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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.
Washington DC |
Published in
AI
and
Board
| 15 minute read |
This sixth article in my AI Centre of Excellence (AI CoE) series transforms theory into practice with a comprehensive 90-day implementation roadmap. Moving from capability building to value delivery, it introduces the AI Initiative Rubric - a systematic pilot selection tool that ensures your first initiatives deliver Well-Advised value whilst strengthening Five Pillars capabilities. Complete with sprint portfolios, stakeholder engagement strategies, and common pitfall avoidance, this article provides the practical guidance needed to demonstrate tangible AI CoE value from day one.
Washington DC |
Published in
AI
and
Board
| 14 minute read |
The fifth article in my AI Centre of Excellence series provides a comprehensive guide to building essential capabilities across the Five Pillars. Moving from governance frameworks to practical implementation, it details how to develop capabilities that match your multi-speed AI reality - from transforming shadow AI into governed innovation, to creating comprehensive literacy programmes. Complete with a 90-day implementation sprint, maturity assessment tools, and practical templates, this article transforms theoretical understanding into actionable capability development.
Llantwit Major |
Published in
AI
and
Board
| 12 minute read |
In the first three articles of this series, we’ve established why Boards need an AI Centre of Excellence (AI CoE), explored the eighteen essential functions that drive AI success, and used the AI CoE Simulator to reveal the multi-speed reality of AI adoption. Now comes the critical question: how do you structure an AI CoE that can effectively govern this complex, multi-speed landscape?
Seattle |
Published in
AI
and
Board
| 11 minute read |
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.
Washington DC |
Published in
AI
and
Board
| 11 minute read |
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.
London |
Published in
AI
and
Board
| 15 minute read |
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.
Limassol |
Published in
AI
and
Board
| 16 minute read |
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.
London |
Published in
AI
and
Board
| 15 minute read |
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.
London |
Published in
AI
and
Board
| 16 minute read |
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?”
Llantwit Major |
Published in
AI
and
Board
| 9 minute read |
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?”
