- 87% of CEOs stake their job on AI success, but they're facing pressures from all angles
- Around three-quarters face pressure from the board to deliver meaningful ROI
- Impatient workers are using unapproved, risky AI tools
A new Dataiku study has revealed just how much business leaders are betting on AI, with four in five worried their job could be at risk by the end of 2026 if their AI plans fail.
At the same time, more than half (56%) of the 900 global CEOs surveyed admit their competitors have stronger AI strategies, implying there's a growing sense of insecurity and uncertainty over what constitutes a strong AI plan.
"CEOs are staking their jobs on AI, but still questioning its outputs and struggling to control the systems they say they own," CEO Florian Douetteau explained.
Is CEO success determined by AI strategy?
With around three in four US CEOs saying the board is pressuring them to deliver measurable outcomes (72%) and ranking AI as one of their highest priorities (78%) nearly nine in 10 (87%) now stake their job on AI success.
However, while the data suggests that investment in AI continues to grow, trust is not so high. Half of critical business decisions still require human approval, and as many as four-fifths continue to question AI's output. AI agent confidence is also heading in the wrong direction, down to 31% in 2026 compared with 41% in 2025.
Regulatory uncertainty also plays a bigger role this year (51% compared with 37%), and many are worried that poor explainability could trigger trust issues among customers.
Dataiku's report also serves to illustrate where some of the challenges are going forward, and it's clear that endless choice maybe isn't as good as it seems. Two in three (65%) worry about over-investing in the wrong AI platforms rather than under-investing.
Looking ahead, CEOs are set to come under more pressure as the risks around shadow AI rise. Nearly all (96%) believe employees are using unapproved GenAI tools, potentially putting sensitive company information at risk. The answer is a fine balance between investing in the right tools to deliver a strong ROI, and investing in the right tools to meet workers where they are and stamp out shadow AI.
