At the World Economic Forum this week, e& and IBM unveiled an enterprise-grade agentic AI system designed to operate inside the most sensitive parts of a company: governance, risk, and compliance.
This isn’t a conversational assistant meant to sound smart in demos. It’s AI built to reason, take action, and explain itself—inside systems where every decision may be audited.
Why this announcement matters
Most large companies are stuck in AI limbo. Pilots look impressive, but scaling them runs straight into a wall of regulation, accountability, and risk. Agentic AI raises the stakes even further, because these systems don’t just answer questions—they can trigger workflows and decisions.
That’s where this collaboration draws a clear line.
e& is embedding agentic AI directly into its compliance infrastructure, powered by IBM watsonx Orchestrate and integrated with IBM OpenPages. The goal: give employees and auditors fast, traceable access to regulatory and policy intelligence—without sacrificing oversight.
From chatbot experiments to operational AI
Unlike typical enterprise chatbots that sit on top of data, this system lives inside core governance workflows. It can pull from approved policy sources, explain how it reached an answer, and operate within predefined controls.
That distinction matters. Regulators don’t care how fluent an AI sounds. They care whether decisions can be explained, reproduced, and challenged.
IBM says watsonx Orchestrate brings more than 500 tools and domain-specific agents into a governed environment, allowing organizations to design AI that acts—but only within clearly defined boundaries.
Proving it works under real conditions
This wasn’t just a slide-deck reveal.
IBM, Gulf Business Machines (GBM), and e& delivered a working proof of concept in roughly eight weeks, testing whether agentic AI could function reliably at enterprise scale. IBM’s Client Engineering team led system design and integration, while GBM supported deployment across e&’s existing governance stack.
The outcome demonstrated something many enterprises are still skeptical about: that agentic AI can operate in production without becoming a compliance liability.
Executives frame it as a trust problem
“Our ambition is to move beyond isolated AI use cases toward enterprise-scale agentic AI that is trusted and governed,” said Hatem Dowidar, Group CEO of e&.
From IBM’s side, Ana Paula Assis pointed to a shift happening across industries. As companies move from experimentation to deployment, governance is no longer a feature—it’s the foundation.
The bigger signal from Davos
Zoom out, and this announcement fits a broader trend playing out at Davos: enterprises are done chasing flashy AI demos. The next phase is quieter, slower, and far more consequential—embedding AI into systems that actually run organizations.
By focusing first on policy, risk, and compliance, e& is taking what may be the least glamorous—but most strategic—path to scaling AI responsibly.
If agentic AI is going to become mainstream inside large enterprises, this is what it will likely look like: constrained, explainable, and deeply integrated.
Conclusion
This isn’t about AI sounding human. It’s about AI behaving responsibly.
At Davos, e& and IBM made a case that the future of enterprise AI won’t be won by the smartest model—but by the one companies can trust under scrutiny.