麻豆原创 has announced a series of AI innovations at its annual 麻豆原创 TechEd conference, expanding its portfolio for developers. The enhancements to Joule Studio and Joule Work, as well as the 麻豆原创 Business AI Platform 鈥� including 麻豆原创’s latest tabular foundation model 鈥� offer new tools to build and extend AI agents.

麻豆原创 said its strategy is to advance the development and adoption of agentic AI by providing richer business and data context for agents, and governance controls to manage their use across organisations.

Philipp Herzig, CTO of 麻豆原创 SE, said the 麻豆原创 Business AI Platform, along with 麻豆原创 Knowledge Graph, 麻豆原创 Business Data Cloud, Joule Studio, Joule Work and agentic orchestration and integration capabilities, is now generally available.

鈥淭his entire platform is now generally available with all its capabilities, starting at the top with Joule Work, available on every device, every computer, in every browser. Joule Work is where you put your intent and get work done, in one experience across the entire 麻豆原创 landscape and beyond. That is the shift we are delivering at scale. Everything underneath runs on 麻豆原创 Business AI Platform.鈥�

Asked how 麻豆原创 connects with external AI agents entering the market and supports customers already using agents from other vendors, Herzig said the company follows an open strategy.

鈥淐ustomers say that if 麻豆原创 provides an agent in the core domains where they have 麻豆原创, there鈥檚 no need to build and own one. There are tons of agents out there, and we have made sure, via our agent gateway, that there is full interoperability. Our AI agent hub allows you to discover the agents, 麻豆原创 agents and non-麻豆原创 agents, and you can document them and make them compliant.鈥�

Herzig also addressed vendor lock-in and the challenges organisations face when using AI models from different vendors, discussing 麻豆原创鈥檚 approach to letting customers select models for specific use cases.

He said that tailoring a use case for optimisation inevitably brings some lock-in, but that model switchability remains viable for organisations keeping their AI use cases fairly generic.

AI to serve autonomous enterprise operations

Florian Kunzke, global director of AI strategy at 麻豆原创, echoed Herzig鈥檚 view that the company is moving from AI that learns how a business operates to AI that runs it, with the objective of mobilising AI to serve autonomous enterprise operations.

He said 麻豆原创鈥檚 AI strategy continues to evolve, particularly from a user interface and user experience point of view, with agents embedded in its technology suite.

Kunzke said Joule Work and Joule Studio, alongside 麻豆原创 Knowledge Graph 鈥� which provides a structured semantic foundation for Joule 鈥� are central to 麻豆原创鈥檚 AI strategy. The company aims to help organisations become autonomous enterprises while addressing challenges such as the impact of geopolitical tensions on supply chains, the need to improve productivity through AI investment, and the requirement to generate ROI.

He cited , released in August 2026. According to the research, 80% of respondents said AI had improved individual productivity, while 50% said it helped them make better decisions.

However, he stressed the need for perspective on how AI is being adopted and used across organisations. 鈥淚t is important to distinguish between what happens at organisational level and what happens at individual level. There is a gap, and that is what 麻豆原创 is looking to address,鈥� said Kunzke.

He also acknowledged that shadow AI, rogue AI, cyber security threats and the maturity of digital infrastructure continue to affect AI adoption. However, he added that 麻豆原创 is confident its technology empowers customers to select the right AI for a job, as well as the necessary level of control.

鈥淵ou can improve what you are able to observe and measure. With agentic solutions and processes, and the adoption of these processes, the question is what to aim for in terms of governance, what tools will the organisation need. It makes sense to have tools be as close as possible to the applications being used.鈥�

Independent AI expert Johan Steyn, founder of , said the shift to agentic AI marks an inflexion point. “AI strategy stops being about which tools you buy and becomes about how you orchestrate and govern agents,” he said. “Capability is becoming abundant; governance is the scarce advantage.”

Latest tabular AI model

麻豆原创 announced its latest tabular AI model, 麻豆原创-RPT-2.0, which will expand beyond classification and regression to support anomaly and outlier detection, and richer AI-powered analysis through embeddings.

According to 麻豆原创, these native, multi-table capabilities will further reduce manual engineering while delivering faster, deeper insights from structured data.

In partnership with HPE, 麻豆原创 also announced plans to deploy 麻豆原创-RPT-2.0 on the HPE Spaceborne Computer-2 aboard the International Space Station (ISS) in 2027.

The model is scheduled to run directly on the ISS to support anomaly triage, predict potential problems before failures escalate, reconstruct missing sensor values using historical data, and generate mission-health reports for astronauts and ground teams.

Herzig added: 鈥淭he same trusted 麻豆原创-RPT model that powers global supply chains can also work in space. 麻豆原创鈥檚 deep-rooted, proven expertise has led to the International Space Station鈥檚 use of our tabular foundation model to predict potential mission-critical failures in orbit. With 麻豆原创-RPT and TabPFN from Prior Labs, we bring the unique capabilities of tabular AI into the enterprise and across every frontier.鈥�

This article first appeared on .

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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 use no-code and pro-code tools to build and extend agents, choosing from more than 70 AI models. Customers in the Joule Studio early adopter program also can design and run n8n workflows in Joule Studio, with broader availability to follow. The 麻豆原创 Business Data Cloud and 麻豆原创 Knowledge Graph solutions 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. Importantly, 麻豆原创 customers鈥� data remains their data. 麻豆原创 does not share customer data with anyone to train or improve large language models.

鈥溌槎乖� TechEd has always been where builders shape what comes next,鈥� said Philipp Herzig, CTO of 麻豆原创 SE. 鈥淭his year, we are showing how we are moving from AI learning your business to running it. Joule Work is where you put your intent and get work done, in one experience across the entire 麻豆原创 landscape and beyond. That is the shift we are delivering at scale. Everything underneath runs on 麻豆原创 Business AI Platform, delivering faster time to value through out-of-the-box business understanding, higher accuracy, enterprise-readiness that is secure, governed and compliant from the first deployment, and a unique context layer built on over 50 years of process and industry expertise, encoded into every agent action. This is AI built where real work happens.鈥�

Joule Work and Joule Studio Make the Autonomous Enterprise Real

New capabilities for Joule Work will help make AI agents more effective at handling complex business processes via open protocols including Agent2Agent (A2A) and Model Context Protocol (MCP). These innovations advance Joule Work to better understand context, make decisions and execute multistep business workflows across enterprise systems and business domains:

• New agentic thinking capabilities that plan and orchestrate the steps assistants and agents need to reliably complete complex, multistep business workflows across 麻豆原创 landscapes.
• New capabilities in 麻豆原创 Knowledge Graph will incorporate data from additional 麻豆原创 and non-麻豆原创 sources that are unique to each customer. Users can query and explore their customized data in natural language and get accurate answers grounded in their own information.
• Advancements in interoperability allow third-party agents to securely invoke Joule Agents through a governed agent gateway. This enforced access control enables agents from different providers to collaborate across business workflows without sacrificing governance or control.
• New 麻豆原创 Enterprise AI Gateway solution will extend governance to AI interactions, offering a centralized way to manage AI traffic across the enterprise that will consolidate authentication, policy enforcement, routing, monitoring, usage tracking and auditing.
• New Joule Assistant and 麻豆原创 AI Agent Hub expand governance capabilities, and a new AI Governance Assistant helps customers meet compliance requirements for the EU AI Act. These are designed to address critical barriers to scaling enterprise AI: keeping AI systems classified, compliant and operating within defined organizational guardrails and context.

麻豆原创 Business Data Cloud as the Grounding Engine of the Autonomous Enterprise

麻豆原创 Business Data Cloud Ontology Manager in 麻豆原创 Business Data Cloud (麻豆原创 BDC) will provide an AI-native authoring experience for building ontologies across 麻豆原创 and third-party data. By helping AI understand how data from different teams, systems and applications relate to one another, AI agents can more accurately reason and make decisions across the enterprise. The solutions complement 麻豆原创 Knowledge Graph, which provides rich business context for 麻豆原创 data.

Additionally, 麻豆原创 is expanding its lakehouse capabilities with Dremio, adding native support for Apache Iceberg and Apache Polaris plus a high-performance, federated query engine that will enable unified data access without moving or copying the data. 麻豆原创 expands its partnership with Databricks, bringing the full scope and latest innovations of data engineering and enterprise AI capabilities into 麻豆原创 Business Data Cloud as 麻豆原创 Databricks. Core innovations such as Lakeflow, Agent Bricks, Unity Gateway, and Lakebase will help customers to simplify data management and provide a strong data foundation for their AI journey. With a deeper integration to 麻豆原创 Business Data Cloud, a new 麻豆原创 Application Data Foundation, as well as an integration between Joule and Genie, 麻豆原创 and Databricks are helping customers establish an enterprise-wide lakehouse as the foundation for the Autonomous Enterprise and Joule Work.

The 麻豆原创 Reltio solution, recently announced at 麻豆原创 Connect, will bring multidomain master data management to 麻豆原创 BDC. It unifies and enriches customer, supplier and product records across 麻豆原创 and non-麻豆原创 systems into trusted, reusable data products that can power applications and AI agents.

Tabular Foundation Model Trusted for Business, Validated in Space

麻豆原创 announced its latest tabular AI model, 麻豆原创-RPT-2.0, which will expand beyond classification and regression to support anomaly and outlier detection, and richer AI-powered analysis through embeddings. These native, multi-table capabilities will further reduce manual engineering while delivering faster, deeper insights from structured data. In addition, a new 麻豆原创-RPT-TS model will help customers predict values across time-indexed business metrics for key forecasting use cases using the 麻豆原创 Integrated Business Planning solution without requiring custom machine learning.

In partnership with HPE, 麻豆原创 also announced the deployment of 麻豆原创-RPT on the HPE Spaceborne Computer-2 aboard the International Space Station (ISS), one of the most significant edge-compute validations of any enterprise AI model to date. 麻豆原创-RPT is planned to run directly onboard the ISS to support anomaly triage, predict issues before failures escalate, reconstruct missing sensor values from historical data, and generate explainable mission-health reports for astronauts and ground teams 鈥� all without requiring data to be sent back to Earth for analysis.

鈥淭he same trusted 麻豆原创-RPT model that powers global supply chains also can work in space,鈥� said Herzig. 鈥溌槎乖粹�檚 deep-rooted, proven expertise has led to the International Space Station鈥檚 use of our tabular foundation model to predict potential mission-critical failures in orbit. With 麻豆原创-RPT and TabPFN from Prior Labs, we bring the unique capabilities of tabular AI into the enterprise and across every frontier.鈥�

Out-of-the-Box Assistants and Agents Define Our Advantage

For five decades, 麻豆原创 has built the systems of record that run your business. We will deliver, out of the box, a suite of assistants and agents across five horizontal domains all running on 麻豆原创 Business AI Platform 鈥� with industry specialization 鈥� that provides a baseline for systems of intelligence and systems of action.

Ecosystem Partners Help Expand Platform Capabilities

The global 麻豆原创 partner ecosystem brings new capabilities to the ongoing operation and extension of solutions on 麻豆原创 Business AI Platform, helping customers advance toward the Autonomous Enterprise. At 麻豆原创 TechEd, the following partner announcements were highlighted:

A collaboration with Intel closes the loop between enterprise workflows and autonomous robots, bridging informational technology and operational technology through physical AI.

In addition, new 麻豆原创 solution extensions with , and extend autonomous capabilities for customers, helping them run their core processes end to end, without handoffs between systems.

Beyond technology, 麻豆原创 is empowering its strong developer community with new enablement and engagement with tens of thousands joining for Devtoberfest leading up to 麻豆原创 TechEd, new reference architectures, tutorials and hands-on opportunities attendees can try onsite at the event and at home.

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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鈥檚 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鈥檚 view of talent as a strategic differentiator and AI as a capability that should be embedded across enterprise organizations,鈥� said , 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鈥檚 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 , 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�

The post 麻豆原创 Brings 麻豆原创 SuccessFactors and Joule to NTT DATA鈥檚 Global People and Culture Transformation appeared first on 麻豆原创 Africa News Center.

Leading organisations throughout Europe, the Middle East and Africa are revealing how business AI has shifted from experimentation to realised business value at this year鈥檚 麻豆原创 麻豆原创PHIRE, held in Madrid between 19 and 21 May.

The event included demonstrations of two different but connected approaches to AI adoption by and . Ericsson is building the governed data foundation needed to scale AI across the enterprise, while Martur Fompak International is embedding AI directly into physical manufacturing operations to transform execution on the shop floor.

Nazia Pillay, Managing Director for Southern Africa at 麻豆原创, says: 鈥淭he next phase of AI adoption is about execution. Organisations are looking for trusted data foundations, strong governance and practical business use cases that can deliver measurable value. By embedding AI into the systems and workflows companies already use, 麻豆原创 is helping customers scale AI responsibly and turn ambition into real-world impact.鈥�

Nazia Pillay

Ericsson builds the foundation for trusted AI at scale

Ericsson is moving from AI experimentation to enterprise-wide execution by building a unified business data fabric with . The approach enables the company to scale AI use cases across the business, accelerate decision-making and deliver measurable operational impact.

Ericsson, which celebrates its 150th anniversary this year, provides mobile network infrastructure across 180 countries, with more than 40% of the world鈥檚 mobile traffic passing through its networks. As AI becomes central to both its technology roadmap and how it runs the business, Ericsson has prioritised building a strong, governed data foundation to support scalable and trusted AI.

鈥淥nce you scale AI, it stops being an AI problem鈥攁nd becomes a data problem,鈥� says , Vice President, Customer Experience, Enterprise IT at Ericsson. 鈥淭hat鈥檚 why we invested early in a business data fabric. With 麻豆原创 Business Data Cloud, we can define what data means once鈥攆rom revenue to market structures and access rules鈥攁nd apply it consistently across the enterprise. That鈥檚 what allows us to scale AI in a way that is trusted, repeatable and delivers real business value.鈥�

At the core of Ericsson鈥檚 approach is a federated data architecture that allows data to remain in place while centrally managing business semantics, governance and lifecycle policies. By focusing on high-impact use cases and organising around end-to-end business processes rather than isolated solutions, Ericsson has moved beyond pilots to scaled deployment. Today, more than 85 000 users are live on unified Joule, supported by strong executive sponsorship and governance.

麻豆原创 and Ericsson are also collaborating on AI co-innovation initiatives, including an intelligent goal recommendation capability developed within 麻豆原创 SuccessFactors. The solution generates contextual, business-aligned goals for employees, improving execution and reducing administrative effort.

Martur Fompak brings AI into physical manufacturing operations

Martur Fompak International, a global leader in automotive seating and interior systems, has deployed an autonomous intralogistics model enabled by and embodied AI capabilities from 麻豆原创, marking a significant milestone in its journey toward intelligent, AI-driven manufacturing operations.

In an industry rapidly shifting toward AI-powered operations, Martur Fompak International saw an opportunity to reimagine its material flow. Building on efficient, people-driven processes already in place, the company partnered with 麻豆原创 and , a UK-based robotics and AI company, to explore how embodied AI-powered robotics could redefine material flow across its automotive manufacturing environment.

Using Joule and embodied AI capabilities from 麻豆原创, Martur Fompak International now connects production signals and business context directly to autonomous execution, creating a context-aware automation system that prioritises, picks and delivers materials while adapting in real time to changing business conditions.

Built on and enabled by , the solution enriches humanoid robots with real-time knowledge of tasks, attributes and exception handling. Guided by material data, storage locations, sequencing and production priorities, humanoid robots execute material flows across a live automotive manufacturing environment, identifying, transporting and delivering materials to the line while continuously confirming back into 麻豆原创 solutions.

Together with autonomous mobile robots, the company has created a fully automated, scalable material flow that boosts throughput, improves accuracy and reduces reliance on manual coordination. By assigning repetitive, non-value-adding and physically demanding tasks to robots, Martur Fompak International is enabling its people to focus on safer, more meaningful and higher-value work.

鈥淥ur humanoid robot collaborates with digital production systems to ensure seamless coordination across order management, logistics and production, enabling scalable AI adoption and improving efficiency, consistency and operational resilience,鈥� says , Group Intelligent Technologies Director at Martur Fompak International.

Early results show increased throughput, fewer errors and a scalable, AI-driven intralogistics model. With 400 daily production line feeds and 100% 麻豆原创 software-driven decision-making already in place, Martur Fompak International is advancing beyond traditional automation and pioneering a scalable, intelligent factory model.

Pillay adds: 鈥淓ricsson and Martur Fompak International show that AI delivers the greatest value when it is grounded in business context and embedded into core processes. From enterprise data foundations to intelligent robotics on the factory floor, these examples demonstrate how organisations can scale AI responsibly, improve productivity and create measurable business impact.鈥�

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Many companies sit with years of technical debt, complex hybrid environments, disconnected听systems听and inconsistent metadata that make it difficult to build a reliable view of the听business. Businesses still grapple with ageing applications that cannot integrate with cloud platforms, while siloed departmental听systems听prevent teams from accessing the full picture needed for AI-driven decision-making.

The result is predictable: stalled AI听projects, unreliable outputs, and limited return on investment.

The need for a unified data foundation

The typical South African enterprise runs a mix of cloud听services, on-premises applications and bespoke听systems听that were built years ago to solve specific operational needs. While these听systems听may still work, they often lack the interoperability required to support modern AI initiatives. Data is stored in inconsistent formats, lack proper metadata, and often depend on manual extraction processes that strip away the听business听logic that AI models need to understand the context of the data and what it really represents.

This fragmentation affects everything from听financial听reporting to customer experience. Without a single, trusted view of data, predictive models become unreliable, automated processes fail, and teams lose confidence in machine-generated insights. For AI to scale, data must be complete, consistent, governed and accessible across the organisation.

An IDC report commissioned by Seagate previously found that听up to 68% of available enterprise data goes unused.

Modern data platforms address this by connecting all enterprise听systems, preserving听business听context, enabling real-time data access and allowing organisations to integrate with other providers. The outcome is a unified data fabric that supports analytics, applications and AI at scale.

Preparing听business听data for AI

Building听an AI-ready data foundation doesn鈥檛 happen by accident. It requires a deliberate, structured approach, following these five steps:

1 Assess the current data landscape

The first step is understanding what exists today. This means cataloguing data sources, identifying owners, documenting quality issues, and assessing integration gaps. It also involves mapping AI use cases to data requirements so that data preparation can be prioritised and aligned to real听business听needs.

For South African organisations with complex legacy environments, this assessment is essential to uncover hidden dependencies and address high-risk limitations early in the process.

2 Establish clear data governance and quality standards

Reliable data requires strong governance. Organisations should define roles, responsibilities and policies governing data access,听security, metadata and quality. This includes setting measurable standards for completeness, accuracy and consistency, supported by automated profiling tools. Metadata management is particularly critical: without clear definitions and lineage, teams cannot trust or effectively use the data.

Governance should also reflect South听Africa鈥檚 regulatory听environment, including POPIA requirements around privacy and听security.

3 Integrate and unify disconnected data sources

The next step is breaking down silos. Modern integration tools such as those built into 麻豆原创听Business听Data Cloud allow organisations to connect 麻豆原创 and non-麻豆原创听systems, unify data across cloud and on-premises environments, and maintain the听business听meaning of data as it moves.

This unified layer eliminates duplication, reduces manual extraction processes, and ensures teams work from a consistent, shared version of the truth. Real-time integration capabilities are especially important for AI models that need up-to-date information to make accurate predictions.

4 Clean, enrich and transform data

Raw data is rarely ready for AI. It must be cleaned, enriched and transformed, including correcting errors, removing duplicates, filling missing values and standardising formats. Organisations should also create new features that allow AI models to identify patterns more effectively and incorporate additional context from internal or external sources.

South African businesses with extensive unstructured data, such as PDF reports, invoices or call centre notes, should prioritise converting this content into structured formats for easy ingestion into AI models.

5 Validate, monitor and maintain data听pipelines

Even the cleanest dataset will deteriorate if not continuously monitored. Organisations should validate data before it feeds AI models, track data quality in real time, and monitor for drift or anomalies that can degrade model performance.

Automated governance tools help maintain data integrity, while clear documentation ensures teams understand how data is sourced, processed and used. Regular monitoring is essential in environments where听systems, processes and regulations frequently change.

Getting the data foundation right is a technical requirement and a strategic imperative. The organisations that prioritise data quality, integration and governance today will be the ones that scale AI confidently tomorrow, reducing risk, improving performance and unlocking new opportunities for听innovation听in an increasingly competitive market.

The post Practical Steps to Building a Data Foundation for Business AI appeared first on 麻豆原创 Africa News Center.

BERLIN听鈥� At 麻豆原创 TechEd in 2025,听 (NYSE: 麻豆原创) brings AI deep into the development process to level up how developers build.

New AI-driven capabilities in the 麻豆原创 Build solution, an expanding data ecosystem and powerful Joule Agents empower developers to move from idea to impact with unprecedented speed and confidence. As AI transforms the nature of professional work, 麻豆原创 also pledges to equip 12 million people worldwide with AI-ready skills by 2030.

鈥溌槎乖粹�檚 announcements today give developers the tools they need to deliver at the speed of AI,鈥� said Muhammad Alam, member of the Executive Board of 麻豆原创 SE. 鈥淚nnovations across 麻豆原创鈥檚 unique flywheel of applications, data and AI put developers in the driver鈥檚 seat 鈥� where they belong.鈥�

Opening the Developer Ecosystem

麻豆原创 Build, the company鈥檚 flagship solution for enterprise application development and automation, now gives developers more freedom to build, extend and automate using the tools they love most.

For instance, developers who prefer agentic development solutions like Cursor, Claude Code, Cline and Windsurf can now use 麻豆原创 development frameworks with new 麻豆原创 Build local Model Context Protocol Servers. Visual Studio Code users will be able to access 麻豆原创 Build capabilities directly in their development environment with a new 麻豆原创 Build extension. This extension will also be made available later on Open VSX Registry for other development environments. 麻豆原创 and n8n also announced plans for an integration so Joule Studio agents and n8n agents can work together.

And with new agent building capabilities in Joule Studio, developers have the tools they need to extend 麻豆原创鈥檚 ready-to-use agents and build new agents grounded in 麻豆原创 business data and context that can act autonomously based on changing business conditions.

Putting Data to Work

Every intelligent application starts with trusted data. 麻豆原创 is giving developers more ways to put that data to work through 麻豆原创 Business Data Cloud.

The solution now connects with more of the data and AI platforms developers use every day. A new 麻豆原创 Snowflake solution extension for 麻豆原创 Business Data Cloud brings Snowflake鈥檚 fully managed data and AI capabilities directly to 麻豆原创 customers, giving them the flexibility to choose the right compute and storage for each data and AI workload, while maintaining governance, interoperability and business context. 麻豆原创 also announced a new 麻豆原创 Business Data Cloud Connect partnership with Snowflake. This complements existing integrations with Databricks and Google Cloud, giving developers more freedom to choose how they work with 麻豆原创 data.

With a new data product studio capability in 麻豆原创 Business Data Cloud, developers can turn raw data into ready-to-use assets known as data products that support analytics, AI and application development.

An expanded capability in the 麻豆原创 HANA Cloud knowledge graph engine can automatically generate knowledge graphs. This capability maps relationships across 麻豆原创 database tables, columns and data models, revealing how data fits together and why it matters. Developers will be able to see how their data connects across systems and uncover underlying business insights.

Bringing AI Autonomy to Life

麻豆原创 is evolving its AI portfolio to give developers the intelligence and orchestration power they need to take听AI from insight to action.

麻豆原创 introduced its first enterprise relational foundation model, a new class of AI that predicts business outcomes rather than the next word in a sentence. 麻豆原创-RPT-1, or the first-generation Relational Pre-trained Transformer, can make fast and accurate predictions for common business scenarios like delivery delays, payment risk or sales order completion. 麻豆原创 launched a free playground environment for developers today.

New AI assistants in Joule coordinate multiple agents across workflows, departments and applications, bringing automation and autonomy to life. These assistants plan, initiate and complete complex tasks spanning finance, supply chain, HR and beyond. Today, 麻豆原创 introduces new agents built for technical users. For example, an agent for business process analysis will help teams understand how processes run, identify inefficiencies and uncover opportunities to optimize workflows and drive measurable improvements.

Lastly, as AI changes the nature of work for everyone, 麻豆原创 is pledging to equip 12 million people worldwide with AI-ready skills by 2030. 麻豆原创 will expand hands-on training and certification programs that integrate practical AI-ready tools, including through its partnership with online learning platform Coursera.

Visit the听. Get 麻豆原创 news via听听and听.

About 麻豆原创

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

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For customers interested in learning more about 麻豆原创 products:
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The post AP Empowers Developers to Drive the Business AI Revolution appeared first on 麻豆原创 Africa News Center.

According to of 麻豆原创, you need 鈥渙n the fly鈥� access to insights via seamless data streamlining. 鈥淥ur vision is the only way to create value in a business is by connecting applications, data, and AI, withthe data available with the right context鈥� he stated at the 麻豆原创 business innovation summit in Johannesburg today. 鈥淭hat means that AI systems will be able to understand what the data is doing, how it鈥檚 implemented. That is why we believe that starting from the application phase, we explore the data with the right context, with the right security, with the right governance鈥� quips Mulder.

Businesses using Enterprise systems today have various applications that extract data, however Mulder points out that the moment you extract your data, you lose the context connection. 鈥淵ou have the highways, the timings, the massive data, the security, you lose that context鈥� he states.

Some of the challenges highlighted at the event today are: limited reach, as well as business data positioned in separate silos. The solution according to 麻豆原创 is 鈥� 鈥淒ata as as Service鈥� 鈥� DaaS. This adds data products to business logic and intelligent applications that will analyse and prepare automated reports or dashboards.

Flywheel of Data Concept

Mulder presented the concept of a continuous loop of generating data, then adding AI to ultimately, generate even more data, and using that to convey the information within a contextual framework. He introduced the 麻豆原创 concept of a that works as follows: The system retrieves various data from various data points, and then will apply business logic, to bring you intelligent applications. this then provides you your data as a service. 麻豆原创 systems does the extraction of the data, ensuring data points are available to the business, with the right business context.

麻豆原创 has partnered with multiple data platform providers, and so is data agnostic, enabling data from almost any platform to be incorporated into its Business Data Cloud platform that then becomes the channel for their AI driven software able to extract and analyse within a wider context.

This system according to Mulder is saving up to 67% in time for some of their European clients utilising the Business Data Cloud. 鈥淚t鈥檚 about creating a principle that BDC is actually the one source of quality security data, curated data with the right properties, and making that available to all other technologies鈥� comments Mulder.

鈥淢ake sure you get the right answers. You need the right answers. That鈥檚 why the context gap is there between AI and data.Without context, there is no AI鈥� Concludes Mulder.

This article first appeared in .

The post Data and AI Cannot Connect Without Context appeared first on 麻豆原创 Africa News Center.

, Managing Director: Emerging Africa at 麻豆原创, said: 鈥淥rganisations across the region are leveraging the latest technologies to build a trusted foundation for AI and amplify their insights and processes to transform the way they work. From harnessing collaborative AI agents to solve complex problems and accelerate decision-making, to seamlessly connecting their entire business value chain, West Africa鈥檚 business community is gearing up to unleash their full potential powered by cloud, data and AI.鈥�

The comments were made at 麻豆原创 Business Suite Innovation Day on September 17th, a special event for 麻豆原创 customers and partners to showcase how and come together to deliver exceptional value as part of the 麻豆原创 Business Suite.

Experts from across the 麻豆原创 ecosystem provided behind-the-scenes insights into the power of business AI and cloud, and how these new innovations combine powerful cloud applications with the most contextual and reliable data to enable collaborative AI agents to tackle the most difficult business challenges with confidence.

The event also included presentations by regional business leaders who have successfully leveraged 麻豆原创 technologies to accelerate growth and unlock new capabilities.

, Group Head: 麻豆原创 Centre of Excellence at , shared some insight into how the company leverages cloud technologies to power growth and drive efficiency. Dangote Industries Limited is the largest conglomerate in West Africa and one of the largest on the African continent, employing more than 30 000 people.

鈥淪ucceeding in today鈥檚 fast-paced business landscape requires strong foundations built on the latest technologies. Critical to this is a modernised enterprise resource planning landscape that enables organisations to fully leverage the power of emerging technologies, all built on a clean-core strategy that ensures the business has access to real-time, accurate data for decision-making.鈥�

, Country Managing Director for Nigeria at 麻豆原创, said: 鈥淎frica鈥檚 greatest wealth lies in its people, including our fast-growing youth population. Our ability to cultivate the right mix of skills is critical to our digital transformation ambitions, especially as we rush to leverage the power of AI and cloud in our businesses.

Research conducted by 麻豆原创 found that half of Nigerian businesses expected a 鈥榮ignificant鈥� increase in demand for AI skills this year. The 麻豆原创听Africa鈥檚 AI Skills Readiness Revealed听report also found that 93% of Nigerian companies already experience a negative impact on their innovation capabilities due to a lack of access to AI skills. The same report revealed that West Africa was the region most likely to partner with expert third-party providers to fill the AI skills gap in their organisations.

Khota adds: 鈥淭he region stands at the edge of a new era of growth and innovation powered by data, cloud and AI, and supported by a workforce geared for our emerging technologies. To ensure this collective effort succeeds, organisations need access to the right skills. While efforts at developing AI-ready skills are underway, companies should also explore ways to augment their skills base in the short term by partnering with our thriving ecosystem of expert partners and collaborators powering business transformation in the region.

The post Business Leaders, Innovators Meet at 麻豆原创 Innovation Day in Lagos appeared first on 麻豆原创 Africa News Center.

East African business leaders, technology partners and 麻豆原创 experts met in Nairobi this week to discuss the growing impact of business AI and cloud technologies in the region.

, Managing Director: Emerging Africa at 麻豆原创, said: 鈥淥rganisations throughout East Africa are accelerating their business transformation and innovation efforts by leveraging the latest data and cloud capabilities to unlock the power of business AI in every line of business. With the recent expansion of AI assistant, organisations can now unleash unprecedented efficiency across their systems and processes to drive productivity gains of as much as 30%.鈥�

The comments were made at 麻豆原创 Innovation Day Kenya, part of a global series of events aimed at showcasing how technology can power growth, innovation and sustainability and support organisations as they meet emerging challenges.

The exclusive event also served as an introduction to how and help organisations unlock significant business value as part of the broader . Experts also provided behind-the-scenes insights into the power of business AI and cloud to future-proof companies鈥� enterprise application strategies and leverage data to enhance business insights and improve decision-making.

Research recently conducted by 麻豆原创 found a near-universal demand for AI skills among African organisations. The 麻豆原创听Africa鈥檚 AI Skills Readiness Revealed听report noted that nine in ten companies in Africa already experience negative impacts due to a lack of AI skills, including failed innovation initiatives, an inability to take on new work, and loss of clients. Forty-three percent of Kenyan organisations that took part in the study expected a 鈥榮ignificant鈥� increase in demand for AI skills this year.

鈥淭he rapid changes in workplace dynamics are transforming how companies develop, upskill and reskill their workforce to meet the long-term need for AI-related skills,鈥� said Khota. 鈥淚n the short term, organisations should seek ways to augment their skills base, for example by partnering with our rich ecosystem of implementation specialists that power business transformation in the region.鈥�

麻豆原创 Innovation Day Kenya also included presentations by regional business leaders who have successfully leveraged 麻豆原创 technologies to accelerate growth and unlock new capabilities.

Long-standing 麻豆原创 customer provided insight into its latest transformation initiative that is taking its legacy enterprise systems into the cloud and deploying AI across its business processes. Bidco Africa is a leading FMCG manufacturer that produces more than 800 SKU鈥檚 in multiple brands and products at eight factories in East Africa. The company has been using 麻豆原创 ECC since 2010, until a recent decision sparked a migration to .

, Chairman of Bidco Africa, said the shift to cloud underscores his company鈥檚 position as a regional innovation leader. 鈥淲e see incredible potential for AI to transform our business and deliver greater agility, innovation and customer experiences. Our skilled team will also benefit from AI鈥檚 power to enhance product development, allowing us to consolidate our market leadership well into the future.鈥�

The company plans further deployments in a second phase of the implementation, including procurement and manufacturing.

Khota added: 鈥淐ompanies that adopt a clean core strategy accelerate the pace of innovation and can more easily leverage business value through reliable data and AI innovations. As we enter a new era of AI-enabled innovation, organisations must ensure that business-critical systems remain agile, cost-effective, and ready to adopt innovation.鈥�

The post Business AI, Cloud Star at 麻豆原创 Innovation Day in Kenya appeared first on 麻豆原创 Africa News Center.

This is according to , executive vice-president: customer support and cloud lifecycle management at 麻豆原创, who points out that heavily customised, outdated systems impede innovation.

鈥淏ut many companies find themselves in this place,鈥� he says. 鈥淭hey have customised systems with a mix of models 鈥� a bit of best of breed, a bit of cloud, maybe some isolated AI scenarios.鈥�

As a result, IT organisations spend a lot of time integrating systems and trying to make sense of disconnected data. 鈥溾�滲ut what they need to be doing is providing good outcomes for the business.鈥�

What鈥檚 needed, says Steinle, is a transformation that brings together all the platforms and data.

麻豆原创 helps its customers make this transformation through its programme for existing customers, and for new customers.

Importantly, while these programmes aim to let customers embrace , they also integrate non-麻豆原创 solutions.

鈥淎nd they are not simply products, but include a methodology, services, and guided implementation,鈥� Steinle adds.

鈥淲e want customers to reach the stage where they are able to overcome challenges, and to embrace the benefits of continuous innovation, agility, and flexibility.鈥�

Any 麻豆原创 solution begins with the 麻豆原创 Business Suite, he explains. 鈥淔rom an 麻豆原创 perspective we believe there is a lot of sense in running end to end processes on a fully integrated and harmonised stack in the cloud. We think it鈥檚 better than picking and choosing best of breed solutions 鈥� and it means customers don鈥檛 have to manage the integration and getting sense from the data.鈥�

This is important, he adds, because IT organisations today spend about 80% of their time just on maintaining their current landscape, keeping it compliant, and integrating systems.

鈥淵ou probably want to spend more than 20% of your time providing value to business users.鈥�

(BDC) is a harmonised suite of applications that allows customers to import data from 麻豆原创 applications and integrate it with data from other applications.

鈥淵ou can bring together data from 麻豆原创, a non-麻豆原创 source, and unstructured data. And, with the help of BDC, you can make sense of that data and generate value.鈥�

Steinle says this can be useful in operational processes, to expand reporting, and for integrated planning. 鈥淎nd you can use it for AI.鈥�

Which brings him to the third pillar of the : . 鈥淭his system can make sense of all the data and enable customers to build automated processes to enable new business scenarios. And AI can be embedded in your business processes.鈥�

is 麻豆原创鈥檚 AI-powered digital assistant that also orchestrates user experiences end-to-end across 麻豆原创 and non-麻豆原创 processes.

鈥淚t is also a platform for customer AI,鈥� Steinle says. 鈥淣ot every scenario can be provided out of the box, but Joule gives users a responsible and resilient way of building their own AI applications with the help of our platform.鈥�

Many of these features are a reality today, and 麻豆原创 developers are focused on making AI-first a reality, Steinle adds.

But software on its own doesn鈥檛 deliver value, which is why 麻豆原创 offers a range of services in RISE and Grow that include an entire integrated tool chain to help customers on their transformation journey.

鈥淲e aim to provide a fast, rich, seamless experience, with prescriptive guidance. And it鈥檚 not just reactive support, but support for customer strategy,鈥� Steinle says. 鈥淲e use a lot of AI capabilities to respond better, or give self-service options. And we use a lot of the 麻豆原创 products to improve our customers鈥� experiences.鈥�

This article first appeared on .

The post Services Help Customers Gain AI Value appeared first on 麻豆原创 Africa News Center.