How do you move AI from a pilot into everyday work?

Moving AI into everyday work requires an agreed process, capable people and clear ownership after the pilot ends. Before expanding a trial, establish what will change, who will be responsible and how the business will judge whether the new approach is useful. Training is one part of that transition.

A pilot can show that a tool performs a task under selected conditions. Introducing it across normal work adds varied requests, competing priorities, less experienced users and the need for ongoing support. Plan for those conditions before widening access.

Understand the work from the team’s perspective

Ask staff to show how the task is completed today, including exceptions, informal checks and the judgement that experienced people apply. Identify where the proposed approach changes a handover or transfers effort to somebody else.

Consider an illustrative proposal-writing pilot. AI may prepare a first draft quickly, while another person still needs to confirm the scope, pricing and commitments. If that review work grows or becomes harder to perform, the overall process may not improve. The evaluation needs to include the people receiving the output as well as those creating it.

Staff involvement should affect the design. Use their observations to change the workflow, access arrangements, instructions and review requirements. Explain what was changed and why so participation has a visible purpose.

Agree the purpose and the responsibilities

Leaders need a shared account of what the initiative is intended to improve and how success will be assessed. Be specific about whether the aim is greater capacity, better consistency, faster response or another business outcome.

Explain what is decided and what is still being tested. Address questions about responsibilities, performance expectations and how work may change. Where broader workforce decisions are unresolved, keep that distinction clear rather than making assurances the organisation has not agreed.

Document the future process in practical terms:

• Who starts the task and supplies the information.
• What the tool does and what remains a person’s responsibility.
• Who reviews or approves the result.
• Where the completed work is recorded or handed over.
• What to do when the tool is unavailable or the result is unsuitable.

Check that the relevant managers accept those responsibilities and can allocate time to them.

Set a clear decision point for leaving the pilot

Agree the conditions for wider use before judging the pilot. Assess the quality of completed work, the effort required across the whole process and the team’s ability to identify and manage problems.

Use representative tasks, including difficult cases and work from people outside the original enthusiastic group. Record unresolved limitations. A solution that depends on constant intervention from its builder may need further work before the operational team can own it.

The decision can be to proceed within a defined scope, adjust the approach or stop. State who makes that decision and what evidence they need. This helps a pilot conclude with a useful business decision rather than remaining an indefinite experiment.

Prepare people for the actual process

Build training around the work staff will do. Give them examples of acceptable results, examples that need correction and situations that should be referred to someone else. Allow practice using information approved for the exercise.

Managers need preparation too. They should know how to review work, respond to questions and recognise when a problem belongs with the process owner or technical support. People supporting colleagues need time for that role and a clear route for issues they cannot resolve.

Keep instructions close to the task. A short guide covering the approved process, checks and support route is easier to use during work than a presentation that assumes people remember every detail.

Measure adoption alongside quality and value

Usage tells you that a tool has been opened. It does not establish whether the work improved. Combine adoption information with measures of completed work, quality, rework and the effort required to achieve the result.

Compare against the current process and examine the reasons for variation. Low use might reflect access problems, a poor fit, competing work or unclear expectations. High use might still produce outputs that need extensive correction. Speak with the team before drawing conclusions from activity alone.

Be clear about how any released capacity will be used. An improvement in task time becomes commercially meaningful when the business can explain what that change enables and account for the cost of review and support.

Establish ownership beyond launch

Name the person responsible for the process, the person maintaining guidance and the support route for technical problems. Agree how feedback is reviewed and who decides on changes to the tool or its permitted use.

When the new process is accepted, update the working instructions and decide when the old process can be retired. Keep an understood fallback where continuity requires it, so uncertainty does not create two competing ways of working indefinitely.

My people and change management work connects leadership alignment, staff involvement, process design and practical support with the commercial purpose of introducing AI.