AI in Practice: Three Fundamentals for Board Leaders

The event brought together Chairs from across sectors to strengthen their peer network and explore the evolving role of AI in board leadership.

AI is now on every board agenda, but the level of understanding and confidence to engage still varies widely. Chairs are being asked to guide their organisations through unfamiliar territory. The challenge isn’t simply about adopting new technology; it’s about leading through relentless change, where the signals aren’t always clear.

At Vaul Labs, we work with boards, investors, and founders to align business strategy with real execution. For us, AI is part of a broader capability-building journey, one that connects strategic clarity, delivery, cultural adoption and governance.

In his talk, AI in Practice: What Boards Need to Know, Brian outlined three fundamentals we see driving success across scaling organisations.

1. Align Data & AI to Business Strategy

Any energy and resources focused on data and AI must be aligned to business strategy. Without that alignment, initiatives risk becoming fragmented, wasting time and money. The most effective organisations start by ensuring their product, engineering, and data functions are working toward the same commercial goals. A clear roadmap that links use cases to business outcomes prevents AI from drifting into side projects that don’t deliver real value.

This alignment requires clear executive ownership and accountability.  Boards should ask:

• Which business outcomes are we aiming to impact?
• Who is responsible for creating and delivering the data and AI strategy?

We always recommend a named executive sponsor who maintains momentum, unblocks decisions, and reports progress clearly to the board. With alignment and ownership in place, focus on execution basics:

• Build and maintain high-quality, well-managed data - it’s fundamental to unlocking the value of AI and is often treated as a poor relation in leadership and technology priorities.
• Assess your organisation’s current capabilities and plan for the skills you’ll need in the future. Skills planning isn’t a one-time exercise; it evolves with the strategy.

2. Build an AI-Confident Culture - Starting in the Boardroom

Culture is either one of your biggest enablers, or blockers, of AI success. In most organisations, adoption doesn’t start with the front line. It starts with leadership.

When board members use AI tools themselves - whether to support decision-making, scan markets, or streamline board operations - it sends a powerful message to the whole organisation. It signals that experimentation is encouraged, and learning is part of the job.

For Chairs, the best place to start is often close to home. Identify where the board itself could operate more efficiently:

• Automate minute-taking
• Synthesise key themes from papers
• Track board actions across meetings

These are small, visible changes that set the tone for broader organisational adoption.

We see a clear difference between companies running disconnected pilots vs those taking a more coordinated approach. The latter treat AI as a learning journey: they test a few well-chosen targeted use cases, align stakeholders around the outcomes, and share what they discover. The result is compounding value. Confidence grows. Momentum builds. The organisation becomes more capable over time because it’s learning together, not in silos.

3. Establish Governance That Builds Transparency and Trust

As AI becomes more embedded, oversight becomes more critical. Boards have a responsibility to ensure that it’s used safely, ethically, and transparently.

The broad spectrum of governance spans two layers:

• Guidance on the use of AI tools: Internal policies to reduce the risk of data leakage, exposure to cyber threats, or unintentional disclosure of sensitive business information. Setting clear guardrails for employees is increasingly important as generative AI tools become commonplace in daily workflows.
• AI systems built or adopted by the organisation: Assurance that algorithms used to make decisions about customers or employees are being developed, tested, and monitored responsibly. This includes meeting regulatory requirements, avoiding unintended bias, and having the ability to explain and justify automated decisions.

Effective governance isn’t just about risk mitigation: it’s about building trust. Employees need to feel confident that AI is being used in a way that aligns with company values. Customers, investors, and regulators expect clarity, accountability, and compliance.

We recommend boards appoint a named executive owner for AI and data governance, with the remit to report on usage, raise issues, and ensure the organisation is both compliant and confident in its approach.

The Broader Pressure to Act

Across the companies we support, the pattern is familiar:

• Investors want to see AI driving efficiency and defensible value.
• Customers expect intelligent, personalised, responsive services.
• Competitors are experimenting with new models and moving fast.

These pressures are forcing organisations to accelerate.

One client had decades of data with limited ability to extract value from it. Their customers were beginning to expect insights that went beyond standard reporting. The board recognised that without action, they risked falling behind.

We helped this customer by tackling the foundational challenges first: improving data quality, redesigning capture processes, and building new data models that reflected the true shape of the business.

This wasn’t just a technical exercise: it involved rethinking workflows, aligning teams, and making sure the right data was collected in the right way. That groundwork created the conditions for more advanced capabilities, including new forms of insight generation and automation, using both Machine Learning and Generative AI.

What began as a defensive move to retain a key customer, became a springboard for long-term innovation.

AI Isn’t a Tactic. It’s a Leadership Imperative.

AI isn’t a plug-in. It’s not something you adopt once and move on from.

It’s a capability to be nurtured, embedded, and governed over time. A common theme through these three fundamentals is that boards must ensure there is executive ownership, alignment, and accountability to be able to move beyond the hype and the headlines to unlock its potential.

At Vaul Labs, we’re proud to support investors and leaders on that journey.

If you’re wrestling with similar questions, let’s talk.