆原创 BTP). This tool听integrates 麻豆原创 SuccessFactors data to display salary ranges across career levels, which听can replace听guesswork with confidence and can give employees clear insight into their value, career progression, and how pay decisions are made.

From compliance to strategic intelligence: the EU Pay Transparency Directive

The shift from voluntary transparency to regulatory mandate is already underway. For European Union member states, the EU Pay Transparency Directive is driving change by requiring salary range disclosures in advance of the first interview, employee access to pay information, and gender pay gap reporting, with corrective action mandated when unexplained gaps exceed 5%. As implementation timelines approach, HR, legal, and finance teams across the EU are racing to operationalize new transparency requirements, making pay governance a board-level issue for many organizations.

鈥淥ne of the most meaningful shifts introduced by the EU Pay Transparency Directive is giving employees clearer tools to understand their own compensation. With capabilities like individual pay transparency reports generated through 麻豆原创 SuccessFactors Employee Central, employees now have a self-service way to see how their pay compares within their role and organization. That level of visibility is a major step forward for pay equity because it brings clarity to something that historically has been difficult for employees to question or address.鈥�

Anita Lettink, Future of Work and Pay Expert

Compliance is just the starting point. Organizations that embed transparency into everyday HR processes ensure pay decisions are consistent, equitable, and aligned with skills, performance, and business priorities. 麻豆原创 is already preparing customers for this shift, with tools designed to help meet these new requirements confidently.

With EU Pay Transparency Insights, a new capability within the , organizations can:

• Identify structural pay gaps and outliers before they become systemic issues.
• Connect compensation data to job architecture, skills, and performance to inform decisions and governance.
• Generate directive-aligned, ready-to-use reports without heavy manual effort.
• Turn transparency into action, guiding adjustments, equitable promotions, and workforce planning at scale.

These insights complement established fair pay practices鈥攕uch as structured job architecture, peer-based analysis, and centrally funded adjustments鈥攅nabling customers to implement transparent, equitable pay practices while meeting regulatory requirements.

Giving to gain: the leadership opportunity

This International Women鈥檚 Day, transparency should be treated as a strategic priority, not a compliance task. Clear, consistent pay practices help employees understand their value and help leaders make smarter, data-driven workforce decisions.

Pay transparency is accelerating, and organizations that act now will be the ones that lead. Don鈥檛 miss our upcoming webinar, EU Pay Transparency: Turning Fair and Equitable Pay into Your Strategic Advantage, where Future of Work and Pay expert Anita Lettink will break down the latest regulatory expectations and share best practices for building fair, equitable, and motivating compensation structures. .

Maryann Abbajay is chief revenue officer for 麻豆原创 SuccessFactors.

Today, we鈥檙e announcing that is now integrated with , working to deliver a unified experience, connected data, and integration with AI companion and to embed intelligent assistance directly into hiring workflows to help teams move faster, make better decisions, and deliver better candidate experiences. This integration, following 麻豆原创鈥檚 acquisition of SmartRecruiters in September 2025, establishes the foundation for a fully connected talent architecture, where hiring decisions, skills intelligence, and workforce planning can operate as one system.

Advancing intelligent hiring with SmartRecruiters for 麻豆原创 SuccessFactors

The solution can deliver a consistent, end-to-end hiring experience designed to meet the scale, speed, and intelligence requirements of modern organizations. By combining intuitive workflows with embedded AI, recruiters can eliminate repetitive administrative tasks and focus on higher value interactions, while candidates move through a streamlined, personalized journey from first touch to offer.

The integration with 麻豆原创 SuccessFactors HCM builds on these capabilities by connecting hiring processes to the full employee lifecycle and the broader business, helping to ensure that every hiring decision is grounded in real-time data and organizational context. Designed for scale, SmartRecruiters for 麻豆原创 SuccessFactors helps set the foundation for a complete intelligence layer across hiring and HR, with people, job, and organizational data flowing seamlessly between 麻豆原创 and SmartRecruiters.

Organizations can gain a more predictable hiring process with streamlined workflows, consistent tools, and shared real-time data across each hiring stage. They can expect:

• Single login: one entry point into 麻豆原创 SuccessFactors and SmartRecruiters for recruiters, hiring managers, and approvers
• Unified navigation: a seamless experience across 麻豆原创 SuccessFactors and SmartRecruiters to help reduce complexity and speed up adoption
• Aligned data: synchronized people, job, and organizational data that flows between systems, helping to ensure accuracy and consistency end to end

In practice, core organizational data like job families, cost centers, and locations can flow automatically from 麻豆原创 SuccessFactors into SmartRecruiters, helping to eliminate manual entry and inconsistencies. New roles open with these attributes already applied, and user management is just as smooth: recruiters, hiring managers, and approvers created in 麻豆原创 SuccessFactors appear in SmartRecruiters with the right permissions, helping to reduce errors and keep approval flows and reporting clean. As integration deepens, hiring becomes fully connected to core HR and workforce systems, creating a unified, trusted foundation for talent decisions across the enterprise.

With the enhanced benefits of SmartRecruiters for 麻豆原创 SuccessFactors, simple and flexible integration paths are now available for customers currently using the 麻豆原创 SuccessFactors Recruiting solution. 麻豆原创 will continue to honor all contracts, and customers will not be required to migrate.

Integration that activates enterprise鈥�ready AI

With 麻豆原创鈥檚 continued investment, SmartRecruiters for 麻豆原创 SuccessFactors is evolving quickly, bringing AI-driven innovation to every part of the hiring experience. High-volume hiring can become high-quality hiring through AI-assisted workflows, including intuitive applications, automated scheduling, intelligent matching, and streamlined interview feedback.

Beginning in 2026, Winston and 麻豆原创鈥檚 generative AI solution will work together as connected agents. Additionally, new protections such as fraud detection, enhanced consent management, and applicant data transferability will help embed trust in the hiring cycle, strengthening both system integrity and candidate confidence.

From talent acquisition to talent readiness

As organizations look beyond filling roles to building future-proof capabilities, intelligent hiring becomes just one part of a broader talent strategy. The power of integration delivered by SmartRecruiters for 麻豆原创 SuccessFactors extends beyond hiring, creating a connected, AI-enabled talent experience across the entire 麻豆原创 SuccessFactors HCM suite and, ultimately, . This is how organizations become skills-ready: hiring decisions tied to outcomes, and employees supported with clear paths to grow and contribute.

See SmartRecruiters for 麻豆原创 SuccessFactors in action:听Catch the听听of our March 5 webinar – 鈥淭he Future of Intelligent Hiring鈥� – to explore how 麻豆原创 is redefining hiring, talent orchestration, and long-term workforce strategy.

Lara Albert is chief marketing officer, 麻豆原创 SuccessFactors.
Rebecca Carr is CEO of SmartRecruiters, an 麻豆原创 company.

To date, many employers have approached pay equity at their own pace, but a new era is beginning, one that will redefine pay practices and workplace culture for organizations across the European Union (EU). Set to take effect across EU Member States in 2026, the (EU Directive 2023/970) strengthens the principle of 鈥渆qual pay for equal work or work of equal value鈥� as enshrined in EU law, requiring employers to adopt transparent pay practices and close gender pay gaps or face potential legal and financial consequences.

can provide a single source of truth for the critical data-driven insights needed to help organizations meet EU pay transparency requirements. Today, 麻豆原创 is announcing new capabilities that can make it even easier for organizations to meet their requirements across EU countries.

Launching in 1H 2026, EU Pay Transparency Insights is a new capability within the , an intelligent, AI-powered application that can deliver ready-to-use, actionable insights to help leaders make more informed decisions. EU Pay Transparency Insights enables organizations to analyze compensation, identify outliers, and address pay gaps, helping them meet reporting requirements while unlocking the workforce and business performance benefits of achieving true pay equity.

Three requirements every employer must meet鈥攁nd how 麻豆原创 SuccessFactors HCM supports them

The EU Pay Transparency Directive represents one of the most sweeping changes to workplace compensation in decades. To meet its requirements, organizations will need to reassess their current HR data management capabilities and processes and begin planning now. As countries move toward putting the directive into law by June 2026, some obligations may already apply, with others set to take effect as soon as national laws are enacted. And because pay gap reporting deadlines vary by organization size鈥攕tarting in 2027 for employers with 150 or more employees and based on 2026 workforce data鈥攐rganizations must act now to be ready.听

麻豆原创 SuccessFactors HCM is uniquely positioned to support organizations in addressing the three key requirements outlined in the directive鈥攇ender pay gap reporting, employee pay transparency, and candidate pay transparency鈥攚ith several capabilities already available today and advanced analytics for gender pay gap reporting delivered through EU Pay Transparency Insights in 1H 2026.

1. Gender pay gap reporting

Once national laws are in place, employers will be required to disclose their gender pay gaps on a predefined schedule, and any gap of 5% or more must be explained or mitigated with a joint pay assessment. With EU Pay Transparency Insights within , organizations will be able to access rich workforce insights to analyze compensation and identify drivers behind pay gaps, giving them the information they need to generate actionable reports with a complete view of workforce equity in a single place.

2. Employee pay transparency

In accordance with the directive, employees have the right to request information on average pay levels by gender for comparable roles. By leveraging the powerful document generation capabilities in 麻豆原创 SuccessFactors HCM, employers can provide employees with a self-service experience to display individual pay transparency statements directly from the People Profile in . These statements can give clear insight into the employee鈥檚 annual pay and the average pay of the same worker category broken down by gender.

3. Candidate pay transparency

Employers will be required to disclose pay ranges in job advertisements or before interviews. They will also be prohibited from asking applicants about salary history. 麻豆原创 SuccessFactors solutions help enhance pay transparency by enabling employers to display pay ranges directly within job postings published through 麻豆原创鈥檚 recruiting solutions, including 麻豆原创 SuccessFactors Recruiting and .

In addition to these 麻豆原创 SuccessFactors capabilities, 麻豆原创 continues to work with our vast partner ecosystem to support pay parity and pay transparency efforts.

An opportunity to lead with accountability

The EU Pay Transparency Directive sets a new baseline for accountability in how organizations manage and disclose pay. By preparing early and partnering with 麻豆原创, organizations can deliver transparent compensation insights, empowering employees with a clear view of their total rewards and career journey and supporting HR professionals in making consistent and measurable decisions with confidence. With continuous innovation and trusted localized expertise, 麻豆原创 helps organizations stay on top of changes and build a sustainable, employee-centered approach to pay equity across the EU.

Learn more about how 麻豆原创 SuccessFactors HCM can help your organization stay compliant with the EU Pay Transparency Directive in the

Dan Beck is general manager and chief product officer for 麻豆原创 SuccessFactors.