Martin Neale

‘By focusing on operating models rather than tools, Martin turned the adoption gap into an opportunity’

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Martin Neale

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

Martin Neale is founder and CEO of ICS.AI, the UK's leading AI transformation company for public services. At 55, he cashed in his pension to launch ICS.AI, a bold personal commitment that has transformed how councils, universities, and public bodies deploy AI at scale with guaranteed outcomes.

Over 35 years, Martin has brought 22 innovations to market, but ICS.AI represents his most impactful work: proving AI can deliver both improved citizen services and financial sustainability. Under his leadership, ICS.AI now powers 57% of UK council AI engagement, processing millions of resident interactions annually, while maintaining the highest standards of governance and ethics.

His approach challenges the industry norm of perpetual pilots. Instead, Martin pioneered the AI Target Operating Model embedding AI into governance, processes, and service design from day one. This methodology has delivered £12 million in savings for Derby City Council alone, while halving customer waiting times and achieving 56% call deflection.

Martin's leadership has earned recognition including Public Sector Entrepreneur of the Year (2025 Enterprise Awards), Socitm Partner Collaboration Award, and parliamentary acknowledgment. Most significantly, he's established a national blueprint proving AI can be deployed responsibly, at scale, with measurable impact.

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

Martin led ICS.AI’s partnership with Derby City Council to deliver the UK’s first unified AI operating model, transforming it into the country’s first AI-native council. This was not a series of pilots, but a whole-system redesign.

Derby faced rising demand, tight budgets and around 100 vacant roles, alongside fragmented digital initiatives. Incremental change was no longer enough; measurable impact was essential.

Through a structured AI Transformation Programme, Martin oversaw the simultaneous rollout of three elements: 24/7 resident access via phone and web, AI-augmented tools for staff across departments, and autonomous back-office agents. AI was embedded into daily operations rather than layered on top.

Impact included:

Derby’s AI assistant, Darcie, illustrates responsible design. It triages enquiries intelligently, identifying vulnerability or distress and routing those cases directly to human colleagues, while resolving routine matters independently.

As Andy Brammall, Director of Digital & Physical Infrastructure, noted: Darcie manages what it can effectively, and brings people in where it matters most.

Derby’s programme is now informing wider adoption across UK local government, demonstrating that AI can strengthen both financial resilience and citizen experience, and marking a shift from experimentation to operational delivery.

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

The greatest obstacle has not been technical capability, but adoption. While 88% of organisations say they are using AI, only 5% achieve measurable impact. Martin recognised this gap as the central barrier to meaningful transformation in public services.

Too many organisations remain stuck in “perpetual pilot mode” — running promising trials that never scale. Fragmented tools, weak governance, limited capacity and unclear value prevent progress. Leaders see the opportunity, but often lack a clear framework for safe, sustainable deployment.

An additional challenge was inclusivity. If AI systems fail to recognise different accents and dialects, they risk excluding communities and undermining trust. To address this, Martin partnered with the University of Sheffield to examine how conversational AI performs in real service interactions, developing practical frameworks to strengthen fairness, reliability and transparency.

Martin’s response was to design an AI Target Operating Model — a transformation blueprint rather than a collection of tools. At Derby, this included:

Derby shifted from isolated pilots to unified AI operations within months. The experience showed that governance, design and integration — not technology alone — determine whether innovation scales.

By focusing on operating models rather than tools, Martin turned the adoption gap into an opportunity, creating an approach now being replicated across UK public services.

How do you balance innovation with ethical safeguards?

In public services, innovation without trust delivers little value. Martin’s approach builds safeguards into the operating model from the start, not as barriers but as foundations for scale.

Built-in governance: ICS.AI deployments include clear guardrails, compliance frameworks, oversight and defined escalation routes. At Derby, Darcie resolves routine enquiries automatically while immediately directing vulnerable or distressed residents to human staff. Ethical design strengthens capability rather than limiting it.

Transparency and accountability: Martin has established AI Compliance and Ethics Boards within client organisations to ensure human oversight, data protection and responsible use. In public services, explainability and clear accountability are operational essentials.

Evidence-based inclusivity: Through collaboration with the University of Sheffield, AI systems are tested against diverse accents and dialects to ensure equitable performance. This research-led approach reduces exclusion and reinforces public confidence.

The result is a powerful paradox: strong governance accelerates innovation. By creating confidence in safe, reliable deployment, safeguards become the enabler of transformation. Martin’s work demonstrates that responsible AI is not a trade-off between ethics and progress, but that sustainable innovation depends on both.

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

The next 12–24 months will be defined by a move from experimentation to operational delivery. Organisations have embraced AI in principle; now they must hardwire it into live services.

Reliability at scale: AI performance will steadily improve, with more tasks completed accurately first time. Agentic systems will take on proactive, low-supervision roles, making AI dependable in fast-paced, real-world settings.

Physical AI convergence: Martin is expanding ICS.AI into wearables, smart glasses and assistive robotics for frontline use. The aim is augmentation, not autonomy - equipping staff with real-time guidance while keeping human oversight central.

The integration imperative: Success will be measured by how well AI is embedded into workflows and governance, not by technical novelty. Proven operating models will replace isolated pilots, narrowing the gap between trial and scale.

Martin’s view is simple: AI should amplify human judgement, not replace it. Organisations that integrate it into core processes will see measurable results; those that remain in pilot mode will lag behind. Integration and impact, not experimentation, will define AI leadership.