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Tagged with: #ai-adoption

Navigate the journey from AI experimentation to enterprise-wide implementation with frameworks that address multi-speed adoption across different business functions. These articles explore how organisations progress through the AI Stages of Adoption, from initial pilots to scaled transformation, while building essential capabilities across governance, infrastructure, and culture. Learn practical approaches for overcoming shadow AI, establishing AI Centres of Excellence, and creating sustainable AI practices that deliver measurable business value.

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: 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.


Upskilling for the AI Era: Building a Future-Ready Workforce

London | Published in AI and Board | 15 minute read |    
A conceptual digital illustration showing a workforce transitioning from traditional learning to AI-driven training — with one side depicting analog tools and classroom settings, and the other featuring holographic interfaces and futuristic technology. (Image generated by AI)

As I discussed in my article on building and managing AI-capable teams, organisations face a critical challenge in acquiring the right talent for AI transformation. This reminds me of the early days of cloud adoption, when I advised enterprises on their migration strategies. Back then, I witnessed the same scramble for scarce talent, which led me to advocate strongly for upskilling existing teams rather than relying solely on external hiring.


From Shadow AI to Strategic Asset: Building Your AI Centre of Excellence

London | Published in AI and Board | 16 minute read |    
The image shows a modern business setting where AI is seamlessly integrated into operations, enhancing productivity while being governed by ethical guidelines. Executives collaborate with a digital assistant, with subtle guardrails symbolizing responsible AI use in a professional and balanced environment. (Image generated by ChatGPT 4o)

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?”


Increasing AI Maturity: Navigating the AI Stages of Adoption with the Five Pillars

Llantwit Major | Published in AI and Board | 9 minute read |    
A futuristic digital painting depicting the increasing maturity of AI. A glowing blue bridge symbolises progress, supported by five distinct pillars representing different stages of AI development. The left side of the image is darker, illustrating early AI with basic automation, while the right side transitions into an advanced AI-powered city, illuminated with intricate blue light networks, symbolising intelligence and connectivity (Image generated by ChatGPT 4o).

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?”


Understanding the AI Stages of Adoption: A framework for business leaders

Llantwit Major | Published in AI and Board | 16 minute read |    
The Artificial Intelligence Stages of Adoption (AISA).

In June of 2024, I introduced the concept of the AI Stages of Adoption (AISA), a framework for understanding where organisations are in their AI journey. Since then, I’ve had countless conversations with business leaders about how this framework helps them navigate their transformation. Today, I want to share a deeper perspective on AISA and how you can use it to accelerate your organisation’s AI adoption.


Europe's AI challenge: Why culture trumps capital in technology adoption

San Francisco | Published in AI and Board | 7 minute read |    
A dystopian image showing the essence of cultural challenges in AI adoption within Europe, blending innovation and resistance visually (Image generated by ChatGPT 4o).

While here in San Francisco for a business trip, I got the opportunity to spend time with technology innovators and leaders, and what struck me was the contrast in AI adoption approaches, and openness to transformation using AI compared to my experiences in Europe. A new benchmark report from Gallup has confirmed what many of us in technology leadership have long suspected: Europe’s lag in AI adoption isn’t a matter of insufficient capital – it’s a cultural challenge that runs deep.


Introducing the AI Stages of Adoption: A framework for understanding AI readiness in your business

London | Published in AI , Board and Data | 15 minute read |     

Earlier this week, I got the opportunity to speak at our Amazon Web Services (AWS) office in London, to an audience of Private Equity firms and their portfolio company executives about driving value creation through AI and data. The presentation focused on how Private Equity firms and their portfolio companies can drive value creation through AI and data. I also took the opportunity to introduce a new concept called the AI Stages of Adoption (AISA), which is designed to help organisations assess their maturity and readiness for AI adoption.