In 2026, we鈥檙e all too aware that assumption no longer holds. Geopolitical volatility, trade realignments, regulatory pressure, climate events, labour shortages, and economic uncertainty increasingly overlap. Resilience cannot remain a contingency plan activated during a crisis. It must become part of everyday operations.

In response, industry leaders have often framed their response as a choice between just-in-time and just-in-case. Just-in-time reduces inventory and waste but can leave a business exposed when supply or transport is interrupted. Just-in-case adds safety stock and redundant suppliers, but can lock up working capital, increase carrying costs, and make it harder to respond when demand shifts.

Closing the gap between planning and execution

This approach presents a false dichotomy. Businesses should not have to make a permanent choice between efficiency and resilience. They need the flexibility to change their operating posture as conditions change 鈥� leaning toward efficiency when the environment is stable and adding protection when reliable signals indicate risk.

The new-era resilience model is no longer defined by how much inventory a company holds. It is defined by how quickly and reliably the company can understand a change, assess the trade-offs, and act.

Traditional supply chain management separates planning from execution. Teams develop a plan, release it, execute against it, and then measure what happened. However, in a continuously volatile environment, the assumptions behind that plan may change before execution is complete.

A demand shift, a port delay, or a supplier constraint can require immediate revision. Yet the signal often must pass through manual reports, sequential approvals, and disconnected systems. By the time the organisation responds, the most efficient options may have disappeared.

As such, planning and execution must increasingly coexist at the same point. That means continuously sensing changes in demand, supply, and logistics, evaluating their business impact, and coordinating action across functions. The delay between planning and execution becomes a structural vulnerability when the system is facing permanent disruption.

What an anticipatory supply chain looks like

Consider a beverage company operating across Southeast Asia. A change in temperature indicates that demand may rise in Vietnam, so an anticipatory system assesses available inventory, customer commitments, production capacity, and transport constraints. It identifies stock that can be repositioned from Singapore, prepares warehousing and logistics capacity in Malaysia, and signals the production requirements to the rest of the regional network.

The Line of Business owners have already set the objectives, business rules, risk tolerances, and escalation thresholds. The system acts within those boundaries, records the decisions it has made, actively scans for anomalies, and sends ambiguous or higher-risk exceptions to the designated person.

This is the shift from visibility to coordinated action. It depends on integrated planning and execution, trusted master data, real-time signals, and governed AI that understands business context. The goal is a supply chain that can respond before a disruption compounds.

The operating conditions differ across Asia Pacific, but the requirement for faster coordination is consistent. Chinese enterprises expanding internationally must manage more complex, multi-tier networks as they diversify production and serve new markets. Southeast Asia is becoming a more connected manufacturing and logistics hub, even as infrastructure maturity varies across countries. In Japan, labour constraints, industrial automation, and decarbonisation commitments make trusted automation increasingly important.

Building automation on context and governance

Enterprise automation cannot be added as a loose layer above fragmented process. AI must operate with the data models, permissions, process logic, and regulatory requirements that govern the business. This context is what allows an agent in life sciences to work within regulated manufacturing processes, or an agent in energy to support maintenance across distributed assets.

That鈥檚 where a solution like Joule can be used, providing an engagement and orchestration layer across 麻豆原创 applications while purpose-built assistants and agents then support tasks in planning, procurement, manufacturing, logistics, and asset management. People direct the AI, the assistants orchestrate it, and the agents execute it. But at the end of the day, people remain accountable for strategy, objectives, and judgment, while high risk or exceptional decisions follow clear escalation paths to a defined human-in-the-loop.

Contrary to popular belief, governance does not slow this model down. When an organisation defines what a system can do, what requires approval, and what must be escalated, it can actually speed up processes while also providing control and a clear audit trail.

Global biopharmaceutical company Takeda offers one example. Through Autonomous Regulated Manufacturing, the company is achieving up to 10% productivity gains, up to a 25% reduction in revenue loss from stockouts, and up to a 5% reduction in safety stock. In the energy sector, 麻豆原创 is working with RWE, one of Europe鈥檚 leading renewable energy operators, on an Autonomous Asset Management scenario where AI agents analyse thousands of past incidents, identify likely root causes, and prepare work orders with the right tools and proven fixes from other sites.

These examples connect automation to operational and financial performance while keeping people in control of consequential decisions.

Starting decision by decision

Supply chains will not become autonomous overnight. Leaders should begin with high-value, high-frequency decisions where delay creates measurable cost or risk, such as replenishment, order confirmation, and exception triage. They should connect the necessary data and workflows, define the boundaries for execution, and measure performance from the start.

South Korean electronics manufacturer reflects this directly. By partnering with 麻豆原创 to build an intelligent supply chain analytics agent using and , they are liberating planners from manual data collection to focus entirely on strategic decision-making. This is a monumental shift toward a fully .

Across industries, the shift is the same. A leading Australian packaging manufacturer has taken the same approach. Through integrated business planning, over 30% of planner time has been freed from routine scheduling 鈥� redirected toward higher-value decisions and execution.

The companies that invest in this foundation do not just absorb disruption 鈥� they leapfrog their competition.

AI automation can then expand as results, trust, and organisational readiness improve. The businesses that win through disruption will be those with the data foundation, integration, and governance to act on what they know before disruption has time to compound.

Most importantly, organisations need to recognise that the measure of progress is not the number of AI pilots deployed. It is the business outcome: lower inventory, fewer stockouts, stronger service levels, greater productivity, faster response, and a better working capital position.

Abhishek Sahay is the Chief Revenue Officer for Supply Chain Management at 麻豆原创 Asia Pacific.

The post Supply Through Disruption-as-Normal appeared first on 麻豆原创 Southeast Asia News Center.

Armed with real-world expertise and extensive know-how, 麻豆原创 consultants act as a bridge between the business and technology domains 鈥� bringing hundreds to thousands of hours of hands-on experience and best practices in implementing, customising, and managing 麻豆原创 roll-outs.

In fact, 麻豆原创 consultants are such crucial pieces of the digital transformation puzzle that the global market for 麻豆原创 consulting is estimated to grow at a compound annual growth rate (CAGR) of 9.8% between 2025 and 2035 to USD 38.98 billion[1].

Earlier this year, we launched to further supercharge the way millions of 麻豆原创 consultants work, helping them augment their productivity, cut down time-consuming searches, and make better-informed decisions.

Joule for Consultants draws from 麻豆原创鈥檚 vast knowledge base 鈥� including over 9TB of expert-curated 麻豆原创 knowledge, 3 million non-public documents, 250 million lines of (advanced business application programming) and 30 million lines of (ABAP core data services) code 鈥� and turns that institutional expertise into a real-time, context-aware assistant. It understands the solution landscape a consultant is working in, interprets code on the fly, and surfaces relevant guidance in seconds.

Across APAC, a significant number of 麻豆原创 partners and consultants have already adopted 麻豆原创 Joule for Consultants and are using the tool across various phases of 麻豆原创 implementation projects.

Early pilots show clear value: faster delivery cycles of up to 14%, smoother onboarding, and as much as 1.5 hours saved per consultant per day. The payoff is not simply efficiency but the ability for teams to spend more time on strategic design, stakeholder engagement, and delivering tangible outcomes for customers.

AI-Powered Consulting: the Next Frontier for 麻豆原创 Partners

According to the recent conducted by Oxford Economics, AI is expected to drive an average ROI of 16% (US$4.7M) per organisation this year, a figure which will nearly double in two years鈥� time to 31% (US$12.3M). Businesses also ranked 鈥渁lignment with business strategy鈥� and 鈥渁vailability and quality of data鈥� as the top two strategies for maximising ROI from AI.

麻豆原创 Joule for Consultants has the potential to help 麻豆原创 partners drive this ROI, and is designed with quality data and expert-aligned advice based on 麻豆原创 best practices for businesses across industries. With AI itself acting as a productivity enabler, consultants are able to accelerate delivery and increase consistency across projects 鈥� ultimately driving greater customer impact.

Importantly, 麻豆原创 Joule for Consultants is not replacing consultants; it is enhancing their expertise. Instead of spending hours searching documentation or manually comparing configurations, consultants can ask targeted questions and receive contextual, 麻豆原创-specific answers in natural language.

Routine tasks 鈥� from generating sample code to drafting configuration notes 鈥� can be automated, freeing consultants to focus on advising stakeholders, shaping roadmaps, and managing change.

麻豆原创 Joule for Consultants also helps ensure consistency and quality at scale. Teams across markets and time zones can draw on the same trusted guidance, cross-check design decisions against proven implementation patterns, and onboard new colleagues more quickly.

By embedding best practices directly into project execution, Joule for Consultants extends 麻豆原创鈥檚 long-standing investments in enablement and certification, turning static learning into live support. In doing so, it helps the next generation of consultants build confidence faster and deliver better outcomes for customers from day one.

麻豆原创 Partners as Catalysts of AI-First Transformation

麻豆原创鈥檚 partner ecosystem remains central to our AI-first, Suite-first strategy, and partners throughout APAC are leading the shift towards AI-enabled consulting. As 麻豆原创 Chief Partner Officer Karl Fahrbach highlighted at 麻豆原创 Global Partner Summit at 麻豆原创 Sapphire earlier this year: 鈥淧artners will deliver the promise of 麻豆原创 Business Suite.鈥�

In APAC, partners such as ABeam Consulting, Infosys, ITSN Korea, LTIMindtree, , , and many more are already embedding 麻豆原创 Joule for Consultants into their methodologies and training programmes to enhance delivery speed and collaboration.

KPMG, for example, was the first global partner to pilot Joule for Consultants with 麻豆原创, and together with 麻豆原创, have been for delivering meaningful real-world AI transformation.

The APAC region is already seeing tangible impact when 麻豆原创 partners combine industry expertise with AI-powered innovation. 麻豆原创 Joule for Consultants is guiding faster design, sharper diagnostics, and cleaner architectures that help our joint customers realise value sooner.

From Pilots to Practice

The next chapter for 麻豆原创 partners is about scaling AI adoption and innovation. Many partners are moving beyond pilot programmes and embedding 麻豆原创 Joule for Consultants into their standard methodologies. Others are co-innovating with 麻豆原创 to explore capabilities like AI-driven diagnostics or automated value-tracking.

As 麻豆原创 across APAC, our partners are also building AI-native skills that go far beyond using a tool: they鈥檙e redesigning how projects are delivered, how teams collaborate, and how value is measured.

And that may be the greatest impact of 麻豆原创 Joule for Consultants. It doesn鈥檛 just make consulting faster 鈥� it makes it smarter, more consistent, and more accessible to the next generation of talent, elevating the work consultants can do, giving them the space to focus on insights, relationships, and results.

Partners have always been the engine of 麻豆原创鈥檚 ecosystem. With tools like 麻豆原创 Joule for Consultants, they are now supercharged with the intelligence layer needed to drive new transformations across APAC.

Peter Moore is the Regional Head of Partner Ecosystem Success at 麻豆原创 Asia Pacific.

[1] Source: Business Research Insights 鈥� 麻豆原创 Consulting Market Size, Share, Growth, and Industry Analysis, By Type (ERP Software, Service and Other), By Application (SMEs and Large Enterprises), and Regional Insights and Forecast To 2035. https://www.businessresearchinsights.com/market-reports/sap-consulting-market-121265

The post Consulting in the Age of AI: How 麻豆原创 Is Supercharging the Way Our Partners Work appeared first on 麻豆原创 Southeast Asia News Center.

WALLDORF, Germany 鈥� October 8, 2024 鈥� (NYSE: 麻豆原创) today unveiled groundbreaking AI innovations across a technology foundation that drives 87% of global commerce, putting its generative AI copilot Joule at the center of a new way of doing business. At its annual 麻豆原创 TechEd conference, 麻豆原创 announced powerful new capabilities that complement and extend Joule, including collaborative AI agents imbued with custom skills to complete complex cross-disciplinary tasks. Other innovations include the 麻豆原创 Knowledge Graph, a next-generation solution poised to help developers unlock the full value of 麻豆原创 data by connecting it with rich business context, and new tools to ensure developers can continue driving Business AI innovation.听

鈥�麻豆原创鈥檚 innovation drives real business outcomes, and today’s advancements help customers harness the power of AI, data and new development solutions to catalyze growth,鈥� said Muhammad Alam, member of the Executive Board of 麻豆原创 SE, 麻豆原创 Product Engineering. 鈥淒rawing on 麻豆原创鈥檚 unmatched business and technology expertise, the AI innovations we鈥檙e announcing at TechEd forge a new human-AI partnership to transform the landscape of modern business.鈥澨�听

Supercharging Joule听听

On the eve of its first birthday, Joule marks a watershed in how business gets done. 麻豆原创 introduces collaborative AI agents to a copilot that truly speaks the language of business, expands Joule鈥檚 capabilities to support 80% of 麻豆原创鈥檚 most-used business tasks and embeds Joule more deeply within the company鈥檚 portfolio.听听

Collaborative multi-agent systems deploy specialized AI agents to tackle specific tasks and enable them to collaborate on intricate business workflows, adapting their strategies to meet shared objectives. 麻豆原创 is infusing Joule with multiple collaborative AI agents that will combine their unique expertise across business functions to collaboratively accomplish complex workflows. These AI agents enhance productivity by breaking down silos and freeing workers to concentrate on areas where human ingenuity thrives.鈥�听

Two use cases debuted at TechEd showcase the agents鈥� transformative power:听

• A dispute management use case employs autonomous AI agents to analyze and resolve dispute resolution scenarios including incorrect and missing invoices, unapplied credits and denied or duplicate payments.听

• A financial accounting use case employs autonomous AI agents to streamline key financial processes by automating bill payments, invoice processing, and ledger updates while quickly addressing inconsistencies or errors.鈥�听

Harnessing the Power of Data听

麻豆原创鈥檚 AI innovations also draw on the company鈥檚 unmatched business data expertise. The new 麻豆原创 Knowledge Graph solution, accessible through 麻豆原创 Datasphere and Joule in Q1 2025, will give users a deeper layer of business understanding by seamlessly mapping relationships and context across 麻豆原创’s vast data landscape, empowering organizations to make better decisions with their data. By offering ready-to-use relationships between business entities like purchase orders, invoices, and customers, the solution can significantly reduce the complexity of manual data modeling. 麻豆原创 Knowledge Graph grounds AI in 麻豆原创-specific business semantics, which reduces the risk of inaccurate or irrelevant results and makes it easier for organizations to build intelligent applications and leverage generative AI more effectively.听

Empowering Developers听听

麻豆原创 also launched a swathe of innovations for developers to continue driving Business AI innovation. New generative AI developer capabilities such as code explanation and documentation search in 麻豆原创 Build, the company鈥檚 platform for extending its solutions, will reduce development time for Java and JavaScript developers. 麻豆原创 Build is also adding an Extensibility Wizard feature that will let developers access 麻豆原创 Build directly from 麻豆原创 S/4HANA Cloud Public Edition, simplifying the extension process. Meanwhile, ABAP developers and fusion teams will get seamless access to ABAP Cloud development tools from 麻豆原创 Build.听

Finally, 麻豆原创 announced that it has already fulfilled its pledge to upskill 2 million people worldwide by 2025. Through its , the company has lowered the world鈥檚 digital skills gap through role-based certifications, free training materials, hands-on opportunities for developers, and more. 麻豆原创 continues to expand its growing portfolio of AI-related learning opportunities, including courses on generative AI, AI ethics, and 麻豆原创鈥檚 advanced AI tools and platforms.听

Visit the 麻豆原创 News Center. Follow 麻豆原创 at .听

About 麻豆原创
As鈥�a global leader in enterprise applications and business AI, 麻豆原创 (NYSE: 麻豆原创)鈥�stands at the鈥�nexus鈥�of business and technology. For over 50 years, organizations have trusted 麻豆原创鈥�to bring out their best by uniting business-critical鈥�operations spanning finance, procurement, HR, supply chain, and customer experience. For more information, visit鈥�.听

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# # #听

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 2023 Annual Report on Form 20-F.听

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The post 麻豆原创 Supercharges Copilot Joule with Collaborative Capabilities to Ignite Enterprise AI Revolution appeared first on 麻豆原创 Southeast Asia News Center.