Your business may already be using AI.
Ask your team which tools they use and what they use them for.
People under pressure look for relief. If they're writing emails, summarizing notes, researching, making reports, rewriting copy, or trying to get unstuck, there's a decent chance someone has already tried an AI tool.
That can be useful when the work is low-risk and the person checks the output.
But unmanaged AI use can create risk.
Why people bring their own AI
Microsoft's 2024 Work Trend Index found widespread use of AI at work, including employees bringing their own AI tools into the workplace.
Writing messages, preparing reports, and summarizing notes all take time.
People are dealing with more messages, more meetings, more tools, more content, more admin, and less uninterrupted time. If AI helps them get through the day, many will use it before leadership has a formal plan.
Your team may have useful examples to share.
What to ask your team
Ask which tasks the tools help with and which answers still need correction.
People doing the work can show you repeated tasks, drafts that are hard to start, and reports they rebuild each week.
Instead of starting with a top-down AI strategy, ask:
- Where are you already using AI?
- What are you using it for?
- What feels helpful?
- What feels risky?
- What do you still have to check?
- What work would you love to automate safely?
Use their examples to choose tasks for a closer review.
The risk
The risk is unmanaged AI use with no shared rules.
That can create problems with:
- private client information
- sensitive business data
- inconsistent quality
- made-up facts
- unclear authorship
- tools no one has reviewed
- work that sounds polished but isn't accurate
- employees relying on AI for decisions they should own
The business may think it has no AI exposure because it has no official AI system.
In reality, the exposure may already exist through everyday tool use.
Use rules instead of bans
Some businesses respond by banning AI.
That may be necessary in specific settings or for specific data. But as a general strategy, a ban often pushes use underground.
People still have the workload. They still have access to public tools. They still want help.
A better strategy is to create a safe path:
- approved tools
- clear data rules
- allowed use cases
- review requirements
- examples of good use
- examples of bad use
- workflows where AI is officially built in
People need to know what's okay.
Start with a practical AI use policy
A small business AI policy doesn't need to be complicated.
It should answer:
- What tools are approved?
- What information should never be pasted into AI?
- Which tasks can AI help with?
- Which tasks require human review?
- Which tasks are off-limits?
- How should AI use be disclosed internally?
- Who owns final output?
The last answer should always be: a human.
AI can assist. A person is responsible.
Then map the workflows
After you know how people are using AI, map the workflows where AI could be safely built in.
For example:
- meeting notes become reviewed action items
- intake forms become client summaries
- project updates become draft reports
- CRM status triggers follow-up drafts
- support questions pull from approved knowledge
Write down the approved tool, source records, and review step for each task.
Check whether the setup works reliably before more people use it.
What leaders should ask this week
Ask your team:
"What is one task you have used AI for, or would use AI for, if we had safe rules?"
Start with the person who's tired of rebuilding the same report every Friday.
Connect policy to practice
AI Team Training gives your team practice with approved tools, realistic tasks, and checking answers. AI Advisory supports decisions that continue as the work and tools change.