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Tagged with: #ai-centre-of-excellence

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.

AI Centre of Excellence: Mapping Your Multi-Speed AI Reality

Seattle | Published in AI and Board | 11 minute read |    
A modern boardroom at sunset with four business professionals using digital tablets to assess AI maturity. In front of them, five large digital dashboards represent the pillars of AI maturity—Governance & Accountability, Technical Infrastructure, Operational Excellence, Value Realisation & Lifecycle Management, and People, Culture & Adoption—each visualised with abstract icons and colour-gradient progress bars. (Image generated by ChatGPT 4o).

In the first two articles of this series, I’ve explored why boards need an AI Centre of Excellence (AI CoE) and detailed the eighteen functions that determine AI success. But before you can build effective governance, you need to understand where you actually are today - not where you think you are, or where you’d like to be. To help boards navigate this challenge, I’m sharing the AI CoE Simulator - a practical assessment tool taken from my AI governance toolkit that operationalises the AISA framework for real-world use.


AI Centre of Excellence: The Essential Functions of the Five Pillars

Llantwit Major | Published in AI and Board | 12 minute read |    
A modern control room with 18 illuminated panels arranged in five distinct colour-coded groups, each displaying abstract representations of AI governance functions, with silhouettes of executives observing the unified system (generated by ChatGPT 4o).

Every AI Centre of Excellence (AI CoE) needs a clear operational mandate. Through my experience designing and building Cloud Centres of Excellence for AWS customers, extensive research, and practical implementation, I’ve identified the essential functions that provide comprehensive AI governance without creating bureaucratic overload. These functions, organised around the Five Pillars mechanism, ensure your AI CoE can effectively govern multi-speed adoption while building the capabilities needed for sustainable AI transformation. Understanding these functions, and how they interconnect is crucial for boards establishing effective AI governance.


AI Centre of Excellence: Moving Beyond Shadow AI Risk to Scaled AI Adoption

Washington DC | Published in AI and Board | 11 minute read |    
Sunrise view of a high-rise boardroom overlooking a city skyline, where glowing blue neural-network lines radiate from the conference table across the floor and out the floor-to-ceiling windows, symbolising millions of AI decisions under board oversight (generated by ChatGPT 4o).

Boards face an unprecedented governance challenge as AI systems operate at speeds traditional oversight cannot match. With the vast majority of AI pilots failing to reach production and shadow AI creating unmanaged risks across organisations, establishing an AI Centre of Excellence has become essential board infrastructure. This article explores how an AI CoE provides the governance framework needed to coordinate multi-speed AI adoption, build capabilities systematically across the Five Pillars, and transform ungoverned AI risk into strategic competitive advantage.


A Complete AI Adoption Framework: AISA, Five Pillars, and Well-Advised

London | Published in AI and Board | 15 minute read |    
A sophisticated boardroom with three interconnected holographic displays, each representing a key AI framework: AISA stages, Well-Advised pillars, and Five Pillars capabilities. Diverse executives collaborate around these dynamic visual representations, symbolising the integration of AI adoption strategies and governance approaches (Image generated by ChatGPT 4o).

I’m regularly asked how to use the AI Stages of Adoption, Five Pillars, and Well-Advised together practically. In this article I explain how these three mechanisms integrate to address the unique challenge of AI’s multi-speed adoption across different business functions. I provide a straightforward approach for boards to coordinate AI transformation whilst managing the governance complexities that emerge when different parts of the organisation advance at different speeds.


Rethinking Business Cases in the Age of AI: and Securing Buy-In from the Board

Limassol | Published in AI and Board | 16 minute read |    
A diverse executive team presents an AI business case to a Board in a modern Boardroom. Digital displays show strategic alignment diagrams and multi-horizon value projections, while executives engage with Board members who are reviewing materials. The scene captures the critical moment of stakeholder engagement and decision-making for AI investments. (Image generated by ChatGPT 4o).

Even the most meticulously crafted AI business case can fail at the final hurdle - securing Board buy-in. With research showing 88% of AI pilots never reach production, effective presentation isn’t just about gaining initial approval but establishing the path to full implementation. This final article in my series explores how to present AI investment proposals to Boards, addressing their six key areas of concern while building the stakeholder confidence necessary for successful transformation. By understanding Board dynamics, anticipating objections, and structuring presentations that balance strategic vision with implementation rigour, you can navigate the critical journey from business case to production-scale AI.


Rethinking Business Cases in the Age of AI: Building Your AI Business Case

London | Published in AI and Board | 18 minute read |    
A professional team collaborates around a conference table reviewing an AI business case document. Digital displays show multi-dimensional value metrics, ROI projections across different time horizons, and strategic alignment graphics. The scene conveys analytical rigour combined with strategic vision in building a compelling AI investment case. (Image generated by ChatGPT 4o).

Organisations are demanding disciplined, comprehensive business cases for AI initiatives that balance traditional financial rigour with frameworks capturing AI’s unique value creation patterns. In this fourth article in my series on AI business cases, I provide a step-by-step guide to building AI business cases that secure approval and set the foundation for successful implementation.


Rethinking Business Cases in the Age of AI: Finding High-Value AI Opportunities

Llantwit Major | Published in AI and Board | 15 minute read |    
A diverse executive team in a modern boardroom reviews a large digital screen displaying a network map of interconnected business processes, with glowing nodes highlighting high-value AI opportunity areas. Surrounding dashboards present analytics on process complexity, strategic alignment, and implementation feasibility. Team members are engaged in discussion, each with laptops showing performance data. (Image generated by ChatGPT 4o).

Finding high-value AI opportunities requires looking beyond the obvious. While most organisations gravitate toward trendy applications like chatbots, the most impactful AI initiatives often lie in less visible but more strategically significant processes. By applying a structured evaluation approach that examines process characteristics, strategic alignment, and implementation feasibility, boards can identify AI investments that deliver transformative value across multiple business dimensions. This systematic method ensures scarce resources target opportunities with the greatest potential impact rather than those with merely the highest visibility or short-term appeal.


Rethinking Business Cases in the Age of AI: Creating the Foundation

Seattle | Published in AI and Board | 14 minute read |    
A business team collaborating around a modern table with holographic displays showing five interconnected building blocks that form a complete AI business case evaluation structure. (Image generated by ChatGPT 4o).

Building on my previous thoughts about why traditional business cases fail for AI investments, this article explores what I consider to be the essential building blocks for a more effective evaluation approach. This foundation provides boards with the tools to assess AI’s unique value creation patterns while maintaining financial discipline - helping leaders confidently navigate investment decisions that conventional models simply cannot adequately evaluate.


Rethinking Business Cases in the Age of AI: What Boards Need to Know

London | Published in AI and Board | 11 minute read |    
A group of business professionals in a futuristic Boardroom analyse AI investment data, with glowing holographic charts, ROI metrics, dollar signs, and an upward-trending arrow pointing toward a central “AI” node, symbolising growth and financial impact in the age of artificial intelligence. (Image generated by AI).

In today’s AI-driven landscape, traditional business case methods fall short when evaluating AI investments. Drawing from my experience developing AWS’s cloud business case tools, I explore why conventional ROI models struggle with AI’s parallel, multi-speed adoption patterns. Unlike cloud’s sequential journey, AI initiatives exist simultaneously across different maturity stages, creating valuation challenges that standard metrics can’t capture. Boards need new evaluation approaches that account for AI’s diverse cost structures, varying timelines for returns, and how investments in one area often enable value in entirely different parts of the business.


Implementing Decision Analytics: A Practical Guide for Boards

London | Published in AI and Board | 11 minute read |    
A diverse business team collaboratively building an AI decision analytics engine in a modern boardroom, with digital data displays and construction tools on a sleek conference table. (Image generated by ChatGPT-4o).

In my previous article, Transforming the Board: Using Decision Analytics for Strategic Advantage, I introduced the concept of AI-powered decision analytics as a transformative approach to board decision-making. I explored how these capabilities can help directors move beyond traditional backward-looking metrics to embrace predictive indicators that model potential futures and enhance strategic decision-making.