The Small Business Administration and its resource partners have spent the summer offering programs on where artificial intelligence fits into small-business operations, how to evaluate tools, and how to implement them responsibly. The interest is understandable. Owners are being told that AI can reduce administrative work, improve customer engagement, strengthen marketing, and accelerate decisions. The danger is not that small businesses will ignore the technology. It is that they will begin with an AI strategy before they have identified the operating problem worth solving.
A small business does not need a broad AI vision to begin. It needs one recurring source of friction. That might be a weekly report assembled by hand, customer inquiries that receive inconsistent answers, delivery routes that no longer match demand, or managers spending hours transferring information between paper and software. The owner should document how the work happens today, how often it occurs, what it costs, and what failure looks like. Only then should the business consider whether AI is the appropriate tool. Sometimes conventional automation, a clearer form, or a better management routine will solve the problem more reliably.
Starting with the workflow creates a more honest economic case. A tool demonstration can show that a task takes seconds, but the business still needs to account for setup, subscriptions, employee training, review, corrections, data preparation, and process change. A useful pilot should establish a baseline and track an outcome that matters: hours returned to customer-facing work, fewer errors, faster response, more completed tasks, improved conversion, or lower operating cost. Usage is not the result. A team can generate hundreds of summaries without improving a single decision.
The first use case should also be consequential enough to matter and contained enough to control. Drafting internal material from approved information is easier to supervise than allowing a system to communicate commitments to customers. Identifying exceptions in a report is safer than authorizing refunds or payments. Owners can begin with read-only access, require human approval, and expand permissions only after the process proves reliable. NIST's AI Risk Management Framework uses the functions govern, map, measure, and manage. A small company does not need a large compliance department to apply the logic. It needs a named owner, a defined purpose, a clear data boundary, a way to test results, and a decision about when the system must stop.
Employees should be involved before the tool is selected. The person doing the work knows which exceptions break the standard process, where information becomes unreliable, and what customers actually expect. Excluding that knowledge creates systems that look efficient in a demonstration and fail under normal operating pressure. Involving employees also changes adoption. People are more willing to use a system when they understand which burden it removes, what judgment remains theirs, and how success will be measured. Change management is not an enterprise luxury. In a small business, it is the difference between a purchased tool and a working process.
At Stottly Enterprises, we have seen the value of this approach in restaurant and distribution operations. The technology mattered, but the gains came from observing managers, mapping the existing work, reducing unnecessary steps, and building the solution around real operating behavior. The strongest result was not the presence of AI. It was the return of management time to employees and customers. That is the standard small-business owners should use: does the system improve the operation, or does it simply add another place to work?
An AI strategy may eventually become useful as adoption expands across the company. It can define principles, investment priorities, risk tolerance, and shared infrastructure. It should not become a substitute for selecting the right first problem. Small businesses have an advantage because owners are close to the work and can see the consequences quickly. Begin there. Find the friction, establish the baseline, improve one workflow, and measure what changed. Strategy will be stronger when it grows from evidence.
Sources
- - U.S. Small Business Administration, “AI Day: What’s New & What’s Next With AI,” July 16, 2026: https://www.sba.gov/event/86267
- - U.S. Small Business Administration, “AI Fundamentals: The Small Business Owner’s Playbook,” June 30, 2026: https://www.sba.gov/event/85301
- - U.S. Small Business Administration, “From Intimidation to Implementation,” June 15, 2026: https://www.sba.gov/event/84442
- - NIST, AI Risk Management Framework: https://airc.nist.gov/airmf-resources/airmf/
- - NIST, Small Enterprise Quick Start Guide: https://www.nist.gov/news-events/news/2024/07/introducing-rmf-small-enterprise-quick-start-guide
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