Briefings for owners and leaders on the decisions AI puts on their desk: strategy, governance, the Head of AI role and fractional executives.
Data sovereignty is the principle that data is subject to the laws and control of whoever governs it. For a company using AI, the useful version is narrower and more practical: knowing, and deciding, who can see, keep, use and move the data that goes into your AI systems and the outputs that come out…
AI consulting services are the outside help a company buys to decide, build and run its use of AI: strategy and prioritisation (often sold as AI strategy consulting), readiness and data assessments, implementation and integration, training and change support, governance, and ongoing managed operation. The category is broad enough that two proposals with the same…
AI change management is the work of getting people to change how they do their jobs because of AI, and to keep working that way once the launch energy has gone. It covers four things: a redesigned workflow worth using, clear permission to use it, the skill to use it well, and an honest answer…
Leading an AI transformation is not a technology programme with an executive sponsor attached. It is a change in what the leadership job consists of: deciding faster on less certainty, choosing deliberately what will not be automated, keeping the organisation honest about what the tools are actually doing, and being the person who answers when…
AI-augmented executive leadership is what running a company looks like once AI stops being a tool the IT function evaluates and becomes a set of decisions the top of the organisation has to own: what to build and what to rent, who is accountable when a system decides something, which capability is worth keeping in-house,…
Switching costs are what it takes to move off a vendor: the money, the engineering, the retraining, and the disruption you would absorb to replace one AI system with another. They matter more than almost any other number in an AI contract, because switching costs are the actual mechanism of vendor lock-in. A vendor rarely…
AI governance is the set of standards, controls, and accountability that determine how a company uses AI: which systems are in use, what data they touch, who is responsible for them, how their decisions can be audited, and what rules they must follow. It is the difference between a company that can answer “how was…
Build versus buy is the question every company asks when it gets serious about AI: do we build our own system, or buy an off-the-shelf tool? It is a reasonable question, and taken as a strict either-or, it is the wrong one. Almost no company should build everything, and almost none should buy everything. The…
A Head of AI decides what AI the company builds and buys, kills the parts that do not work, and owns how AI is used across the business. What they do not do, mostly, is build the AI themselves. That single distinction clears up most of the confusion about the role, because the title makes…
A Chief AI Officer (CAIO), or Head of AI, is the senior executive responsible for how a company uses AI across the whole business: the strategy, the portfolio of AI initiatives, the governance, the vendor decisions, and whether any of it actually produces a return. The role exists because AI became consequential enough to need…