Navigate the sovereignty trilemma where organisations must choose between trust, speed, and control as incompatible AI ecosystems emerge across Europe, America, and China. These articles explore how energy constraints, data localisation requirements, and regulatory divergence force Boards to make explicit choices about where and how they compete. Learn frameworks for managing data centre diplomacy, understanding the strategic implications of infrastructure dependencies, and turning sovereignty alignment into competitive advantage rather than compliance burden.
AI governance is fragmenting into incompatible systems — Europe prioritising trust through transparency, America pursuing speed through scale, China maintaining control through integration — forcing Boards to choose rather than compromise. In this article, I explore the sovereignty trilemma and present three strategic stances for navigating these landscapes without fracturing your strategy.
I'm a Chartered Director and Fellow of the Institute of Directors (IoD) with three decades bridging software engineering, entrepreneurial leadership, and enterprise transformation. As Head of Applied AI & Emerging Technology Strategy at Amazon Web Services (AWS), I lead how AWS enables its global field organisation and clients to accelerate AI adoption and navigate continuous technological disruption.
An alumnus of the London School of Economics and guest lecturer on the LSE Data Science & AI for Executives programme, I partner with Boards and executive teams to develop the strategic fluency and governance disciplines needed to scale advanced technologies responsibly.
My frameworks — the AI Stages of Adoption (AISA), Five Pillars of AI Capability, and Well-Advised — are adopted internationally in enterprise engagements and cited by professional bodies including the IoD.
This work has enabled organisations to move AI from experimentation to enterprise-scale impact, shaping responsible adoption practice across multiple sectors and geographies.
"Boom" reframes financial bubbles as engines of breakthrough innovation - a pattern visible today in AI's investment surge and likely next in quantum, challenging conventional Board wisdom on speculation, risk, and transformative progress." See what else I've been reading.