Everyone is trying to figure out what AI is going to do to their business. Some think it will change everything. Some think it will replace half the workforce. And somewhere, right now, someone is probably trying to use AI to fix a process that could be solved by two people agreeing on who owns a spreadsheet.
AI is powerful, but it is not magic. It cannot fix a process nobody understands, decide which of three conflicting numbers is correct when nobody agrees on the source of truth, or make bad data good because you asked nicely.
That is why I think the better question is not “Where can we use AI?” It is “What problem are we actually trying to solve?”
AI works best when the job is specific
The most useful applications of AI are usually pretty focused: read these documents, compare these records, find the exceptions, summarize these notes, identify missing information, draft the first version, flag anything that does not match the rules.
That is purpose-driven AI. A defined job, a defined outcome, and a human who still knows what “right” looks like.
A faster bad process is still a bad process
If the process is broken, automation does not necessarily fix it. If the data is inconsistent, AI can process inconsistent data faster. If the approval workflow makes no sense, AI can move confusion through it more efficiently.
Sometimes the smartest AI strategy starts with fixing the process first.
The human part still matters
AI can reduce repetitive work, surface information faster, and improve efficiency. But someone still has to define the rules, recognize when the answer is wrong, and own the outcome.
That is why the companies getting the most value from AI are not necessarily the ones using the most AI. They are the ones using it deliberately.
Sometimes the answer is AI.
Sometimes it is cleaner data.
Sometimes it is a better process.
And occasionally the answer is still:
Stop using FINAL FINAL v2.xlsx.
A better question
Instead of asking “How can we use AI?”, ask:
“What work are our people doing today that a machine could do faster, more consistently, or with fewer errors?”
That usually leads to better ideas.
And useful work is where AI gets interesting.
