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Tagged with: #ai-governance
Master the complexities of governing AI systems that make millions of decisions per second through frameworks designed for board-level oversight. These articles address the six key priorities boards face - from strategic alignment and ethical responsibility to risk management and stakeholder confidence. Learn how to establish accountability for AI decisions, implement human-in-the-loop processes, and create governance structures that enable innovation while ensuring transparency, compliance, and responsible AI deployment.
Llantwit Major |
Published in
AI
and
Board
| 15 minute read |
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.
Seattle |
Published in
AI
and
Board
| 14 minute read |
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.
London |
Published in
AI
and
Board
| 11 minute read |
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.
London |
Published in
AI
and
Board
| 11 minute read |
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.
Llantwit Major |
Published in
AI
and
Board
| 14 minute read |
The EU AI Act, which came into force on August 1, 2024, establishes significant penalties for non-compliance, including fines of up to €35 million or 7% of global annual turnover for serious violations. As regulatory frameworks for artificial intelligence rapidly evolve worldwide, Boards face a new imperative: navigating complex compliance requirements while maintaining the innovation speed necessary to compete.
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?”
London |
Published in
AI
and
Board
| 10 minute read |
The rapid advancement of artificial intelligence is fundamentally changing the velocity of business decision-making and how organisations operate, compete, and create value. With AI, boards are moving from overseeing hundreds of decisions made per day to millions made per second - and they must be confident that each of those decisions is transparent, explainable, and correct.
Limassol |
Published in
AI
,
Board
and
Cloud
| 7 minute read |
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?
London |
Published in
AI
,
Board
and
Data
| 10 minute read |
Last week, I had the privilege of delivering a keynote presentation at Monday.com’s Elevate conference in London. The topic, “Leveraging data and artificial intelligence (AI) for organisational transformation,” allowed me to challenge some common misconceptions about AI adoption and share practical insights on harnessing the power of existing data. In this post, I outline the key themes discussed and provide some additional context.
