Practical thinking on
AI and automation
for businesses like yours.

AI often creates more work in a small business because the level of human oversight the tool actually needs does not match the level the process demands. Either someone is checking every output when the process was stable enough for AI to run it unattended, or the AI is running work that needed oversight and the humans are now fixing the results.

Yes, because a ChatGPT subscription and business AI are two different categories of tool doing two different jobs, where ChatGPT helps an individual person work faster at their desk while business AI runs inside an operational process and changes how the business itself operates.

AI pilots in small businesses fail for three specific reasons that are visible before the build starts: the wrong problem was chosen, the real operational data looks nothing like the data the demo ran on, and nobody defined what the pilot succeeding would actually look like in the business.

AI keeps disappointing because most small businesses buy at the chat layer, where a person prompts a tool and gets a clever reply, while the operational problems they wanted to solve sit one layer down in the workflow, which no amount of chat use will ever reach.

Most AI projects in small businesses fail because they skip the diagnosis — jumping to tools and builds before anyone has mapped where the business is actually losing time, what is causing it, and whether AI is even the right solution for that specific problem.

You cannot find your most costly business blind spots yourself because the closer you are to how your business operates, the more invisible the friction becomes.