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IBM: Agentic AI is reshaping governance, controls and trust

As AI agents move from answering questions to making decisions and acting, businesses face a growing challenge of keeping accountability in step with the pace of change.

LONDON -- Agentic AI is changing business operations, but the pressure to keep up with rapid advancements means many are using tools without knowing where they will lead.

That was a central theme at IBM’s Think on Tour EMEA 2026 conference on Wednesday, where executives argued that trust, governance and oversight are now as important to business outcomes as transformation itself.

In her keynote, Ana Paula Assis, senior vice president and chair for EMEA and APAC at IBM, said 80% of executives expect AI to drive revenue growth, yet only 20% can explain exactly how that will happen.

The stakes are rising as businesses move beyond chatbots toward agents capable of carrying out tasks and making decisions with less human intervention. IBM research presented at the event found that three-quarters of surveyed executives across EMEA expected an agent to execute a complete business task and make a decision without human intervention by 2027. Meanwhile, 80% said at least one AI-related problem had reached the boardroom or C-suite.

“The question now is: Can we operate it at scale safely, reliably?” Assis said. “That is not a technology problem. That is an operating problem, and it requires a fundamentally different, new AI operating model.”

Applying AI without losing control

Michael Nimhauser, global head of sovereignty at Atos, a France-based IT services and consulting firm, said organizations were attracted by AI’s potential but worried about losing control as adoption accelerated.

“With all of the stars in their eyes and the potential, they also have a lot of fear of loss of control,” he said.

That concern extends beyond where data is stored to include control over infrastructure, models and the systems coordinating AI agents. To combat this, Nimhauser (alongside other speakers at the conference) argued that governance must be built into the architecture from the outset.

“It needs to be by design,” he said. “It cannot be an afterthought.”

Celerity, an IBM partner that uses IBM’s AI-powered software development tool Bob internally, has taken a parallel approach to AI adoption and governance. The company assesses applications for their potential business value and ROI, while a separate governance review considers risk, data and access.

Craig Aston, CEO of the U.K.-based managed services provider, said businesses need to encourage employees to identify opportunities to use AI, without allowing enthusiasm to outpace appropriate controls.

“Having governance run alongside the adoption for me is the most important point,” he told TechTarget. “It’s really important that we don’t quell the energy of innovation, and we really do want our teams to come to us with ideas. But it does ultimately come down to risk and, if you get it wrong, it could bring a company down.”

Keeping humans involved

U.K. insurer Markerstudy has also been deploying Bob, using it to help assess the risks and options involved in modernizing legacy technology.

The company used Bob to analyze six million lines of code in a core insurance system it built over roughly 30 years. The review took four weeks and produced a heat map to help identify which parts of the system were most relevant to its future needs.

Previously, Markerstudy could examine only sections of the code and extrapolate from them. The wider analysis helped inform a targeted modernization program, rather than a wholesale replacement. CTO Dan Fiehn noted, however, that the process did not entirely place decisions in the hands of AI.

“We kept our team in the loop throughout the process,” Fiehn told TechTarget. “It wasn’t a ‘fire-and-forget.’ We had people validating output and training the models. But what Bob did do here is move something that was quite a subjective decision to make it quite objective.”

For Fiehn, the objective was not simply to deploy more AI, but to use it to improve decision-making. “We don't think it's about who deploys the most AI wins,” he said. “We feel it's more about delivering measured outcomes that give better decisions for our customers and our colleagues.”

IBM’s answer: a new operating model

IBM is positioning its hybrid cloud and AI offerings as part of its response. Assis argued that AI initiatives can struggle when data is isolated and infrastructure fragmented.

“There is no good AI without good data,” she said.

IBM has introduced Sovereign Core, an open source platform intended to give organizations greater control over the deployment and operation of AI environments. The company is positioning it as one option for businesses seeking to manage data, operations and governance as AI adoption grows.

Regardless of the platform they choose, businesses will need to embed governance and controls into their AI strategies from the outset, conference attendees said.

“AI is no longer just supporting the business,” Assis said. “It has become the business model. The organizations pulling ahead are not just adding AI, but rethinking how systems, decisions and processes work together with AI.”

Scarlett Evans is a freelance writer with a focus on robotics and emerging technologies. Previously, she was assistant editor at IoT World Today, where she specialized in robotics and smart city technologies. Scarlett also has a background in the mining and resources sector, with experience at Mine Australia, Mine Technology and Power Technology.

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