People-first strategies for AI adoption in financial services

To move beyond technical implementation and realise real impact, financial services firms must put people, culture, and workforce transformation at the centre, with HR leading the shift toward a truly AI‑enabled organisation.

The rise of the intelligent enterprise is rewriting the world of work. But although AI continues to dominate the headlines, many organisations are struggling to realise its full value, with 95 percent of initiatives falling short of their goals.

In financial services specifically, our latest roundtable event with financial services leaders indicated that accelerating AI adoption within regulatory environments and an AI skills shortage were two of the most recurring challenges.

To address AI value shortcomings, many organisations are still looking at AI adoption through a technical lens. However, putting people and culture at the heart of transformation is the secret to successful adoption. People Teams have a unique and growing role to play in leading AI transformation, and in this article, we talk about how they can move forward at pace – both across the enterprise and within their own function.

HR’s leading role in enabling AI across the enterprise

As humans and AI technologies collide, financial services organisations need to rethink their end-to-end operating model. The People Function has a critical role to play in readying organisations for scaled AI adoption across operating models through redesigning roles, rethinking people policies, and creating a robust, ethical culture.

To enable the rapid adoption of AI across the enterprise, People Teams in financial services should consider the following steps:

• Redesign organisational structures for the digital age: No longer limited by rigid jobs, today’s talent ecosystem is based on flexibility. To support financial services organisations to scale AI across the different business functions, HR must lead bold organisational redesign, moving from traditional static hierarchies to dynamic, skills-based networks; and from human teams to human-agent teams. This means creating flatter structures, distributing decision-making authority closer to the work, and designing teams that promote cross-functional collaboration. Bringing together the right skills to solve operational challenges will create a flexible, AI-ready workforce.
• Prioritise skills, not jobs: Our research indicates that just over half (57 percent) of financial services firms are actively implementing or piloting continuous skills-based workforce planning. As traditional strategies of buying talent in from the external marketplace are looking less viable, a skills-based approach enables organisations to shift the focus to investing in the existing workforce. The role of People Teams is to facilitate a cycle where AI skills are continuously identified, assessed, and developed, as well as implementing talent strategies for in-demand skills.
• Create adaptive career paths: AI and automation are reshaping traditional financial services organisational entry points. Career paths built on linear progression, fixed roles, and deep specialisms are increasingly misaligned with the realities of modern work. As financial services organisations become more dynamic and fluid, People Teams need to remove barriers to mobility, replacing the notion of a single, predetermined ladder with a network of flexible pathways.
• Build strong ethical foundations: Navigating the evolving landscape of AI demands a proactive commitment to AI accountability and trust. As organisations embrace intelligent technologies, embedding core values into the fabric of AI design and decision-making to enhance trust is essential. People Teams need to establish clear frameworks for fairness, transparency, reliability, and accuracy (FTRA), and convene with cross-functional ethics boards to govern decision-making.

How HR can accelerate AI adoption across the function

Research suggests that around 60 percent of HR functions are already adopting AI in some form. But progress is often slowed by the realities of poor people data, unintegrated people systems, and outdated HR skillsets – challenges not limited to financial services. To drive from the front with confidence and impact, People Teams should:

• Evolve the HR skills profile: While the foundations of traditional HR expertise remain essential, the emergence of digital skills is rapidly redefining what it means to be an HR professional. The demand is evidenced by the 66 percent year-on-year increase for AI skills. People Teams must accelerate their learning journey, embracing new capabilities that empower them to shape the AI agenda.
• Craft a human-first AI strategy: While AI may soon be everywhere, culture remains irreplaceable. The organisations that will thrive are those that design AI-enabled strategies with purpose, anchored in their unique context, and guided by principles that put people first. People functions need to be deliberate in the development of their AI strategy, identifying guiding principles and recognising that not every process should be automated, just because it can.
• Level up data strategy: The promise of AI is only as powerful as the data that fuels it. In a world where insight is currency, the integrity, accuracy, and ethical stewardship of information is more important than ever. For People Teams, this means investing not only in smarter systems, but a relentless commitment to quality and transparency of people data – as we did with Rabobank. By championing these principles, People Teams can ensure that AI delivers meaningful, trustworthy insights.
• Embrace experimentation: The potential of AI appears limitless, but in the early stages of adoption, it can also be ambiguous, particularly for People Teams as they navigate the sensitivities of safeguarding people and their data. Through experimentation in areas including talent acquisition, People Teams can start small, pilot new approaches, and iterate rapidly. This approach not only de-risks change but also empowers teams to build confidence and capability as they go.
• Drive change, not deployment: Unlocking the true value of AI demands more than simply rolling out new tools; effective change management is fundamental to successful adoption. Involving and engaging HR teams through the co-creation of use cases will help ensure AI adoption is seen as a collective responsibility.

Those who see the AI revolution as a technical challenge may find they are quickly left behind. Real value will be achieved by the firms that recognise AI as a whole system change, with critical contributions from HR, including organisation redesign, skills development, and behaviour change.

Now is the time to shift the narrative from the implementation of AI to a people-first agenda.