Sue Turner

‘The premise that innovation and ethics must be "balanced" implies they're in tension. In my experience, that's false.’

Part of the AI Leadership Index – a curated list of the most inspirational figures shaping the AI revolution.

I bridge the gap between AI's technical possibilities and its responsible deployment, combining a Law degree, leadership expertise and an MSc in Artificial Intelligence and Data Science to guide organisations through AI transformation with wisdom and integrity. As Founding Director of AI Governance Limited since 2020, I've developed practical frameworks that enable businesses to move from AI paralysis to AI action.

My clients (ranging from Fortune 100 and FTSE listed businesses to small companies and charities) gain the techniques to discover and develop opportunities to benefit from AI whilst building effective governance. I champion responsible AI globally through my role as founder member of the United Nations AI Skills Coalition and as one of the first 14 people globally accredited in Foundations of Independent Audit of AI systems. As Professor in Practice for AI and Technologies at the University of Bristol Business School, I'm collaborating with cutting-edge researchers across the University to develop new programmes at undergraduate, post-graduate and executive education levels.

Awarded an OBE in 2021 for Services to Social Justice, I bring decades of leadership experience across regulated industries to help organisations harness AI's transformative power responsibly.

Please share a case study of how you have you innovated with AI over the last year?

In 2025, I took on a financial services mutual as a client. Mutuals are values-driven, budget-conscious and risk-aware, existing to serve members rather than shareholders. Their Board saw AI as essential to staying competitive but feared costly mistakes such as over-investing, falling behind, or undermining member trust.

I designed a four-part programme:

• AI Literacy Development – Practical sessions for senior leaders and staff demystified AI through relevant industry examples, creating shared understanding.
• AI Use Case Ideation – Using my methodology, I ran workshops to identify real business problems AI could solve, turning abstract ideas into prioritised, high-value initiatives.
• Strategic Provocations – At the Board Strategy Day, I challenged assumptions about risk, helping directors separate genuine threats from perceived barriers.
• Policy and Governance – I reviewed and strengthened their AI policy, embedding my Eight Stages of Good AI Governance and Responsible AI Framework tailored to their regulatory context.

Within months, the Board moved from defensive caution to proactive strategy, allocating budget for AI investment in 2026. Directors now have the confidence and frameworks to evaluate proposals rigorously while enabling innovation.

This work underpins my AI Toolkit for Leaders, which I’m scaling in 2026 to equip leaders to ask better questions, assess AI effectively and build governance that accelerates, rather than restricts, progress.

What is the biggest challenge you have faced with AI innovation and how you have overcome it?

My biggest challenge isn’t creating practical AI opportunity and governance frameworks, It’s getting them to the leaders who need them most. I’ve built tools that move organisations from AI paralysis to action, yet I face two opposing forces.

On one side are leaders chasing quick wins who see responsible AI as bureaucratic drag. In the absence of strong UK and US regulation, many prioritise competitive advantage over governance. When I raise ethics and risk management, I can see they’ve already moved on. They may only recognise the value of governance after regulatory, reputational or discriminatory harm occurs when it’s too late.

On the other side are well-intentioned leaders who understand AI matters but lack the literacy to engage confidently. They struggle to ask the right questions, separate hype from reality and keep pace with change.

I’m addressing this on several fronts: embedding responsible AI into programmes at Bristol University; speaking at major industry platforms (including Salesforce, UKSPA and Quest Software); developing a scalable 2026 programme; and continuing to advocate for stronger UK regulation.

Shifting mindsets at scale before poor AI governance causes lasting harm is an ambitious mission. I haven’t solved it yet—but I’m making meaningful progress.

How do you balance innovation with ethical safeguards?

The premise that innovation and ethics must be "balanced" implies they're in tension. In my experience, that's false. Ethical safeguards don't slow down good AI innovation. They accelerate it by preventing costly mistakes, building stakeholder trust and ensuring solutions work for the people they're meant to serve.

I've seen too many organisations rush AI deployments only to face expensive rollbacks when they discover bias in their algorithms, regulatory breaches or user backlash. The "move fast and break things" mentality breaks trust, damages reputations and ultimately costs more in remediation than building governance upfront.

My approach embeds ethics from the start, not as a compliance checkbox but as a strategic advantage. When clients use my AI Opportunities methodology, we evaluate ethical considerations alongside business impact and technical feasibility. This surfaces potential issues early when they're cheap to fix, not after deployment when they might be catastrophic.

The Eight Stages of Good AI Governance framework explicitly positions Responsible AI as an enabler of innovation. The organisations winning with AI aren't choosing between innovation and ethics. They're recognising that sustainable innovation requires both.

How do you believe the artificial intelligence space will change over the next 12-24 months?

The next 12–24 months represent a critical window between today’s AI capabilities and far more powerful tools on the horizon. The next generation from big tech will bring major advances in autonomy, reasoning and contextual understanding—well beyond current systems.

That makes 2026–2027 a vital preparation period. Organisations that use this time to organise data, map workflows, build AI literacy and establish governance will be ready to harness these capabilities. Those that don’t risk scrambling to catch up—or deploying powerful systems without adequate safeguards.

The shift from content generation to autonomous decision-making changes the risk profile entirely. A chatbot error is embarrassing; an autonomous agent negotiating contracts, approving spend or hiring without oversight raises far higher stakes.

Leaders who recognise this inflection point and build capability and governance in parallel will shape the competitive landscape of the next decade. Those who delay risk lasting disadvantage.