Before Your Business Buys Another AI Tool, Answer These Five Questions

AI planning starts with understanding the work your business needs to improve. Before choosing a tool or adding another subscription, take a close look at one process that costs your team time every week.
Maybe employees keep rewriting the same customer information. Maybe an internal request moves through several inboxes before anyone takes responsibility. Maybe your team spends too much time preparing a first draft of a routine update.
A useful starting conversation brings the business owner, the person doing the work and the IT team together. Here are five questions we recommend putting on the agenda.
1. What specific task are we trying to improve?
“We want to use AI” is a direction, but it does not define a project. Name the task, the people involved and the result you want.
For example: “We want to reduce the time it takes to prepare the first draft of our internal weekly update.” That statement gives the team something to test. It also makes it easier to notice whether the real problem is a missing process, unclear ownership or information scattered across too many places.
Write down the current steps before changing them. Include the time spent correcting errors and reviewing the finished work.
2. What information would the tool need?
List the information required for that task. Then decide what the pilot is allowed to use, who approves access and where the results will be stored.
Start with a narrow example and approved sample material. Before connecting business systems, have your IT team review permissions, account ownership and the relevant service settings and terms. Customer records, confidential business information and credentials need deliberate handling.
The pilot should have a clear boundary. “Everything in our shared drive” is a very different starting point from a small collection of approved internal documents.
3. Who checks the work and approves the next action?
Choose a named person to review the output. Define what that review covers: facts, completeness, tone and whether the result is appropriate for its intended use.
Also decide which actions require approval. Drafting an internal message and sending a message to a customer are separate steps. Your first pilot can produce a draft while a person retains control of distribution.
Give employees a clear way to report an incorrect result. Decide who can pause the process if it behaves unexpectedly.
4. How will we decide whether the pilot helped?
Pick a few measures before the test begins. Consider total time per task, corrections required and whether the finished work meets the team's quality standard.
Count review time. A fast first draft is useful only if the complete process improves. As an illustration, if a task takes 30 minutes today and the pilot takes 10 minutes to draft plus 15 minutes to review, the saving is five minutes. That is a hypothetical example, not a promised outcome.
Compare similar tasks and record exceptions. A measured result gives you a practical basis for deciding whether to continue.
5. What must be true before we expand?
Agree on an end date for the pilot and a short review. Decide whether to continue, revise or stop based on what the team observed.
Expansion should include documented instructions, employee training, access review and an owner for ongoing checks. A successful test with one person does not automatically answer how the process will work across the company.
For organizations developing a broader approach, the NIST AI Risk Management Framework is a voluntary resource for managing AI-related risks. It offers a starting point for structured evaluation; using it is not a certification or a guarantee.
Start with a practical discovery conversation
Flint Tech Solutions helps business leaders examine where AI could fit, what information and systems are involved, and what oversight the work needs.
Our first conversation focuses on your current process and goals. From there, we can discuss whether a separately scoped discovery assessment or implementation project makes sense.
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