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Tagged with: #organisational-culture

Posts tagged with #organisational-culture address the human dimensions of technology transformation that often determine success or failure.

AI Centre of Excellence: Building Capabilities That Scale With AI Adoption

Washington DC | Published in AI and Board | 14 minute read |    
A modern corporate training centre where diverse teams work at stations representing the Five Pillars. Digital displays show capability maturity levels progressing from basic to advanced, with interconnected pathways between stations symbolising integrated capability development. The AI CoE team facilitates from a central hub. (Image generated by ChatGPT 4o).

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.


AI Centre of Excellence: Designing Structure for Multi-Speed Governance

Llantwit Major | Published in AI and Board | 12 minute read |    
A modern glass-walled boardroom showing an organisational chart on a large screen. The chart displays a hub-and-spoke AI governance model with a central AI CoE connected to various business units at different stages of AI maturity, represented by different colours and connection strengths. Executives are gathered around the table reviewing the structure. (Image generated by ChatGPT 4o).

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?


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.


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.


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.


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.


The future of AI expertise: Building and managing AI-capable teams

Limassol | Published in AI , Board and Cloud | 7 minute read |    
Futuristic business setting with diverse professionals collaborating in a sleek office, featuring holographic AI systems, data visualizations, and interconnected networks, symbolizing AI's transformative role in modern organizations (Image generated by ChatGPT 4o)

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?


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.


Dawn of the three-hour work week: AI's impact on employment and compensation

Vienna | Published in AI and Board | 10 minute read |    
A futuristic office seamlessly blended with a beach setting. It shows humans relaxing and working alongside AI robots, reflecting a balanced lifestyle where work and leisure coexist harmoniously (Image generated by ChatGPT 4o).

As artificial intelligence (AI) advances into the workplace rapidly, one of the most pressing questions on everyone’s mind is, “If machines can do our jobs faster, more accurately, and at a lower cost, what happens to us?” It’s true that AI is beginning to redefine the very essence of work, raising concerns about the potential displacement of knowledge workers. However, I’d like to propose an alternative perspective—one where those same workers earn the same or more whilst working far fewer hours.