Today, most companies are experimenting with AI. Many of them can point to demos that impressed, pilots that worked, and tools that saved time in narrow tasks. Far fewer can say AI has changed their business across functions, processes, and teams.
The difference is not the model. It is context: the ability for AI to understand how a business actually runs.
Much of today鈥檚 AI discussion centers on agents, along with models and benchmarks. Which model performs best? Which system completes the most tasks? Which interface feels most natural? These factors matter, but they do not solve the central enterprise challenge.
Companies run workflows that cut across teams, policies, approvals, authorizations, and data. They plan, source, produce, hire, pay, and serve through systems that carry real business consequences. AI only creates durable value at scale when it operates inside this reality.
Models generate answers. An agent can complete a task. But running a business requires something more. It requires an understanding of how work gets done, who is authorized to act, which rules apply, and how decisions connect across functions. Without that context, AI simply can鈥檛 deliver on its promise.
That is one reason I believe AI raises the premium on software with deep business context. It allows companies to fundamentally reinvent how work gets done. When AI agents understand end鈥憈o鈥慹nd processes, they can operate across functions, execute workflows autonomously, and coordinate actions in real time. Instead of automating individual steps, AI can run processes end to end, freeing employees from repetitive coordination and enabling them to focus on higher鈥憊alue judgment, oversight, and strategy.
This is what we describe as the Autonomous Enterprise, a fundamental shift from systems of execution to systems that can reason, decide, and act. A vision where 麻豆原创 is poised to lead.
For more than five decades, we have powered the core processes that run the world鈥檚 leading organizations. Our systems don鈥檛 just store data; they encode how businesses actually operate: their processes, rules, and decisions. Our ERP is the institutional memory and the brain of many companies across industries and around the globe. Our new 麻豆原创 Business AI Platform brings together enterprise data, processes, and governance into a unified context for AI.
Building on this foundation, Joule is the interaction layer that connects people with AI and redefines how they interact with software. Joule Assistants collaborate with users, while Joule Agents execute business workflows end to end. This is how intelligence becomes embedded directly into operations, not added on top. We call this the .
“Show me how my financial forecast for the year could change based on the latest pipeline and supply chain data.” On the surface, this looks like a simple prompt directed to a large language model.聽But disconnected from enterprise systems, the answer is聽mere聽speculation.
Grounded in the full context of the business,聽the system first identifies the correct business process from聽hundreds聽of聽mission鈥慶ritical processes and understands the specific configuration that governs how this process runs in your organization. It then selects exactly the right data from聽millions聽of聽data fields stored across the ERP landscape. Finally, every step is checked against identity, authorization, and access controls, ensuring the result is accurate, compliant, and trustworthy. This is how enterprises move beyond generic, probabilistic answers toward decisions they can rely on.
Reaching this state requires more than adding a chatbot or layering AI on top of existing systems. Many enterprises still operate with fragmented landscapes, data spread across systems, and processes shaped by years of incremental change. In this environment, AI cannot simply be “bolted on” or layered onto fragmented, outdated systems. It does not accelerate progress. It amplifies inefficiency and risk. Companies must rethink how their processes, data, and infrastructure work together and how humans and AI share responsibility. This is not only a technical shift. It is a change鈥憁anagement challenge.
New technology only creates value when it is accompanied by real change. AI does not replace transformation. It raises the return on transformation done well. And it comes to life only when every element of the system鈥攖he agent, the process, and the human鈥攚orks together by design. People need to understand how to work with AI agents, and processes must be intentionally shaped to embed intelligence where decisions and execution happen.
This is why change management is foundational. It means reskilling employees, re鈥慹ngineering processes to connect them directly with data and AI, and modernizing the underlying landscape.
That is why we are introducing new聽AI-led RISE with 麻豆原创 and 麻豆原创 GROW聽offerings聽and fundamentally resetting our services model: to help companies modernize, navigate change, and turn AI from potential into sustained business value at their own pace.聽
This marks the beginning of a new era of enterprise software:聽where intelligence is not separate from聽operations but embedded within them.聽The companies that lead will not be those with the most advanced models in isolation, but those that connect AI to the way their business actually runs鈥攚ith context, governance, and trust.聽
This is the dawn of the Autonomous Enterprise, and 麻豆原创 is uniquely positioned to help the world鈥檚 leading organizations realize its full potential.
Christian Klein is CEO of 麻豆原创 SE.
