XFactorAi chief executive John Margerison has predicted that AI systems will take on around a third of CEO workloads by 2028, arguing that senior leaders will increasingly offload repeatable operational tasks to software while focusing more heavily on strategy, change, and face-to-face leadership. His comments come as businesses continue to test how generative AI might fit into senior management workflows.
Margerison said the shift would be driven by the amount of executive time still spent on tasks such as data analysis, report compilation, routine sign-off, and other repeatable processes. “There is a growing realisation that the CEO role is set to change in very deep ways. That shift will transform not just the CEO’s role, but the day-to-day work for the wider C-suite as well,” he said. He added: “Right now, a significant share of executive leadership time is spent on operational activity, such as analysing data, compiling reports, signing off routine actions, and handling other repeatable tasks.”
His forecast is that at least a third of that activity will move to AI over the next 18 to 24 months. Margerison said XFactorAi had already demonstrated elements of that model by combining sales, marketing, and writing capabilities within executive AI tools. He argued that the more meaningful question for larger organisations is no longer whether AI will reach the executive suite, but how quickly it can be deployed in a way that leaders, employees, and regulators are prepared to trust.
That trust gap, he said, remains one of the biggest barriers. “Many regulators still view AI as a black box, where decision-making cannot be properly or easily scrutinised. There is deep regulatory discomfort with AI CEOs. That reflects a wider trust issue among the wider workforce too, with uptake held back because employees do not fully trust AI to carry out work reliably,” said Margerison. He added that AI systems “need to explain their actions and decisions in clear, logical terms” and must be built to keep humans in the loop while confidence develops.
Margerison also warned against relying solely on in-house development teams to build leadership-grade AI systems. In his view, that approach risks slower deployment, stalled projects, and weaker competitiveness, particularly in non-technology sectors. He said more businesses are likely to seek capability through acquisition or exclusive licensing, and suggested that could lift AI-related M&A activity in the second half of 2026. The forecast remains one executive’s view, but it adds to a wider debate about how much of the C-suite’s operational load can realistically be automated.
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