Digital Innovation & Entrepreneurship
E arlier this year, Mrinank Sharma quit his job as an AI safety researcher at Anthropic, claimed that the “world is in peril”, and returned to the UK to study poetry. Apocalyptic warnings like this may dominate the headlines, but, for businesses, the most pressing concern is how to use AI tools to drive quality and efficiency. McKinsey surveyed approximately 2,000 professionals for its report on The State of AI in 2025 . Of those, 88 per cent said their company regularly used AI in at least one business function. However, nearly two thirds said it was not yet being scaled across the business. Adopting AI is not easy. It can offer companies an opportunity to gain competitive advantage, but only if it is done well. When adopted carelessly, the cost can be huge – as it was for Deloitte, whose reports for the Canadian and Australian governments were found to contain AI-fabricated citations. With that in mind, researchers at Warwick Business School (WBS) have identified five common traps to avoid when using AI in the workplace. 1 . Over-automation. A common safeguard for companies using AI is a commitment to ‘keep humans in the loop’. But how effective is that approach? It depends on how those workers interact with AI – and that varies considerably. WBS researchers found that consultants who used ChatGPT for a complex problem-solving task tended to fall into one of three distinct groups. Sixty per cent behaved as ‘cyborgs’, using AI for each sub-task
in a highly integrated manner. They assigned personas to the AI, interrogated its outputs, exposed contradictions, and validated results. This taught them new skills and helped them to extract maximum value from the collaborative process. Yet they did not produce the best results. Those came from a second group that behaved as ‘centaurs’. This accounted for only 14 per cent of the consultants. They used AI to gather information and refine their own content, but kept themselves firmly in the driver’s seat, using AI as a tool rather than a partner. They did not develop significant AI-related skills, but strengthened their expertise as consultants, while their results were more accurate and just as compelling as those produced by the cyborgs. “Executives need to abandon the notion that simply having a ‘human in the loop’ is sufficient” The final group delegated large tasks to AI and accepted the results with few or no changes. Their work was fast and polished but lacked depth and was less likely to be accurate. They also developed fewer skills than their colleagues. The researchers called them ‘self-automaters’. Hila Lifshitz, Professor of Management and Head of the AI Innovation Network at WBS, said: “The fact that a quarter of highly educated, hard-working, and motivated consultants
wbs.ac.uk | Warwick Business School
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