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Tagged with: #ai-transformation

Posts tagged with #ai-transformation guide you beyond using AI as just a tool to fundamentally rethinking how your business operates, competes, and creates value.

AI Centre of Excellence: Future-proofing Through Continuous Evolution

London | Published in AI and Board | 12 minute read |    
A futuristic AI control centre at sunset where interconnected data networks visualise the evolution from pilot projects to enterprise-scale transformation. Expanding luminous nodes and holographic displays illustrate emerging technologies such as multi-agent systems, quantum-AI hybrids, and federated networks, symbolising adaptive governance and continuous evolution within the AI Centre of Excellence. (Image generated by ChatGPT 4o).

You’ve built your AI Centre of Excellence. It’s governing multi-speed adoption, delivering value, and - as we explored in the previous article - scaling beyond pilots to enterprise transformation. But here’s the uncomfortable truth: the AI landscape will look radically different in eighteen months. Multi-agent systems, decentralised agent ecosystems, embodied AI, neurosymbolic reasoning, quantum-AI hybrids, cross-modal intelligence, federated AI networks, and artificial superintelligence will challenge every governance framework you’ve carefully constructed. Having achieved scale, this final article tackles the strategic imperative of continuous evolution: how to future-proof your AI CoE to govern these disruptive technologies whilst building the adaptive capacity to thrive on change rather than being disrupted by it.


AI Centre of Excellence: Scaling Beyond Pilots to Enterprise Transformation

Llantwit Major | Published in AI and Board | 12 minute read |    
An expansive control centre where AI initiatives scale from single monitors to vast digital landscapes. Teams work on interconnected platforms whilst governance frameworks adapt dynamically. The transition from pilot projects to enterprise transformation is visualised through expanding networks of light. (Image generated by ChatGPT 4o).

The successful completion of your AI Centre of Excellence’s first 90 days marks an important milestone, but it also brings into sharp focus the next critical challenge. Whilst the AI Initiative Rubric has proven effective for pilot selection and early wins have demonstrated value, the transition from isolated successes to enterprise-wide transformation requires fundamentally different approaches. This progression from pilot to scale represents one of the most significant hurdles in AI adoption, demanding new structures, governance models, and ways of thinking that go well beyond what initial success required.


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.


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.


Transforming the Board: Using Decision Analytics for Strategic Advantage

Seattle | Published in AI and Board | 13 minute read |    
A contemporary boardroom scene with executives thoughtfully engaging with futuristic holographic visuals above a polished table, displaying graphical analytics and predictive indicators, symbolising the strategic shift toward decision analytics and AI-driven insights. (Image generated by ChatGPT-4o).

In my article The Board in the machine, I argued that “Boards will find that there are no barriers to making the right decisions at the speed of light”. More recently, in AI is transforming governance: Six key Boardroom priorities, I observed that boards “are moving from overseeing hundreds of decisions made per day to millions made per second”. This acceleration of business decision velocity presents both an unprecedented challenge and opportunity for Directors and the Boards they serve.