The Power User Gap for professional services
AI training for professional services teams, on their own client work.
In professional services the split shows first in client work: the first draft of a report, the research behind a recommendation, a proposal that has to read as if a partner wrote it. I look at how your teams do that work, find where AI can do it, and teach your people to use it there.
For whoever is responsible for getting non-technical people using AI. Nothing to code.
74 talks and 77 workshops in 35 countries since 2014. Google Developer Expert, Agentic AI Foundation ambassador.
Where the gap shows in professional services.
The Power User Gap for professional services teaches the consultants, advisers, accountants, analysts and support staff in a professional services firm to hand their own client work to ChatGPT, Claude or Gemini, and to check what comes back.
These are the kinds of work I'd look at first. Your team leads and process documents decide which ones we actually start with.
First drafts of client reports from notes
Meeting notes, interview notes and the last report in the same series go in, and a structured first draft comes out for the person who owns it to rewrite and sign off. Most people still start these from a blank page.
Research synthesis
Pulling the points that matter out of a stack of sources, with each claim tied to where it came from, so the reviewer checks the sources instead of redoing the reading.
Proposal and pitch preparation
Turning a brief and the firm's past proposals into a first structure, the questions the client is likely to ask, and a draft in the house style.
Meeting notes to actions
A call transcript or rough notes turned into decisions, owners and the follow-up email, in the format the team already uses.
A read before it goes out
Asking the tool to read a draft the way the client will, and to flag gaps, inconsistencies and claims with nothing behind them, before a senior reviewer sees it.
What the teaching looks like there
First the people attending say how they do this work today, which is the baseline. Then they practise on their own client work with the tool the firm already pays for: what context to give it, how to ask for a draft they can use, and how to check it against the sources before it carries anyone's name. Afterwards the same people say what they now hand to AI and what they still do by hand.
You see what changed, team by team.
The people attending say how they use AI before anything is taught, and what they hand to it after. It works with whatever tools you've already bought. Remote or on-site, so teams in different countries get the same teaching without anyone flying anywhere. No pre-work for attendees.
For when someone asks what the licences bought.
You hear from the people attending how they use AI before anything is taught, and from the same people afterwards what they now hand to AI and where they still don't. That's the before and after, team by team, to take to whoever approved the spend.
The teaching comes as named courses, one per group of teams, and the call picks which.
A 30-minute call
Where your rollout is, and which teams or workflows you'd like to start with.
I look at how your teams work
I talk to the team leads and go through the process documents for the workflows you've chosen, and suggest others where I see a better place to start. How long it takes depends on the scope we agree.
A baseline before anything is taught
The people attending say how they use AI on those workflows today and how that work gets done. That is the mark everything after is measured against.
I teach your people to use AI there
Remote or on-site, for the people who haven't worked it out yet. They learn to use AI on those workflows, so they do that work more efficiently and AI becomes the first thing they reach for. Your power users are welcome to join.
What changed
After the teaching, the same people say what they now hand to AI and where they still don't. You see the change against the baseline, team by team, and we decide where the next cohort starts.
Same task, same tool, two different jobs.
What most people send
Write a summary of this report for the leadership team.
What your top 5% send
Here is the report, and the three slides the board saw last quarter.
Summarise it for our leadership team, who already know the background and want what changed.
One page. Lead with anything that moves a number. Flag anything you're unsure about rather than smoothing it over.
Nobody taught anyone the second version. The people who write it worked it out on your documents and your approvals, which is why no vendor course covers it. I teach it on your own work.
Why the gap is still there.
You have probably tried some of these already. This is what each one leaves you with.
The vendor's own course
Teaches the product: the features, the modes, what the assistant can do. Your power users didn't learn there. They worked it out on your documents and your approvals, which no vendor has seen.
An e-learning platform
Produces completion rates. Everyone finishes the module, and on Monday the same one-line prompts go out as before.
Your own power users
They can show what they do, and they often will. They can't see where their habits came from, and they have their own jobs, so the rest of the team gets a lunchtime demo and a link.
A generic AI trainer
Runs the same day for every organisation, on prepared examples. Here the teaching starts from your workflows, so what people practise is the work they go back to.
Where the gap shows up first.
The same split appears wherever the licences went out to everyone. This is the work I'd start with.
Professional services
The first draft of a client report, the research behind a recommendation, a proposal that has to read as if a partner wrote it. The 5% already hand these over and check the result. Everyone else still starts from a blank page.
Financial services and insurance
Policy documents, client communications and regulatory reporting, where the tools have to be used inside the rules. The work is finding what can be handed over without moving the line on accuracy.
Technology and telecoms
Engineering got the training and the rest of the company got the licences. Sales, support, operations, HR and legal are where the gap is widest, and where most of the hours are.
Legal
First-pass reviews of long documents, research starting points, first drafts of letters and clauses. The 5% already hand these over and check every line. Everyone else still reads and drafts from scratch, fee earners and support teams alike.
Luxury and heritage
Client follow-ups, product and heritage copy, the same story adapted for every market. The 5% already hand over the first draft and keep the house voice. Everyone else writes it all by hand, or keeps away from the tools.
Who is in the room
The people who have not worked it out yet, whatever their job: customer success, sales, support, operations, HR, finance, legal. No technical background, and nothing to code. Your power users are welcome, and it works with the tools you have already bought.
If your rollout has not started yet, the teaching works just as well before the licences go out. Your engineering team is different work: the AI Engineering Workshop teaches them to work with coding agents and to build agents, by the same person, so one conversation can cover both.
What they leave able to do
They use AI on their own workflows to do that work more efficiently, and reach for it first in their day-to-day work.
What else the engagement can include.
A talk for the whole company
The split, shown to everyone at once, so the teams being taught know why before the teaching starts.
Talks for leadersMore cohorts
The same teaching for the next teams.
Briefings for managers
For the managers of the teams being taught.
Follow-up clinics
Time with the people who attended, on what they run into back at work.
Change management
Working with whoever owns the rollout on the change around it.
Agents in the workflows
Putting agents into the workflows we reviewed, for one person, one team or the organisation, as extra work alongside the teaching.
Before you book
- Does it work within our firm's AI policy?
- It works with the tools and the policy you already have. Where the policy says which tools are approved and what can go into them, the teaching follows it on every workflow. Writing the policy stays with you, and nothing here is legal or regulatory advice.
- Is it only for the people who bill clients?
- No. Anyone whose work runs through the workflows we choose can attend: consultants, analysts, bid and proposal teams, practice support and operations. Nothing in it involves code.
- Can people practise on real client work?
- They practise on the workflows we chose in the review, with the kind of material they handle every day. What can be used in the room follows your firm's own rules on client data.
- Which AI tools does it use?
- ChatGPT, Claude or Gemini, whichever your firm already pays for.
- What do attendees need to prepare?
- Nothing. There is no pre-work. The scoping happens between us before the teaching.
- What does it cost?
- It is quoted against the scope we agree on the call. Nothing is priced on this site because no two organisations need the same amount of work.
Questions about the tools, who attends and recording are answered on the Power User Gap page.
Who you'd be working with
I've spent twenty-five years teaching engineers and their organisations whatever technology had just arrived, and the last few building with these tools.
Google Developer Expert in Web Technologies, Agentic AI Foundation ambassador, MBA. 25 years across software engineering, developer relations and technical training, and 151 talks and workshops in 35 countries.
More about meStart with a 30-minute call
Tell me when the tools went out and which teams you'd start with. It's one quote, for the workflow review and the teaching of the teams we agree on the call, so the figure you forward covers all of it.