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Tagged with: #ai-implementation

Posts tagged with #ai-implementation demonstrate how to move beyond pilots to strategic deployment with frameworks that balance innovation speed with responsible oversight.

Implementing Decision Analytics: A Practical Guide for Boards

London | Published in AI , Board and Data | 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.


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 | 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.