What AI coaching for a senior leader looks like, hour by hour

Two different things travel under the name AI coaching. One builds your view on AI adoption so you can hold a room, a board, a policy discussion. The other sits with you on your own documents until one piece of your weekly work runs differently. I do the second one, one to one, and this is what the hours in it actually contain.

What is executive AI coaching in India?

At the senior level it splits into coaching about AI and coaching on your own work. The first kind is strategy fluency: what the technology does, where it lands in an industry, what a leadership team should fund next. Institutional programs run this well, in cohorts, against a curriculum, and a functional head who needs a defensible view on AI leaves with one.

The second kind starts from the file open on your laptop. The hour goes on your sales deck, your distributor data, your launch note. That shape cannot be run in a cohort. A cohort cannot hand the whole hour to one participant's own documents. A curriculum written in advance cannot know which problem reached you this week.

Here is the difference in one task. A marketing head preparing an entry into a new export market can learn, in a classroom, that AI is useful for market research. Or the hour can be spent turning research you have already verified into the launch brief and the competitor table for that market. You decide which claim in it survives a check. The first leaves you with a position on AI. The second leaves you with the brief.

What happens in the 90 minutes of a session?

The session is spent building one thing on your material, live, and you are the one typing. Module 1 of A.D.A.P.T. AI Coaching, called AI Essentials, is five sessions of 90 minutes, four to eight days apart, about a month end to end. Sessions run on Zoom. A ChatGPT Plus subscription is the prerequisite.

The basics are not covered in the session. Pre-session videos sit gated on your own login for that. So the 90 minutes go on work you brought: a document that is too long, a data pull that takes your team two days, a note you rewrite every quarter. The output comes back and you read it against what you already know about your market. The vague and wrong parts get found in the room, not three weeks later in front of a customer.

Each session ends with one thing that exists afterwards. Session 1 ends with a working setup and your first business problem picked. Session 2 ends with a reusable set of instructions for your own recurring work. Session 3 ends with ChatGPT running on your real documents and data. Session 4 ends with a research brief on your own market. Session 5 ends with a custom assistant handling one repeatable task.

Between sessions there is homework on live work, and I review it before the next session. The gap of four to eight days is deliberate. It is long enough for the new thing to meet real work and break, and short enough that you still remember how it was built. Written notes follow every session. Live recordings are never shared.

What a senior leader is holding at the end

After the month you hold five things you can run without me. The setup. The reusable instructions. ChatGPT working on your own documents. A research brief on your market. One assistant doing a repeatable task. That is the test to apply. If those five would not change a week of your work, the calendar time is not worth it.

Module 2, Inside Claude, is three sessions of 120 minutes, open to Module 1 graduates only. It goes further into tooling: a Claude Project built for your role, connected tools with a working data-to-deck workflow, and one automation running on your real work. An automation at this level looks ordinary. A report you already receive on a fixed day, arriving instead as ranked insights, the open questions and the next actions. You still decide what to act on. The ranking is just the queue.

One more fact about the format, because it changes what the hour can be. Every session is delivered by me, and I take four clients a month. The site describes the people who arrive this way: "Done with courses, ready to implement." A senior leader with an IT policy upstream and juniors already using AI downstream has usually seen enough course material. One tool, used on this quarter's real work, with the judgment to catch a wrong output, covers the gap.

What else do senior leaders ask before starting?

Which AI program is best for a senior executive?

It depends on which problem you have, and the program page usually tells you which kind it is. Look for what you leave holding. A page that lists modules and a final project is teaching the category. A page that names what gets built on your own material is teaching the work.

Can I do this without putting company data into a tool?

Yes, because you choose the material each session runs on. Plenty of senior work is not customer or employee data: market research, competitor reading, your own drafts, published filings, your slide decks. Start there, learn where outputs go wrong, and take the data question to whoever owns policy with a working view of your own.

Do I need any technical background for this?

None. I cannot code and never have, so nothing in the five sessions assumes you can. The prerequisite is a ChatGPT Plus subscription and a real piece of work to bring. Typing is not the skill being built here. Spotting a wrong output in front of you is what you practice.