NTT Data’s Tom Winstanley: UK & Japan Can Rewrite AI Rules

2026-06-11 · Source: AI Magazine · Field: Technology & Digital — Artificial Intelligence & Machine Learning, Public Policy & Governance, Regulatory Affairs & Government Relations · Depth: Intermediate, medium

Summary

NTT Data's Tom Winstanley, CTO UK & Ireland, asserts that urgent global AI governance must balance innovation with citizen safeguards, proposing the UK and Japan are uniquely positioned to lead a "third path." This approach contrasts with the US's minimal oversight, China's surveillance model, and the EU's strict AI Act. Winstanley highlights the UK-Japan Digital Partnership's shared values, which prioritize human-centered innovation and regulatory pragmatism, using principles and guidance rather than rigid rules. Both nations advocate for controlled sandbox environments to foster safe experimentation and build trust. To achieve leadership, the UK must significantly invest in digital infrastructure, mirroring Japan's US$65bn national plan for AI and semiconductor development and the US$500bn US Stargate project. Deepening collaboration through joint technical standards and public-private partnerships is crucial for demonstrating responsible growth.

Key takeaway

For Directors of AI/ML evaluating global AI governance strategies, recognize the UK-Japan "third path" as a viable model. This approach prioritizes human-centered innovation and regulatory pragmatism, using principles and sandbox environments to foster responsible development without stifling growth. Advocate for similar balanced frameworks within your organization or national context. Explore public-private partnerships to secure necessary infrastructure investment for scaled AI capabilities.

Key insights

Global AI governance requires a "third path" balancing innovation and protection, led by pragmatic, human-centered approaches.

Principles

• Trust is a strategic asset, built via transparency.
• Regulatory pragmatism guides without stifling innovation.
• Human-centered innovation addresses societal challenges.

Method

Regulators can create sandbox environments for safe AI system testing, informing future rules through iterative, evidence-led approaches to balance risk and progress.

In practice

• Implement sector-based AI regulatory frameworks.
• Promote voluntary safety and transparency measures.
• Invest in advanced computing infrastructure.

Topics

• AI Governance
• UK-Japan Digital Partnership
• Regulatory Pragmatism
• Human-Centered AI
• AI Infrastructure Investment
• Sandbox Environments

Best for: Policy Maker, Director of AI/ML, CTO

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Editorial summary, takeaway, and curation by AIssential. Original article published by AI Magazine.