Micro-Automations: The Quiet AI Revolution
When it comes to AI, the spotlight tends to shine on the dramatic: Models that ace medical exams, write like seasoned authors, or spit out images indistinguishable from real photos. But while those headlines grab attention, the real transformation is happening quietly, behind the scenes in the form of micro-automations.
These are not all-competent copilots. They’re surgical, single-task automations that chip away at the inefficiencies baked into our everyday workflows. And done right, they shift the productivity curve without anyone noticing.
Efficiency isn’t always flashy, but it adds up
There’s a tendency to equate productivity gains with big, obvious tools such as AI note-takers, code or content generators. But often, real productivity comes from removing friction, the stuff that drains time but doesn’t make headlines.
Micro-automations excel here. Think of tasks such as file management, tagging assets, pre-filling forms or nudging the next logical step in a process. The key is subtlety.
The best of these tools don’t ask users to change behavior or learn something new. They just take a six-click process and reduce it to one. Over time, those micro-saves become macro value.
Trust builds faster with small, reversible steps
One of the big challenges with automation is trust. It’s hard to hand over entire workflows to a black box. But micro-automations earn trust gradually. They’re specific and understandable, and often keep a human in the loop.
When users see consistent results, a correctly tagged document, a complex data room setup with a click, or a helpful prompt at the right time, confidence grows. If it fails, no big deal. The stakes are low, and the system learns. That’s a much easier pitch than “let the AI run the whole show.”
The future of AI is in understanding the use case
Large language models are becoming commoditized. The real value-add now lies in how well they’re integrated into specific workflows. Micro-automations that are deeply tuned to business logic and domain-specific needs are where the moat is built.
It’s not about whose AI writes a better paragraph. It’s about who knows when a specific paragraph is needed, why and what it should trigger next. Companies leading this space are stitching AI into vertical workflows and mastering its context.
Micro-automations may not be glamorous, but they’re quietly reshaping how we work, one click at a time.
Itay Sagie is a strategic adviser to tech companies and investors, specializing in strategy, growth and M&A, a guest contributor to Crunchbase News, and a seasoned lecturer. Learn more about his advisory services, lectures and courses at SagieCapital.com. Connect with him on LinkedIn for further insights and discussions.
Illustration: Dom Guzman
