Establish effective AI governance through board-level Centres of Excellence that balance innovation with responsible oversight. These articles explain why AI CoEs must report directly to boards rather than IT, how to structure teams that span technical and business domains, and practical steps for managing AI initiatives at machine-decision speed. Discover how to transform shadow AI risks into governed innovation while building capabilities across the Five Pillars that enable sustainable AI transformation.
The EU AI Act, which came into force on August 1, 2024, establishes significant penalties for non-compliance, including fines of up to €35 million or 7% of global annual turnover for serious violations. As regulatory frameworks for artificial intelligence rapidly evolve worldwide, Boards face a new imperative: navigating complex compliance requirements while maintaining the innovation speed necessary to compete.
In my previous articles about the AI Stages of Adoption and the Five Pillars of AI maturity and capability, I briefly touched on the role of the AI Centre of Excellence (AI CoE). Since publishing those pieces, I’ve spoken with numerous Boards and business leaders about AI adoption and the importance of board-level AI governance. A recurring question emerges in almost every conversation: “What are the practical steps to establishing an AI CoE in our business?”
In my previous article on the AI Stages of Adoption (AISA), I outlined how organisations progress through their AI journey—from Experimenting to Adopting, Optimising, Transforming, and ultimately Scaling. Since publishing that piece, many readers have asked the same follow‐up question: “How do we know when we’re truly ready to move from one stage to the next?”
The rapid advancement of artificial intelligence is fundamentally changing the velocity of business decision-making and how organisations operate, compete, and create value. With AI, boards are moving from overseeing hundreds of decisions made per day to millions made per second - and they must be confident that each of those decisions is transparent, explainable, and correct.
As organisations adopt artificial intelligence (AI) more widely, a critical challenge emerges: how do you build and manage teams capable of delivering on AI’s promise of increased productivity, enhanced customer experiences, accelerated innovation, and sustainable competitive advantage?
Last week, I had the privilege of delivering a keynote presentation at Monday.com’s Elevate conference in London. The topic, “Leveraging data and artificial intelligence (AI) for organisational transformation,” allowed me to challenge some common misconceptions about AI adoption and share practical insights on harnessing the power of existing data. In this post, I outline the key themes discussed and provide some additional context.