AI for AI seat adoption

The problem

Many enterprises bought AI seats for whole departments. A few months later, usage reports show the same pattern: a handful of enthusiasts, a long tail of people who tried it once, and nobody who owns adoption. Leaders are asked to renew without evidence that the seats changed how work gets done.

The gap is rarely the technology. People do not have time to work out which of their tasks AI should take on, and the examples in training sessions do not match their actual workflows. Pilots stall between the innovation team and the people doing the work.

At the same time, software spend keeps rising. Departments run several tools that overlap: two note takers, three project trackers, separate form, survey and reporting products. Some of that work could now be handled by the AI seats already paid for, but nobody has mapped it.

What the AI setup does

1. Maps real work. The operator interviews the department and reviews where time goes, using meeting notes, ticket and task data, and calendars, to list recurring tasks by hours spent.
2. Picks the right tasks. Tasks are ranked by hours, repetition and risk. The top few become the first builds.
3. Builds inside existing tools. Each task gets a working setup in Microsoft 365 or Google Workspace, Slack, Salesforce, HubSpot, Jira, Asana or Notion, so people use AI where they already work.
4. Coaches by task. Short sessions show each team how to use the new setups for their own work, with written guides kept in your shared space.
5. Measures use weekly. It tracks which setups are used, by how many people, and the hours they return, and flags teams where use drops.
6. Maps overlapping software. It builds an inventory of the department’s tools, what each is used for, how often, and where it overlaps with another tool or with what AI now covers.
7. Prepares the decision pack. Leaders get a plain summary of options to keep, consolidate or retire, with the evidence behind each.

Tools it works with

We work inside your existing estate: Microsoft 365 or Google Workspace, Slack, Salesforce or HubSpot, Jira, Asana, Notion and Airtable, plus meeting tools such as Fireflies, Granola or Fellow where the department already uses them. We use the AI seats you already pay for, and access is granted and scoped by your IT team.

How we would do it

Enterprise work starts with a 90 day pilot in one department. An embedded operator joins that department, on site and remote, backed by a bench of AI agents and specialist partners.

The first weeks set a baseline of current seat usage, time spent on recurring tasks and the tool inventory. Security and change management are planned in from the start with your IT team, rather than at the end. The first automation is live in week one, chosen so people see a real task get easier straight away. Over the pilot we add setups task by task and report adoption and hours every week.

At the end of the 90 days, leadership gets measured savings, adoption figures and the overlap map, plus a plan for the next department. Our estimate for a department of a few hundred people is 100 to 250 staff hours a month returned, depending on how many recurring tasks move into working setups.

What stays in your hands

You approve everything. Every build is agreed with the department lead, anything customer facing is drafted by AI and approved by a person, and all software decisions remain with your leaders.

You own what we build. Setups, guides and the software map live in your accounts, with no licence fees after the engagement. We keep only anonymized patterns about how work gets done, never your business data.

Mistakes are logged and fixed the same day. The affected workflow pauses until the cause is fixed, and every error appears in the weekly report.