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The Power User Gap for financial services and insurance

AI training for financial services and insurance teams, inside the rules.

In financial services and insurance the split shows first in the documents that have to be right: policy wording, client communications, regulatory reporting. The work is finding what can be handed to AI inside the rules, and teaching your people to do 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.

88%use AI mostly for search and summarising
5%use it to change how they work
The Power User Gap is the split EY's Work Reimagined Survey measured in August 2025: 88% of employees use AI at work, mostly for search and summarising, and 5% use it to change how they work. 15,000 employees and 1,500 employers, 29 countries.

Where the gap shows in financial services and insurance.

The Power User Gap for financial services and insurance teaches the non-technical people in a bank, insurer or other financial firm to use ChatGPT, Claude or Gemini on the documents they handle, inside the AI policy the firm already has.

These are the kinds of work I'd look at first. Your team leads and process documents decide which ones we actually start with.

  • Policy and procedure lookups

    Finding what the internal procedure says about a case, with the section quoted, so anyone can check the answer against the source before acting on it.

  • Summarising long documents for review

    A policy wording, a claims file or a credit paper cut down to the points a reviewer needs, with page references, so the review starts in the right place.

  • Customer correspondence, drafted for a person to check

    First drafts of letters and emails in the approved tone. A person reads, corrects and sends every one, and stays accountable for what goes out.

  • Checking a document against a checklist

    Running a document past the firm's own checklist and listing what is missing or inconsistent, as a first pass before the human review.

  • Staying inside the AI policy

    Which tools are approved, what data can go into them and what has to stay out is already decided by your firm. The teaching works inside those lines and makes them concrete for each workflow.

What the teaching looks like there

The baseline comes first: the people attending say how they handle these documents today and where they already use AI, if they do. Then they practise on their own work with the approved tool, and much of the time goes on checking: asking for sources and page references, spotting where the tool has guessed, and knowing which work stays with a person. Afterwards the same people say what they now hand to AI and where they still don't, so the change shows against the baseline, team by team.

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.

  1. A 30-minute call

    Where your rollout is, and which teams or workflows you'd like to start with.

  2. 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.

  3. 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.

  4. 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.

  5. 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.

  • 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.

  • 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.

  • 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 leaders

More 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

Can it work inside our AI policy and the rules we operate under?
It works with the tools and the policy you already have. Which tools are approved and what data may go into them is your firm's decision, and the teaching follows it on each workflow. Nothing here is legal or regulatory advice.
Does AI replace the human review?
No. Everything in it assumes a person checks what the tool produced before it is used. Much of the teaching is about making that check easier: asking for sources and page references, and for a flag wherever the tool is unsure.
Which teams is it for?
The people who handle the documents: customer service, claims, underwriting and operations teams, HR and finance. No technical background, and nothing to code.
Can we start before the tools are fully rolled out?
Yes. The teaching works before the licences go out as well as after.
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.

Tamas Piros teaching a full room, standing at the front and explaining with both hands

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 me

Start 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.