Help your team use AI with confidence.

Choose the work

Where should a team start with AI?

Start with one recurring task that has a clear purpose, an accountable person, and an output someone can check. A first pilot might turn approved project notes into a draft status update or help a team organize internal information before a meeting.

Write down the current process before choosing a tool: where the information comes from, who uses it, what happens next, and where work stalls. If nobody agrees on what a good result looks like, clarify that first.

Choose a task where a mistake can be caught and corrected before it affects a customer or another team. Keep consequential decisions with the people accountable for them.

Choose the right approach

Does the workflow need AI or automation?

A workflow can use both. AI can prepare a draft; a person checks it; an automation moves the approved result to the next step. AI output can be wrong, so a fluent answer is not enough to approve it.

For predictable steps, start with a simple rule. Read our guide to choosing which business processes to automate first.

Illustrative workflow

From meeting notes to accountable action.

This example illustrates a possible workflow, not a client case study or a claim of measured results.

1. Capture approved notes. Use information the team is permitted to process in the chosen tool.
2. Prepare an action draft. Ask AI to separate decisions, proposed actions, named owners, and open questions. Mark missing details as unknown.
3. Review before assigning. The meeting lead compares the draft with the notes, checks names and dates, and confirms commitments with the relevant people.
4. Connect the approved work. An automation creates confirmed tasks in the team's system and routes reminders. Unresolved questions go back to a person.

The approval step is part of the workflow. A suggested action should not quietly become a commitment just because a tool can create a task.

Make governance usable

What rules should be in place before a pilot?

A short, usable set of rules should answer the questions people face while doing the work:

• Approved tools and dataWhich tools may the team use, and which information may go into them? Confirm the organization's access, retention, and data-handling requirements before the pilot.
• Review and approvalWho checks the output, what do they check, and what must be approved before sharing or taking action?
• Ownership and exceptionsWho is responsible for the workflow? Where does someone report an error or stop a result they cannot verify?
• Changes over timeWho reviews the workflow when the tool, data, or intended use changes?

Match the oversight to the work and its consequences. Involve the organization's relevant security, privacy, or compliance specialists where needed.

For a broader governance resource, the NIST AI Risk Management Framework Playbook describes the importance of defined responsibilities, oversight, and training. The workflow above is our practical illustration, not a certification or compliance assessment.

Build confidence through practice

What should practical AI training include?

Train people on the workflow they will actually use. A demonstration is a starting point; confidence comes from practicing, checking the result, and knowing when to ask for help.

Leave the team with a reusable example, a review checklist, and a named point of contact. Ask each participant to complete a practice task and explain their checks.

Decide what earns expansion

How do you know whether AI adoption is working?

Record a baseline before the pilot. Compare the same kind of work afterward, including time spent checking and correcting the output.

• Time from request to approved result
• Errors and corrections required
• Missed or unclear handoffs
• Team confidence and independent use

Agree on what would justify expanding, changing, or stopping the pilot. A fast draft is not a useful improvement if review creates more work downstream.

Use the team's feedback to refine the instructions, training, and approval points. Expand when the process is useful and repeatable, with ownership still clear.