Organisations need to combine intelligence with business context to make their operations predictive rather than reactive, according to SAP. The company says this is also important for adopting agentic AI and achieving a return on investment.
Emmanuel Raptopoulos, global president of customer success for Europe, Asia-Pacific, the Middle East and Africa at SAP, spoke to ITWeb following the recent SAP Connect 2026 event in Las Vegas.
“You need enterprise context to make meaningful decisions from information held in your systems. That is the foundation for moving from reactive towards predictive operations,” said Raptopoulos.
He added that organisations need an AI layer anchored in their operational context to respond faster and improve predictions. This involves more than data; it also encompasses how a company operates, makes decisions and uses its transactional systems.
He believes Africa could use emerging technologies to bypass some stages of technological development.
"We have seen technologies emerge in the past that allow markets to leapfrog previous stages of development. You do not necessarily have to go through every preceding step. I think Africa has another opportunity to leapfrog from a technology perspective. With an agentic approach, there is potential to jump a stage and apply the technology to areas such as transparency and efficiency in the public sector, citizen trust, access to public services and education," said Raptopoulos.
He said there is a lot of opportunity, but guardrails are extremely important.
"We should continue to apply judgment. Human judgment is here to stay. Governance, security and clear accountability are essential to managing autonomous systems safely."
Risks of AI agents
Raptopoulos acknowledged that AI agents could behave unpredictably even when rules and controls are in place, including measures to ensure they are task-specific and appropriately prompted.
“There is always a possibility. Our role as a vendor, together with our customers and their governance frameworks, is to control that probability. If you respect the design principles and put appropriate governance around the technology, you can reduce the probability significantly. Cyber security is also evolving alongside AI capability. The same underlying technological capabilities can be deployed defensively,” he said.
“You therefore need the right governance internally while heightening external defences to create a shield around your systems. The objective is to prevent this becoming an issue in future.”
Dr Pierre le Roux, MD of digital consultancy MOYO, said AI is moving from technology that tells people what they can do to technology that can increasingly do it for them.
That shift could pose a major governance challenge as businesses move from generative AI and copilots to autonomous AI agents that can access systems, initiate transactions, communicate with customers, change data and execute business processes, said Le Roux.
“Until now, much of the AI conversation has been about the accuracy of the answer,” he added. “Agentic AI changes the question. If the technology is able to take an action, the issue is no longer simply whether the answer was right or wrong. You have to ask who gave it permission to act, what it was allowed to access, where its authority ended and, ultimately, who is accountable for the outcome.”
Le Roux said the issue is becoming more urgent as businesses move beyond AI experimentation. He cited a Gartner prediction that by 2027, 40% of enterprises could demote or decommission autonomous AI agents because governance gaps are discovered only after deployment.
“AI may execute the decision, but accountability remains with the organisation that designed the process, gave the agent access and determined its authority. The question is no longer whether you trust AI, but whether your organisation has engineered the boundaries within which AI is allowed to act.”
Raptopoulos said companies were increasing their investment in AI and integrating it into their operations, but questions remained about their ability to control agents operating within their systems.
“Awareness has risen. Recent high-profile events have helped make the issue visible even beyond people who are highly technically literate,” he said.
“The concern is that you do not want agents moving around enterprise systems in ways that could make data available to the wrong person. That is a potential boardroom nightmare. One important design principle is to make agents very specific about what they are supposed to do and give them clearly defined objective functions. An agent is ultimately an application trying to fulfil an objective. If that objective is defined too broadly, it has greater scope to find unintended ways of fulfilling it. Agents should therefore be specific to the task at hand and grounded in the enterprise objective.”
Share
