In a recent ServiceTitan industry report covered by Homepros, service businesses are splitting into two camps: those embedding AI into daily operations and those choosing to wait and see.
On the surface, waiting feels reasonable. AI is moving fast. Tools are noisy. No one wants to disrupt workflows that already feel stretched.
But in service operations, waiting isn’t neutral. It’s a decision with real revenue and operational consequences. For growing service businesses, the question is no longer if AI belongs in the front office.
It’s whether your communication infrastructure is built to scale — or to stall.
In this post, we'll break down why the cost of inaction is higher than most teams realize, what the data actually shows, and what it looks like to adopt AI in a way that scales your team instead of replacing it.
Every service business runs on 1:1 customer communication:
According to the ServiceTitan data, only 12% of service businesses have fully embedded AI into their operations, while 41% report taking a wait-and-see approach and 34% are limited to small-scale experimentation.
Demand isn’t slowing down while leaders evaluate. Customers don’t pause expectations because internal systems can’t keep up.
When response speed lags or follow-up depends on overloaded teams, revenue quietly disappears. Waiting doesn’t preserve the status quo but it locks in inefficiency.
This isn’t speculative adoption. The same report shows AI is already delivering measurable gains:
These are the workflows that break first when volume increases and the exact moments where speed, consistency, and follow-up determine whether revenue is captured or lost.
One of the biggest reasons teams hesitate is fear,especially among CSRs, that AI means replacement.
That’s not how modern service operations work.
At Hatch, AI and humans work as one operational layer by design:
AI CSRs handle speed, volume, and consistency across voice, SMS, and email — so human CSRs can focus on nuance, escalation, and real customer connection.
This isn’t automation for automation’s sake, it’s operational leverage.
The result:
AI becomes infrastructure — not another tool to manage.
The service businesses actively embedding AI aren’t chasing hype. They’re solving operational problems:
The report shows efficiency and productivity gains are the top benefits contractors associate with AI, outweighing even direct cost reduction.
That advantage compounds over time and waiting doesn’t just delay results, it widens the gap between leaders and laggards.
The industry is moving from disconnected tools to unified operational systems.
AI is no longer an add-on. It’s becoming the foundation that allows service businesses to scale revenue — without scaling complexity.
Teams that move now gain:
Those who wait will still adopt — but later, under pressure, and with less ability to shape outcomes.