What the government's AI skills compact signals for boardrooms

With AI adoption and workforce capability central to its growth agenda, and Prime Minister Andy Burnham being a long-standing advocate for skills and technical education, the direction of travel is clear. Major financial services firms like Barclays, Nationwide, and the London Stock Exchange are also recognising the importance of skills, putting their names behind the AI Skills Compact.

While the Compact was launched under the previous Chancellor, it reflects a broader and continuing recognition across Government and industry that AI skills and workforce capability are essential to long-term economic growth. The new administration has maintained that direction of travel, reinforcing the importance of investing in the skills needed to adopt AI at scale.

The initiative aims to boost critical skills, including AI capabilities, for more than half a million city workers, enabling them to keep up with the changing demands of their roles and future-proof their careers.

It may be framed as a training initiative, but the Skills Compact’s significance runs deeper than that. It matters because it moves skills from an L&D concern to a strategic board-level priority.

And as AI becomes more embedded in day-to-day work, workforce capability is becoming a business issue, not just a learning one.

The conversation is shifting from “How do we train people?" to "How do we build an organisation that can adapt?”

You can't hire your way to capability

Financial Services firms have already invested in the people who got them to this point. They hold institutional knowledge, customer understanding, regulatory expertise, and operational experience that isn’t cheap or easy to replace.

When work changes, people need pathways to adapt. The challenge now is helping those people succeed as AI changes their work and the way it gets done. That means looking beyond short-term retraining programmes and thinking more broadly about workforce development, career pathways, and capability building at every level of the organisation.

Skills are the foundation. Capability creates value

One of the most important distinctions in the AI conversation is the difference between skills and capability. Skills are the foundation. Capability comes when those skills are embedded into the way people work. Value and impact follow when new skills change decisions, improve processes, strengthen governance, and help teams work differently.

The most successful organisations will treat workforce development as a strategic priority rather than a compliance exercise. That requires leadership attention because capability isn’t created through training alone. It’s shaped by management practices, incentives, workflows, standards, and culture.

AI is exposing gaps as much as it’s changing workflows

AI is exposing weaknesses that were already there. Unclear processes, fragmented ownership, capability gaps, and outdated ways of working become far more visible when organisations try to scale change. That’s why AI transformation is increasingly becoming a capability challenge rather than a technology one.

The value of technology doesn’t come from switching to the next tool. It comes from unlocking new opportunities, rewiring processes with customers in mind, and helping people create value in new ways.

The organisations gaining advantage aren’t those deploying the most AI but the ones building the capability to absorb it.

AI strategy is now workforce strategy

AI is changing the work and the way people do it, but it’s not eliminating the need for talented workers. As a result, organisations need to rethink employee development from early careers through to leadership capability. Future success will depend on how effectively organisations develop judgement, adaptability, technical capability, and leadership capacity across the workforce.

The Skills Compact reinforces a growing recognition that, instead of being an afterthought, workforce capability is essential for business performance.

What financial services firms can do now

1. Maximise the apprenticeship levy to build future-critical skills at scale across AI, data, technology, and leadership.
2. Equip leaders to spearhead AI transformation so they can build confidence, support behavioural change, and help teams adopt new ways of working.
3. Build internal forward deployed engineer capability (software engineers embedded within business teams) so technical and business teams can work together to translate AI opportunities into operational outcomes, instead of relying indefinitely on external support.

The organisations that benefit most from AI over the next decade are unlikely to be those with access to the most technology. They’ll be those that build the capability to turn technology into better decisions, better work, and better outcomes.