“It’s just a fad.”
Sometimes that is a sensible response to a new technology. Businesses cannot afford to chase every announcement, subscription or impressive demonstration.
But sometimes it is something else: a comfortable way to postpone a difficult decision.
Because if a technology matters, we may have to learn something. Reconsider a process. Admit that a method we have defended for years could be improved.
Dismissing it allows tomorrow to look reassuringly like yesterday.
For a while.
The cost of waiting is difficult to see
A software subscription has a price. A development project has a budget. Training takes hours that appear in someone’s calendar.
Doing nothing rarely arrives with an invoice.
Instead, its cost is scattered across the working week.
Someone copies information between systems. A customer waits while a colleague searches for an answer. An owner spends Sunday evening assembling a report from several spreadsheets.
Each task feels manageable. Together, they consume capacity that could support better service, more customers or a less exhausting business.
That is why the useful question about AI is specific:
Could it help us change something that currently costs us time, money or opportunity?
Scepticism should lead to a test
Imagine a business receiving similar enquiries every day.
An experiment could connect approved product information to a system that prepares draft responses for staff to check. The business could then assess preparation time, accuracy, corrections and customer experience.
Perhaps it works well. Perhaps the information is too inconsistent. Perhaps a simpler automation solves the problem more reliably.
All three outcomes teach the business something.
“It’s a fad” teaches it nothing.
There is an important difference between examining a technology and dismissing it before examining a relevant use.
You do not need certainty to begin
You need a problem worth investigating, a limited trial and a way to judge the result.
That is how uncertainty becomes evidence.
At InnoWeb Ventures, this is the work that interests me: taking a business frustration and exploring whether AI, automation or better software can meaningfully improve it.
There is no value in forcing AI into a process that does not need it. There is also little value in defending a frustrating process simply because it is familiar.
Some new tools will disappear. Others will become ordinary parts of working life.
The question is whether your business has a way to tell the difference.
What have you dismissed recently—and what evidence would make you reconsider?