In July, the Government published its AI strategy for insurance. This is an ambitious task: adopting new technology is remarkably difficult. Research from Boston Consulting Group suggests that some 70% of technology projects fail to meet their objectives, and yet only a small proportion of AI investment (3 to 6%, according to analysis of data produced by Deloitte) is directed towards employee training and AI literacy.

Technology alone does not deliver change. People bridge the gap between a technology’s potential and its real-world impact. The Government’s AI strategy recognises this challenge, highlighting the need for a skilled, AI-fluent financial services workforce, with different capabilities for board, specialist and frontline levels. It also prioritises equitable access to reskilling and training across regions and socioeconomic backgrounds.

Meeting this challenge requires the right mindset, built on two foundations. First, organisations must recognise that technology, including AI, is a means to an end. Its value lies in helping individuals and organisations fulfil a purpose, not in adopting AI for its own sake. Second, organisations must prioritise behaviours at least as much as they value technical expertise. Technical knowledge evolves quickly and shortcomings in early technologies are gradually addressed. Poor behaviours, by contrast, can become entrenched, creating lasting barriers to learning, innovation and implementation.

Developing the right behaviours requires more than good intentions. It demands a structured, professional approach. Many sectors have adopted professional frameworks to identify and encourage the behaviours required for success. In financial services, the Chartered Insurance Institute’s Professional Map provides such a framework, setting expectations that evolve as individuals progress into more senior roles. While junior employees may be expected to handle information responsibly when using AI tools, leaders should actively promote transparent data and AI practices that maintain public trust.

Many of the behaviours most relevant to successful AI adoption extend far beyond technical competence. They include customer focus – ensuring technology delivers sustainable value rather than short-term excitement; curiosity – encouraging continuous learning as technologies evolve and new use cases emerge; a drive to deliver – the resourcefulness and determination to take responsibility for an outcome, ensuring its delivery without ever blaming third parties; impact – knowing how to use technology in a way that achieves better customer understanding, and not just delivering more information; integrity – understanding the ethical dimensions of technology, and especially AI, and how to confront poor practice such as social scoring or ‘emotion recognition’ for pricing; insight – not just in how technology works, but in how it interacts with consumer psychology and behaviour; and inclusivity – to understand the impact of technology on all potential customers so that systems are designed to work for all.

For financial services, avoiding the common pitfalls of new technology adoption depends on two key principles: putting purpose before technology and creating a clear framework of behaviours that support implementation. These principles should form the foundation of the Government’s partnership with business on AI. Without them, we risk repeating a familiar pattern in which the promise of transformative technology takes far longer than necessary to become reality.

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