How to hire for AI governance

Author Tom Woods
August 20, 2025

The EU AI Act may not be GDPR but the hiring pressure already feels familiar. As artificial intelligence (AI) adoption accelerates and regulatory frameworks take shape, organisations are starting to recognise that AI governance is not just a technical challenge, it is a leadership one.

Legal, privacy, risk and compliance teams are being asked to step in, scope roles and source the right people. For many, this starts with hiring data protection professionals and expanding the remit to include AI-specific risks and governance. The question is no longer if you need AI governance capabilities, but how to hire for them.

Here are five things to consider when building your AI governance capability.

What skills should you look for when hiring for AI governance?

There is no single skillset that defines AI governance. What matters most is how the hire complements the skills of your existing team. For example:

  • Do you already have strong privacy by design and technical input? In this case, a legal or policy specialist may bring better balance
  • Are you currently approaching this through a legal or risk lens? A candidate who understands assurance frameworks and can collaborate with engineering teams might be a better fit
  • Do you need operational traction? If so, prioritise candidates with experience delivering policy implementation, model assurance or control frameworks—not just theoretical fluency

AI governance is cross-functional by nature. Hiring should be, too.

What experience can you expect from AI governance professionals?

Very few candidates have more than two to four years of direct AI governance experience, and that is to be expected. Instead of focusing on job titles or formal certifications, look for practical evidence of how they have contributed to AI governance frameworks in real world environments.

Strong candidates may have:

  • Contributed to or implemented internal AI risk, compliance or policy frameworks
  • Worked on large language model (LLM) governance, helping assess and document appropriate use of generative AI tools
  • Supported model assurance efforts, including transparency, fairness and bias mitigation
  • Been involved in ethical AI initiatives, cross functional working groups or regulatory response planning
  • Worked closely with product, engineering or data teams to operationalise policy and embed privacy by design

What we prioritise in candidate profiles depends on the business’s goals, but we often look for those who can bridge legal, operational and technical perspectives. Candidates who have experience translating abstract governance principles into workable processes or controls, particularly across risk, privacy or regulatory teams, tend to stand out.

To better understand what level experience or background you need to hire, see How to make your first data protection hire.

How to attract AI governance talent in a competitive market

Candidates with experience at Big Tech firms (such as Google, Meta, OpenAI) are in high demand and often command premium salaries. If your budget for a leadership role is under market value, you may need to think creatively.

  • Sponsorship: Especially for UK roles, visa sponsorship can differentiate you and open up access to global talent
  • Flexibility: Offering hybrid or remote models can expand your reach and appeal
  • Adjacent profiles: Professionals from privacy, risk, data governance or regulatory backgrounds often bring valuable and transferable experience

For guidance on salary benchmarking, see our UK data protection salary guide.

What the EU AI Act means for hiring governance professionals

During the GDPR rollout, organisations faced a surge in demand for privacy expertise, often without internal clarity on what they actually needed.

The AI governance space is developing along similar lines: high expectations, low supply and unclear ownership.

Acting early, aligning stakeholders and properly scoping roles now will save time, money and pressure later. Even if hiring timelines are flexible, your thinking should not be.

How to define and scope your AI governance role before hiring

Uncertainty around seniority, remit or reporting lines is normal at this stage. Before launching a search, start with three questions:

  • Who currently owns responsibility for AI within legal, privacy, risk or technology teams?
  • What touchpoints already exist between your business and AI systems?
  • Do you need policy, assurance or control capabilities, or all three?

You should also consider where this hire sits structurally. Will they be embedded in a function such as privacy, compliance or risk? Will they work across multiple teams? Should they have dotted line accountability to product or engineering?

A clear view of ownership and structure will sharpen the brief, improve the quality of the shortlist and increase the likelihood of a successful hire.

For more on designing the right structure, see how to build your data protection team.

Mistakes to avoid when hiring for AI governance

Hiring based solely on brand is a frequent pitfall. While experience at a well-known tech company might sound impressive, it is not always a proxy for impact or fit.

Another risk is over indexing on either legal or technical expertise. Because AI governance is inherently cross-functional, your hire must be able to engage with compliance, engineering, product and senior stakeholders alike.

Waiting too long to act can also leave your organisation exposed, especially if you are already deploying AI tools or using large language models in production.

Finally, skipping internal alignment is one of the most common missteps. Without clear ownership or agreed expectations, hiring often becomes reactive and misaligned. Scoping your needs early makes the entire process smoother and more successful.

What good AI governance hiring looks like – and how we can help

Building AI governance capability is a long-term investment. The right hire will not just help you meet today’s regulatory requirements; they will shape how your organisation approaches innovation, accountability and ethical risk over time.

Whether you are shaping a brief, testing the market or trying to define what good looks like, we are here to support you. Reach out to our specialist team in privacy, risk and compliance hiring.

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