Liza Tullidge, CEO and founder of Netā, a training consultancy for non-executive directors, answers PA Future‘s questions on the use of artificial intelligence (AI) from a governance perspective and helping executive teams adapt to an evolving business environment.
How is AI being used internally at businesses in terms of governance?
AI isn’t a governance solution – it’s a tool that must be actively governed itself. While AI can enhance governance by surfacing insights and improving visibility, it doesn’t replace judgment, oversight, or accountability. One of the biggest risks I see is businesses treating AI as an infallible source of truth rather than recognising it as a tool that still requires human interpretation and strategic application. It’s important to see AI as a partner to the board, amplifying capabilities and improving functionality.
What’s already setting companies apart is how they are balancing AI adoption, with intention. The companies that are using AI most effectively in governance aren’t just chasing efficiency or implementing AI solutions ad hoc, they’re looking at how they can integrate into sustainability, risk, and resilience strategies.
A key consideration for boards is the infrastructure behind AI adoption. While AI is being leveraged to flag risks, optimise operations, improve board reporting, regulatory compliance, and business intelligence, it also introduces new operational and ethical questions, such as:
- Does the AI model increase efficiency without creating additional governance risks?
- Is it auditable and explainable to leadership and regulators?
- Does it align with long-term business priorities rather than short-term cost-cutting?
- How do we address the environmental and social factors that come with increased AI use?
Boards that are asking these questions will be ahead of the curve as AI becomes increasingly embedded in governance practices.
See also: How to harness the power of artificial intelligence for good
How is this making businesses more efficient?
When deployed strategically, AI allows boards and leadership teams to move beyond reactive governance – instead of responding to risks as they emerge. Businesses can anticipate vulnerabilities in areas such as regulatory exposure, financial stress testing, and supply chain disruptions. AI-powered tools can track real-time compliance shifts across multiple jurisdictions, reducing the manual burden on governance teams and allowing businesses to stay ahead of evolving requirements.
But efficiency isn’t just about speed – it’s about clarity and precision. The businesses seeing the greatest gains from AI are those using it to reduce complexity rather than add to it.
However, efficiency cannot come at the expense of accountability. A system that accelerates decision-making without ensuring transparency, auditability, and ethical oversight can create as many risks as it mitigates. The key for businesses is to ensure that AI adoption enhances governance rather than bypasses it.
What do we need to be mindful of? Can AI develop unconscious biases (in recruitment, for example)?
AI doesn’t just inherit bias but it can amplify it if businesses aren’t intentional about how it’s developed and deployed. While bias in AI often gets discussed in HR and recruitment, the bigger issue in governance is how bias shapes risk assessments, compliance decisions, and investment strategies. If AI models are trained on historical corporate data that reflects past blind spots, they can reinforce outdated assumptions rather than challenge them.
For example, if a company’s AI system is programmed to flag high-risk investments or suppliers based on past patterns, it may unintentionally penalise emerging markets, undervalue sustainability-linked investments, or reinforce exclusionary lending practices. Likewise, in governance risk management, AI models trained on historical regulatory actions may miss emerging risks, such as the financial materiality of climate exposure or geopolitical shifts that traditional models wouldn’t have prioritised.
AI can be a powerful governance tool, but only if it’s treated with the same scrutiny as any other strategic investment. The key isn’t avoiding AI – it’s ensuring that businesses actively audit and challenge how their AI systems are making decisions.
What would you say boards need to be aware of to balance ambition and accountability?
AI governance isn’t just about managing risk – it’s about governing value creation. Boards need to ensure that AI adoption supports long-term business priorities, rather than just chasing short-term efficiency or cost-cutting. The challenge is how they integrate it responsibly – balancing ambition, accountability, and real-world impact.
AI presents an incredible opportunity for businesses, but it also introduces hidden risks that boards must actively address – not just in terms of governance and oversight, but in long-term strategic planning and environmental responsibility.
One of the biggest risks I see is boards adopting AI without fully understanding its implications or second and third-order consequences. If AI models are being used in decision-making – whether for financial forecasting, risk profiling, or regulatory compliance – then boards need visibility into how these models work, what assumptions they’re making, and where they might fall short. The worst-case scenario isn’t that AI makes mistakes – it’s that those mistakes go unchallenged because no one knows how to question them properly.
Another overlooked risk is that AI isn’t just a digital solution – it depends on physical infrastructure, from high-energy data centers to resource-intensive computing power. Boards that fail to consider the environmental and operational trade-offs of AI adoption may find themselves facing unexpected costs, regulatory scrutiny, or reputational risks. AI governance isn’t just about what AI can do for a company – it’s also about what AI requires from a company.
From the start, AI should be a board-level discussion, not just a tech implementation – because ultimately, it’s not just about what AI enables, but about whether businesses are using it in a way that enhances good governance.
