For years, a lot of companies treated support like a mop.

Something to bring in after the real work was done.

Sell the product.

Ship the product.

Then clean up the confusion.

That model is breaking.

Gartner’s latest customer service survey says 91% of service and support leaders are under pressure from executives to implement AI in 2026. The goals are not tiny either: customer satisfaction, operational efficiency, and self-service success are all top priorities.

In a related view of where the function is going, Gartner’s customer service trends report says service is moving upstream, with AI helping teams shift from reactive demand handling toward product usage, adoption, and revenue growth.

That last phrase is the real headline.

Support is not just cost control anymore.

It is becoming growth infrastructure.

I say that with love, because I’ve made the same mistake.

In plenty of startups, GTM is built like this:

Neat boxes. Clean slide. Looks smart in a board deck.

Real life is messier.

The support team hears friction first. They see onboarding pain first. They notice product confusion first. They know where expectations broke, where documentation failed, and where customers start getting nervous about value.

That is not back-office noise.

That is commercial intelligence.

A lot of executives hear “AI in service” and immediately think “fewer humans.”

Maybe some of that will happen in narrow workflows.

But the smarter takeaway is different.

AI can absorb repetitive questions, speed up resolution, improve routing, surface knowledge, and reduce customer effort. That creates room for human teams to do higher-value work:

That is revenue work.

If a customer gets stuck in week two and never activates the part of your product that drives stickiness, no marketing campaign on earth is going to save that economics later.

One of the more interesting ideas in Gartner’s 2025 trends piece is that customers themselves are increasingly willing to use AI assistants to interact with service on their behalf.

That means your support function is starting to serve two audiences:

I love and hate that future in equal measure.

I love it because it can reduce friction and make routine issues faster to resolve.

I hate it because it exposes every weak process instantly.

If your policies are inconsistent, your knowledge base is thin, your workflow depends on tribal knowledge, or your response logic is full of edge-case chaos, machine-mediated service will drag all of that into daylight.

This is the mindset shift.

The old question was:

The better question now is:

That changes what matters.

Metrics still matter, but the set gets broader:

Once you look at it that way, support stops being the place where growth goes to die.

It becomes the place where growth gets protected.

Which issues signal churn risk? Which questions signal expansion intent? Which onboarding blockers hurt retention later?

AI should kill repetitive friction before it touches nuanced judgment.

If the docs are bad, self-service is fiction.

Embed support signal into onboarding, lifecycle, product, and sales enablement.

Let AI handle repetition so people can handle judgment, reassurance, and complex problem-solving.

If you still think support is just a cost center, you’re probably undercounting how much revenue is leaking through confusion.

And confusion is expensive.

The companies that win the next phase of GTM will not just acquire demand better.

They will protect and expand value better after the sale.

That means support is no longer the cleanup crew.

It’s part of the growth engine now.