The timing could hardly have been more pointed. Across the world, executives are losing patience with AI experiments that overpromise and underdeliver. Boardrooms have heard enough about pilots and proofs of concept, and now want systems that improve margins and forecast outcomes.

TechEd took place in that atmosphere, amid assurances that performance could replace promise. 麻豆原创 used the event to demonstrate how deeply AI now runs through its own operations before unveiling its next leap forward.

Rather than another round of hype about possibilities, 麻豆原创 aimed to show a working example of AI at scale, handling everyday complexity inside one of the world鈥檚 largest software organisations.

麻豆原创 chief technology officer and chief AI officer, Philipp Herzig, told Business Times at TechEd that the clearest evidence of maturity came from within 麻豆原创 itself. The company鈥檚 AI assistant, Joule, acts as a conversational layer across its software stack, connecting data, applications, and agents to automate tasks and surface insights on demand.

鈥淚f you look at AI at scale, what is really real and what is working very well, just look at Joule,鈥� he said. 鈥淚t鈥檚 used by more than 30,000 employees every month, about a third of the 麻豆原创 workforce. We have more than 100,000 policies and documents in different languages, and depending on where you work, in Brazil or South Africa, you get the correct HR or travel policy surfaced to you.鈥�

Herzig said Joule had become the company鈥檚 single interface for daily tasks. 鈥淵ou can do your expense reports, indirect procurement, and financial tasks all in one place. It works, and it works at scale. We have a thumbs-down rate of only 1%, which is phenomenal when you think about the size of the company.鈥�

Innovations across 麻豆原创鈥檚 unique flywheel of applications, data and AI put developers in the
driver鈥檚 seat 鈥� Muhammad Alam, 麻豆原创 executive board member

That success set the stage for TechEd鈥檚 central announcement: an AI model called 麻豆原创-RPT-1, short for relational pre-trained transformer. The model introduces a new class of AI: the enterprise relational foundation model. It interprets structured business data and the relationships within it, mapping how orders, invoices, logistics, and payments interact to forecast what comes next.

麻豆原创 described it as a model that 鈥渃an make fast and accurate predictions for common business scenarios like delivery delays, payment risk or sales order completion鈥�. Instead of producing text, it reads how data behaves across systems, turning business logic into predictive insight.

Herzig said 麻豆原创-RPT-1 marked the transition from incremental automation to full predictive architecture.

鈥淲e see a shift from what I call a cloud-native architecture to an AI-native architecture, as AI becomes an ever-increasing part of the software stack. 鈥淲hat we wanted to solve are the problems where we have a reason to solve them: because we have the data, the relational data, the structured business data and so on. We set out this research project two years ago, talked a little about it, but now it actually becomes a reality.

鈥淚t鈥檚 a shift that needs several things to come together: the knowledge graph, this predictive model now with RPT-1, and of course the large language models. So there are many elements in the software stack that change. Every day, each little piece adds to this picture and solves a particular challenge in the stack.鈥�

Herzig said the greatest challenge lay in making this intelligence work at enterprise scale.

鈥淎nyone can do a demo. Getting it enterprise-ready at scale 鈥� that鈥檚 the tough challenge. That鈥檚 why we鈥檙e solving one problem after another, each for a specific outcome in the overall stack.鈥�

麻豆原创 executive board member Muhammad Alam tied this philosophy to the developer community.

鈥溌槎乖粹�檚 announcements give developers the tools they need to deliver at the speed of AI,鈥� he said.

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�

That 鈥渇lywheel鈥� anchored the narrative of TechEd:
鈥� applications generate data;
鈥� data trains predictive models;
鈥� models return intelligence to the applications.

Each loop strengthens the next, creating a flywheel effect of acceleration of innovation. 麻豆原创 announced that it would equip 12-million individuals worldwide with AI-ready skills by 2030 through a partnership with Coursera that provides hands-on certification in 麻豆原创鈥檚 ecosystem. The goal is to align those skills with the AI-native architecture now taking shape inside the company. It also sends the message that people remain at the heart of the AI journey.

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麻豆原创 has taken artificial intelligence beyond the realm of language. At the 麻豆原创 TechEd 2025 conference in Berlin this week, the company introduced a new class of AI designed to predict business outcomes rather than words. The result is what 麻豆原创 claims to be the first enterprise relational foundation model, called 麻豆原创-RPT-1, or Relational Pre-trained Transformer.

It represents a shift in what a foundation model can be: rather than being a generator of sentences, it is a predictor of decisions.

麻豆原创 describes 麻豆原创-RPT-1 as an AI that 鈥渃an make fast and accurate predictions for common business scenarios like delivery delays, payment risk, or sales order completion鈥�. It uses the relationships between business data rather than linguistic patterns to anticipate what happens next in an organisation鈥檚 operations. In simple terms, it reads the business, as opposed to mere text.

To encourage developers to explore what that means in practice, 麻豆原创 has launched a free playground environment where they can test predictive scenarios, simulate business situations, and see how relational AI behaves when exposed to live data. For developers accustomed to fine-tuning language models, it represents a different kind of creativity, rooted in the mechanics of business itself.

鈥溌槎乖粹�檚 announcements today give developers the tools they need to deliver at the speed of AI,鈥� says Muhammad Alam, member of the executive board of 麻豆原创. 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�

That flywheel was clearly visible across the rest of TechEd鈥檚 announcements.

The company鈥檚 麻豆原创 Build platform, its centrepiece for enterprise application development and automation, has been re-engineered to give developers more freedom to use tools they already rely on.

Developers who prefer agentic development environments like Cursor, Claude Code, Cline and Windsurf can now use 麻豆原创 development frameworks through new 麻豆原创 Build local Model Context Protocol Servers. Visual Studio Code users can access 麻豆原创 Build capabilities directly in their existing development environment via a new 麻豆原创 Build extension, which will later also appear in the Open VSX Registry for use with other development environments.

麻豆原创 revealed plans for integration with automation platform n8n, allowing its Joule Studio agents to work alongside n8n鈥檚 own agents. This kind of cross-agent collaboration reflects the company鈥檚 growing emphasis on orchestration: enabling multiple intelligent systems to coordinate tasks across applications and departments.

The data layer that feeds these systems is also evolving. Every intelligent application depends on trusted data, and 麻豆原创 is extending its reach through 麻豆原创 Business Data Cloud. A new 麻豆原创 Snowflake solution extension brings Snowflake鈥檚 managed data and AI capabilities directly to 麻豆原创 customers, giving them 鈥渢he flexibility to choose the right compute and storage for each data and AI workload, while maintaining governance, interoperability and business context鈥�.

The announcement was reinforced by a new 麻豆原创 Business Data Cloud Connect partnership with Snowflake, adding to existing integrations with Databricks and Google Cloud. The result is a more open, federated data ecosystem that lets developers work with 麻豆原创 data wherever it resides.

A new data product studio capability in 麻豆原创 Business Data Cloud now allows developers to turn raw data into ready-to-use assets known as data products, designed for analytics, AI and application development. At the same time, the 麻豆原创 HANA Cloud knowledge graph engine can automatically generate knowledge graphs. This means it maps relationships across 麻豆原创 database tables, columns, and data models to reveal how data fits together. For developers, it is a new way of seeing how information connects across systems, turning structure into insight.

麻豆原创 is also extending its Joule AI portfolio, which now includes new assistants that can coordinate multiple agents across workflows, departments and applications. These assistants are designed to 鈥減lan, initiate, and complete complex tasks spanning finance, supply chain, HR, and beyond.鈥�

Among the new offerings is an agent for business process analysis, helping teams understand how processes actually run, identify inefficiencies, and uncover opportunities to optimise workflows and achieve measurable improvements.

麻豆原创 pledged to equip 12-million people worldwide with AI-ready skills by 2030, through a partnership with Coursera that expands hands-on training and certification in practical AI tools. The goal, 麻豆原创 says, is to make AI accessible to 鈥減eople everywhere鈥�.

*听Arthur Goldstuck is CEO of World Wide Worx, editor-in-chief of听, and author of听The Hitchhiker鈥檚 Guide to AI 鈥� The African Edge.

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The most powerful decisions inside modern enterprises may well arise beyond boardrooms. They can now emerge from听systems听that learn, adapt, and act before anyone issues a command. In other words, intelligence no longer needs to wait for permission.

That compelling scenario was painted at Saphila 2025, the biannual conference of the African 麻豆原创 User Group (AFSUG), held at Sun City this week. The event drew together technology leaders and enterprise architects from across the continent, focused on the impact of AI, cloud, and digital transformation on African business. In keynote sessions and breakout talks, a unifying theme emerged: the听systems听that drive operations are beginning to think for themselves.

In one of the most compelling sessions of the event, , chief strategy and innovation officer for 麻豆原创 EMEA North, described the concept as 鈥渁uto-sapiens听systems鈥�. Such enterprise technologies act with purpose, interpret context, and make decisions inside live business processes.

鈥淭hese听systems听follow purpose and context by design,鈥� said Schleimann in his talk. 鈥淭hey act because the logic, the purpose, and the data already exist inside them.鈥�

They handle invoice reconciliation, adjust logistics, dispatch field service teams, and optimise supply chains, all in real time. Tasks once dependent on manual triggers or lengthy approvals can now be executed automatically, with speed and precision.

鈥淭hese听systems听operate with embedded awareness,鈥� he said. 鈥淭hey apply intelligence where it matters most: inside the flow of work.鈥�

It sounds like the concept of agentic AI that giants like Google, Salesforce and Microsoft regard as the next big thing, but it is more like the next next big thing.

鈥淚ntelligence lives inside the process,鈥� he told Gadget on the sidelines of Saphila. 鈥淚t aligns with context and delivers relevance. That creates real transformation.

鈥淭he process creates data, the data provides context, the context feeds intelligence, and the intelligence improves the process. That鈥檚 the flywheel. Each turn makes the system more effective.鈥�

This dynamic feedback loop enables continuous refinement without waiting for external intervention. AI could not be separated from the action or bolted on.

鈥淭his has to be at the heart of the vehicle. It has to be embedded from the beginning. When you open up an application, you鈥檙e not just seeing a blank sheet. It will immediately have a level of insight that supersedes your own. That鈥檚 really the big thing: bringing the ontologies of data together with your own business and AI.

鈥淚t鈥檚 not about putting a brain on top. It鈥檚 about making the system itself intelligent.鈥�

But it is also not about doing away with human beings. Schleimann believes this issue is deeply relevant to South Africa.

鈥淵ou have a great tradition for mining. You have great natural resources. Now we鈥檝e got to mine our people and our data.鈥�

In his vision, the raw material of the future is not underground, but embedded in enterprise听systems, processes, and minds. This shift, 鈥渇rom mine to mind鈥�, as he puts it, redefines value creation. It is now about extracting insight from operational truth, refining it through AI, and using it to unlock human potential.

鈥淭hat really is your moat long-term as an enterprise. Bringing people together with that data and unlocking their minds.鈥�

This, he suggested, requires more than dashboards and data lakes. It calls for a transformation in how intelligence is designed, applied, and trusted, by every layer of the organisation.

Schleimann鈥檚 outlook extends beyond automation. 鈥淎I can make me better. It can bring out the best in me and help coach me. As we see AI increasing the productivity of people, the demand for people will go up. From an enterprise viewpoint, upskilling, reskilling, and change management will be the new competitive advantage.鈥�

This human-centred view stands in sharp contrast to fear-based narratives around AI job displacement. Schleimann sees an urgent imperative for organisations to elevate their people alongside their听systems, or risk being outpaced by competitors that do.

麻豆原创鈥檚 latest S/4HANA enterprise resource platform reflects this mindset. It includes generative agents, embedded analytics, and intelligent workflows. These are defaults rather than add-ons.

鈥淲e don鈥檛 treat AI as a feature. It has to be part of the foundation from day one.鈥�

Across industries, the results are tangible. Healthcare workflows accelerate. Educational content adapts. Procurement uncovers anomalies before they cascade. Each result builds from live intelligence, acting at the speed of need.

* Arthur Goldstuck is CEO of World Wide Worx, editor-in-chief of听, and author of The Hitchhiker鈥檚 Guide to AI.

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Juergen Mueller, chief technology officer of German software giant 麻豆原创, used the phrase during his keynote address this week at the 麻豆原创 TechEd 2023 conference in Bengaluru, the Silicon Valley of India, when he described the endless uses of AI that had suddenly become possible.

A few days earlier the world鈥檚 biggest PC maker, Lenovo, unveiled a comprehensive suite of AI capabilities and an 鈥淎I for all鈥� strategy at its Tech World 2023 event in Austin, Texas. Lenovo chair and CEO Yuanqing Yang was joined on stage by the CEOs of two of the world鈥檚 biggest chip makers, Nvidia鈥檚 Jensen Huang and AMD鈥檚 Lisa Su. The event was addressed via video by Microsoft chair and CEO Satya Nadella, Qualcomm CEO and president Cristiano Amon, and Intel CEO Pat Gelsinger.

Yang announced that expanded partnerships with these organisations would help businesses deploy custom generative AI applications. The generative AI revolution sparked by the launch of ChatGPT at the end of November last year has also sparked fears of economic and social disaster. This prompted British Prime Minister Rishi Sunak to convene this week鈥檚 summit in England that led to more than 25 countries and the EU signing the 鈥淏letchley Declaration鈥� establishing a common approach to AI oversight on Wednesday.

On the same day, Microsoft began selling its highly anticipated Copilot AI add-on for its Office software, targeting large enterprises. It is expected to add billions of dollars in annual revenue for the world鈥檚 biggest software company.

麻豆原创, ranked number three globally in software sales, works closely with Microsoft, but has developed its own AI platform, Joule, with the catchphrase: 鈥淭he AI copilot that truly understands your business.鈥�

On Thursday, Mueller announced a comprehensive series of new generative AI capabilities aimed directly at developers. Combined with the Microsoft Copilot release and the Lenovo announcements, it underlined the extent to which software and hardware giants are pushing the AI envelope.

鈥淭oday鈥檚 dynamic technology and business landscape means every developer needs to be an AI developer,鈥� said Mueller in his keynote address. 鈥淭he innovations we鈥檙e launching at 麻豆原创 TechEd [are] supporting the developers at the heart of the AI revolution and providing them with resources they need to transform the way businesses run.鈥�

He unveiled 麻豆原创 Build Code, which draws on Joule to boost productivity by embedding code generation capabilities for AI systems and applications. He also announced a 鈥渧ector database鈥� that would manage unstructured data, such as text, images or audio, and provide long-term memory and context to AI models.

鈥淔or example, users can search for suppliers based on the language in their contracts to examine payment history and trace听 individual orders. These powerful new vector database features enhance interactions between large language models and an organisation鈥檚 mission-critical data.鈥�

麻豆原创 chief marketing officer Julia White joined Mueller on stage and revealed that most developers creating and extending 麻豆原创 solutions were working at partner organisations. Of the more than 2,000 partner solutions available in the 麻豆原创 software store, she said, more than 400 already offered AI as part of the solution.

鈥淚f I look where AI is going, I imagine that every person working across the world has that smartest colleague right by their side, helping them” – 麻豆原创 chief marketing officer Julia White

She told Business Times that AI promised a bright future for any working person. 鈥淚f I look where AI is going, I imagine that every person working across the world has that smartest colleague right by their side, helping them, like the AI serving up those insights that you might not have discovered otherwise, or connecting dots in a new way to unlock new insights and making everyone more productive or capable. And also, of course, doing it responsibly.鈥�

Five years from now, she said, everyone will have 鈥渢hat partner at our side, that AI capability, with us. And it’s going to be very natural 鈥� I think it’s going to become almost invisible 鈥� but in a way where there’s still humans at the wheel but the technology is invisibly powering us.

鈥淥ne of the fundamental problems of the world today is communication breakdowns, and not everyone is a brilliant communicator. That leads to a lot of animosity and difficulty that, if we had fantastic communications across the globe, we wouldn’t face. What if we all were brilliant at it, and we can understand each other better? I think we’re all learning fast and we’ll adjust from there. We’re trying to create an experience that is more assisting a human than doing it on behalf of a human.鈥�

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Last week, three of the world鈥檚 biggest technology organisations unveiled their visions for a future of business that will see a revolution in efficiency.

麻豆原创, the German company that leads the world in enterprise resource planning (ERP) software, search giant Google, and chipmaker Intel, all hosted major international events where they launched new products and services, and provided a glimpse of the future of business.

麻豆原创 in particular, at its annual Sapphire event in Orlando, Florida, signalled an acceleration of efforts to bring greater intelligence to the systems that run organisations鈥� operations.

Google鈥檚 annual I/O developer conference was heavy on new consumer gadgetry, in particular plans to launch a Pixel smartwatch later this year. However, it also introduced artificial intelligence (AI) productivity tools that will, among other, provide instant summaries of long documents. Meanwhile, Intel unveiled a new generation of computer processors that will reduce the time it takes to train large-scale AI models.

But it was 麻豆原创 that provided the clearest picture of how businesses are likely to operate in the near future. And one word stood out: efficiency. We asked chief technology officer Juergen Mueller to look into his crystal ball.

Before that, however, during a keynote address at Sapphire, 麻豆原创 CEO Christian Klein said that the company planned to draw on data about best practices from more than 40,000 customers. It would leverage Signavio, an enterprise business process intelligence platform it acquired last year, which helps companies transform and manage their business processes at scale.

This, he said, would allow business and IT leaders to discover new growth opportunities and launch new business models, as well as uncovering inefficiencies in internal processes. This would lead to a revolution in business efficiency.

Later, he told Gadget: 鈥淲hen you think back 50 years, there鈥檚 so much knowledge inside 麻豆原创 and in our ecosystem, we implemented and designed so many business processes, now we really have our finger on the pulse of how they need to change in a digital world to create a seamless experience.

鈥淲e are collecting all of the data, the best practices, not only from 麻豆原创, but also from all our partners. That鈥檚 a big differentiator of Signavio: You don鈥檛 need to replicate data in a third-party data mining tool. You can use your data and then you can benchmark it against how these business processes look in your industry.鈥�

麻豆原创 chief technology officer Jurgen Mueller, said in an exclusive interview that this capability would change the way businesses make decisions.

鈥淲e acquired Signavio for a reason: we saw there鈥檚 a gap in our portfolio,鈥� he said. 鈥淚t鈥檚 very important to customers to understand the business processes and we鈥檝e modelled business processes for 35 years or so, but they were often a separate artifact, so your processes are not connected to your execution.

鈥淪ignavio gives you an X-Ray into your real processes and execution. That has to be the foundation, grounded in reality, from where you then can change, find efficiencies, find how you can do things better, how you can serve your customers faster. Companies often have a good idea where they want to go, but today this X-Ray doesn鈥檛 exist.鈥�

Signavio, however, will allow any size company to access the kind of business intelligence that has enabled tech giants like Microsoft, Amazon, and Google to have an instant insight into their business processes. From there they have been able to implement a solution and assess its success within minutes, replacing or improving it before most customers know it existed. However, this is not possible without the ability to mine massive amounts of data on the fly 鈥� an ability previously restricted to the giants.

鈥淲e have tens of thousands and potentially hundreds of thousands of other companies that can now get such a detailed level of understanding of their processes,鈥� says Mueller. 鈥淲e learn and develop industry-specific best practices in 25 industries, and we can bring the best of what we know to customers.鈥�

The end-result, he says, is vastly improved efficiency. However, that in itself is not a differentiator, if all companies become more efficient. Efficiency, in effect, becomes a ticket to the game.

鈥淲e see a huge difference in companies that really embrace digital technologies, and who always want to create differentiating capabilities through technology, compared to the ones that are just using technology where they have to.鈥�

Mueller says he does not believe there is a single differentiator between the more competitive companies and those who fall behind. However, 麻豆原创 has discovered a strategy that helps set companies apart: 鈥淥ften you see companies really go through the end-to-end processes of their the value chain, to identify the most value-generating activities in the company 鈥� and then pick a few where you really make a difference.鈥�

While this approach is not a secret, it has tended to evade organisations because it requires an integration of strategic planning and supplier data across the entire logistics chain. Mueller is frank about the limitations of existing technology in this regard.

鈥淚ntegrated planning is something that will happen in the next three to five years. We have components of that already, but this will be something where I see a lot of innovation happening, with real impact on companies.鈥�

• Arthur Goldstuck is editor-in-chief of Gadget. He was a media guest of 麻豆原创 at the Sapphire conference in Orlando, Florida.

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