Questions leaders actually ask us.

It's a structured programme that builds a working mental model of what AI actually does, what it's reliable for, and where it fails — taught through the decisions leaders already make, not through code or model architecture. The goal is judgment, not technical skill.

Most AI courses are built for practitioners — people who will use AI tools day to day. Cortessian is built for the people who approve, govern, and answer for AI decisions, but won't be building the models themselves. The content, examples, and pace are set for that audience specifically.

Boards, executive committees, functional leaders (legal, HR, finance, risk, operations), founders and CEOs, and non-executive directors — anyone who needs to evaluate or govern AI decisions without becoming an AI specialist themselves.

No. The programme assumes intelligence and business experience, not familiarity with AI terminology. Nobody needs to write code or understand model internals to get full value from it.

Training builds the shared foundation — a working framework anyone can apply. Workshops apply that framework directly to a live decision your team is facing. Consulting is ongoing, direct advisory for higher-stakes situations, such as governance frameworks or major vendor decisions, where a named advisor works with your team over time.

Training programmes typically run as 4 to 6 short sessions over several weeks, or as a single compressed day. Workshops are half a day or a full day. Advisory engagements are scoped individually, from a few weeks to a standing retainer.

Both. Training works well either way. Workshops are strongly recommended in person, since they're built around live discussion and decision-making. Advisory is usually a mix of both.

It depends on format, group size, and scope, so we don't quote a fixed price on the website. A short initial conversation is enough to give you an accurate estimate.

No. Cortessian is a literacy and advisory practice, not an implementation partner. We build your team's ability to evaluate, govern, and decide on AI — the actual building or deployment of systems is intentionally outside our scope.

The specific tools and models discussed are updated for every engagement, but the underlying framework is deliberately built to outlast any one product cycle — it's a way of reasoning about capability, risk, and fit, which holds regardless of which model or vendor is in the news that quarter.