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Your teams already use AI. Can you show the gain?

We find the tasks where AI saves real hours, test them with the people who do the work, and measure the gain before you roll it out across your business units.

Book a 30-min discovery call

For the head of transformation whose teams adopted AI faster than the company did.

Why the gain stays invisible

Licences went out and people use them. A few enthusiasts build their own agents, others paste the odd email into a chatbot, and most of the team works the way it did last year. Nobody can say which task got faster, by how much, or whether it would hold in another business unit. That shadow AI is real energy. Without a method, it never turns into a gain you can show your executive committee.

Two rules that keep the gain real

Start from the work

The tasks where the hours go

We sit with the people who do the work: the planner who rebuilds the same spreadsheet every Monday, the support agent answering the same question for the fortieth time. They tell us where their hours go and which AI they already use on their own.

We start with tasks, never with a tool.

Measure the gain

Before and after, on the same people

Each use case gets a baseline on the real task: time spent, rework, errors. Once the team has used the prototype, we measure again with the same people.

The evidence is a gain you can show, task by task.

The AI Gain Sprint: one team, four phases

  1. Diagnose

    Interview the team on its real tasks

    Twenty interviews with the people who do the work, Franck in the room. We map where the hours go and the AI already in use, take the baseline, and write the rules for safe use.

  2. Prototype

    Prototype three use cases

    Quick prototypes on their real task and your data, tested by the team itself. What nobody uses stops here, before the budget goes in.

  3. Decide

    Measure and decide

    The gain measured against the baseline, and a written go or no-go for each use case. If the numbers stay flat, we say so.

  4. Roll out

    Build, hand over, move on

    Forward builds version 1 of what survived, with your IT team in the loop from the start. Your team or your usual vendor runs it, and the method moves to the next business unit.

What you walk away with

The method in practice

These engagements were product launches, not AI projects. They show the method our AI work runs on: start from the people, measure, drop what nobody uses.

How Nissan's Lab builds with customers

Nissan Europe 12 weeks

4 strategic options with no product.

6 MVPs with users.

Ivan Ollivier, General Manager, Innovation Lab

See all client transformations

Questions buyers ask

Our teams already use ChatGPT or Copilot. Why bring you in?
Because using AI and saving time are two different things. We find which uses save real time on a real task, measure it, and turn them into a method the other business units can run.
Who builds the solution?
Forward builds the prototypes and version 1. Your IT team is in the loop from the start, on your data and your approved tools. Your team, or your usual vendor, runs it in production.
Can it work across several business units?
That is why we start with one team. The sprint leaves a method, interview guide and gain measurement included, that the next business unit runs the same way.
We already paid for an AI pilot nobody uses. Can you help?
Yes. We go back to the people the pilot was meant for, find the task it should have changed, and test whether another use would hold. Sometimes the right answer is to stop it.
Do you also work on AI features for our customers?
Yes, with the same method. Only the evidence changes: signed purchase orders and committed pilots instead of time saved.
Who does the work?
Franck Debane sits in the interviews himself. There is no handoff to a junior consultant.
How many companies do you work with?
Forward takes on four to six engagements a year, so each team gets the time it needs.

Launching a product rather than an AI use case? See how we work.

Want to show what AI gives your teams?

We need a leader who owns the result across teams, one team willing to talk to us from the start, access to its real tasks and data, and the commitment to drop what nobody uses. If you don't meet these, we'll tell you.

Book a 30-min discovery call