Hands-on implementation support
A monthly engagement that solves "we bought the tool and nobody uses it": define usage metrics, train the frontline, review weekly, change the process until AI is the default.
Going live is not adoption. The usual failure looks like this: the system is bought, accounts are issued, and three months later the only people using it are the two who championed it. This engagement covers the period after launch — fix the metrics, look at the data weekly, find out what is blocking the people who are not using it, and change the process, the prompts or the division of labour until it sticks.
Who it is for
- An AI tool or agent is already live but usage is flat
- There is no dedicated internal owner and the business lead has no time to chase it
- You need to justify the investment to management and have no data to do it with
Not a fit:
- Nothing is live yet. Start with agent delivery.
How we run it
- Define metrics. Agree three measurable indicators with the business owner and record the baseline.
- Train the frontline. Short role-specific sessions — three things per role, nothing else.
- Weekly review. Read the usage data, interview the people who are not using it, and identify the real obstacle.
- Change the process. Write the AI step into the SOP and the performance criteria, and remove the duplicated manual work.
- Monthly report. A comparable set of numbers for management, and a decision on whether to invest more or stop.
What you get
- Metric definitions and baseline data
- Role-specific training material and updated SOPs
- Weekly review records and an obstacle log
- Monthly effect report
Related cases
Questions we get asked
- How long does a typical engagement run?
- It is billed monthly and scoped per engagement. The honest answer is that adoption either shows movement within a couple of monthly cycles or the problem is not training — it is the process or the tool.
- What metrics do you use?
- Three, agreed with the business owner, and always measurable from a system rather than from a survey. Usage rate per role and time-to-complete for the target task are the two that appear most often.
- What if the conclusion is that the tool was the wrong choice?
- The monthly report says so. Continuing to train people on a tool that does not fit the work is the more expensive option.
Related services
See how AI describes your brand todayThe free GEO audit reports the current state across AI platforms. It does not include a fix plan — that is what the paid work is for.
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