Topics

The whole field, and the reason most of the other topics on this page exist. Luis’ interest is narrow and practical: what changes for an organisation once this technology is genuinely available to it.

Systems that take actions rather than produce answers. The interesting question is not capability — it is accountability, and what an organisation is willing to let a system do unsupervised.

Ethics, compliance, data protection and the EU AI Act, turned into something a business can operate. Governance that exists only as a document is not governance.

The gap between a working pilot and something a large organisation actually depends on. Most AI programmes die in this gap.

The ability to judge what an AI system is doing well and where it is wrong. Distributed across an organisation, this matters more than any single tool decision.

Data strategy, business intelligence and governance — framed as a leadership responsibility rather than a technical function.

Changing how an organisation works, not adding technology to how it already works. The distinction decides the outcome.

Strategy, operating model and the uncomfortable structural questions that technology programmes are often used to avoid.

Developing leaders who can hold a defensible position on AI rather than delegating the judgement to whoever built the demonstration.

What automation and augmentation do to roles, skills and the shape of an organisation — and what leaders owe people during that change.

Creating the conditions in which good ideas survive contact with the organisation. Usually an incentives problem, not a creativity one.