AI governance can't wait for regulation. Leaders can't either

While regulation will undoubtedly shape the future of AI, waiting for legislation before taking action is a mistake. Organizations are already using AI across their operations, whether through purpose-built tools or capabilities embedded within the software they use every day. The question now is how to navigate this reality before formal rules catch up.

Too often, AI governance is treated as a future compliance problem rather than a current leadership responsibility. That mindset is understandable. Regulations are still emerging, and standards are still evolving, leaving leaders feeling they lack the technical expertise to make informed decisions. But governance isn't about becoming an AI expert. As it was for other technology, it's about creating accountability, setting direction, and helping people use it safely and effectively.

Governance needs leadership involvement from the start

In my conversations with leaders, one challenge comes up repeatedly. Many still see AI as a technology issue that can be delegated to IT or cyber security teams. It's a familiar approach that has worked before. In the past, when organizations introduced new software, responsibility typically sat with technology departments.

AI is different. It touches every function of the business, from people teams and operations, to legal, procurement, communications, and customer service.

“When leaders aren't actively engaged, uncertainty fills the gap.”

Part of the challenge is that many organizations don't fully understand how much AI they already have. One of the most important steps they can take is to understand their technology estate: what tools are being used, which AI capabilities are already enabled, and where organizational data is being accessed or shared.

Decisions about AI don't just affect systems. They affect people, reputation, revenue, and organizational culture.

That's why leadership involvement is so critical.

When leaders aren't actively engaged, uncertainty fills the gap. Employees begin making their own decisions about which tools to use, what information they can safely share, and where the boundaries lie. Some employees may use personal AI accounts to complete work tasks. Others may experiment with tools that haven't been approved or assessed by the organization.

This "shadow AI" activity often happens with good intentions, but without clear governance it can introduce significant risks around data security, intellectual property, and compliance.

Innovation and governance don't have to be at odds

Organizations also need to recognize that governance is about enabling innovation, not restricting it.

One of the most successful approaches I've seen is when leadership communicates a simple message: we want you to work with AI, but here are the guardrails.

Employees want clarity. They want to know what's acceptable, what's not, and how they can use these tools confidently. Governance should create that confidence. It shouldn't create fear.

Governance starts with accountability

I believe AI governance requires representation from across the organization. Technology teams bring expertise on systems and security. Legal teams help manage risk. But people teams, operational leaders, and executives all have a role to play in shaping how AI is introduced and adopted responsibly.

Regulation will continue to develop. Frameworks such as the EU AI Act provide an important foundation and will help establish greater consistency over time. The Act also reaches beyond the EU: it applies wherever AI is used in the EU, so UK organizations serving EU clients or customers need to comply too.

“The conversation around AI governance often starts with regulation, but it should start with accountability.”

The UK has no AI Act of its own, but existing laws still apply, including UK GDPR, the Data (Use and Access) Act 2025, and the Equality Act 2010, alongside guidance from regulators, such as the Information Commissioner's Office.

For organizations looking for a practical starting point, the international standard ISO/IEC 42001 provides a recognized framework for managing AI responsibly, whichever regulations apply.

But organizations can't afford to wait for regulators to provide every answer. By the time legislation catches up, AI will already be embedded throughout the business.

The conversation around AI governance often starts with regulation, but it should start with accountability. Leaders don't need all the answers, and they don't need to wait for regulators to provide them. What they do need is visibility, clear ownership, and the confidence to make informed decisions about technologies that are already shaping their organizations.

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