If You’re Selling AI to Contact Centers, You’re Actually Selling to Systems IntegratorsOver the last six years, I’ve worked both inside AI vendors selling into contact centers and alongside systems

Over the last six years,  I’ve worked both inside AI vendors selling into contact centers and alongside systems integrators (SIs) who design, build, and run those environments. One pattern shows up again and again:

Early-stage AI founders think they’re selling to enterprises.

In reality, they’re selling to systems integrators first.

This isn’t a semantic distinction—it’s a go-to-market reality. And misunderstanding it is one of the fastest ways for promising conversational AI companies to stall out.

This post is meant to help founders reframe how contact center buying actually works, and why SIs are not just a channel—but the market makers.

Why SIs Control the Contact Center Market

In most large contact center transformations, the initial architecture is defined by the SI—typically by the SI salesperson working closely with the SI's and cusotmer's lead systems architects.

That architecture determines:

• Which platforms are “in scope”

• Which vendors are even considered

• How risk, cost, and timelines are framed for the client

Startups are often introduced after those decisions are largely set—unless they have a strong, trusted relationship with the SI already. The deeper and longer-standing that relationship, the more likely a startup is pulled in before the architecture is locked.

This matters because SIs:

• Can exclude vendors before the vendor ever knows

• Play a very active role in vendor evaluation

• Strongly influence or outright own the final recommendation that is made to the customer

Startup founders sometimes believe that if they “win the customer,” everything else will fall into place. In practice, even when a startup’s technology is selected, the SI often controls how (and how much) the vendor interacts with the end customer. Direct access is not guaranteed—it depends on how the SI wants to manage delivery and the vendor|customer relationship.

How Early-Stage Startups Misread SI Incentives

A common mistake I see is founders assuming SIs primarily care about features and benefits of the vendor’s software solution.

They don’t.

What SIs actually optimize for is:

• Trust and confidence in the software

• Delivery risk (their reputation is on the line)

• The contractual relationship with the vendor

• Whether there are teams and individuals inside the SI who already know how to work with the technology

Revenue and margin matter, but they’re contextual:

• On very large deals, a single software line item rarely moves the needle

• Sometimes higher-priced software is acceptable; other times, lower cost matters if the SI is absorbing risk or effort

• Headcount dynamics matter too—SIs may welcome tools that improve margins on one project, but resist them on another where staffing is already baked in

Two behaviors consistently hurt startups:

1. Trying to bypass the SI to “own” the customer

2. Treating the SI like a reseller, rather than a delivery and risk-bearing partner

A more subtle, but equally damaging mistake is presenting too early to SIs when there is only slideware and a one-pager. SIs want to know that your technology works and that it will create value for both the SI and its customer.   Early-stage companies don’t get the benefit of the doubt. If you don’t have a compelling, working demo or turn around a credible POC, confidence erodes quickly.

Red flags for SIs are both about technology and also the startup’s behavior:

• Lack of knowledge about the domain (in this instance, contact centers)

• Not listening to the SI or client's needs

• Unwillingness to invest in a POC, free trial, or hands-on validation

What SIs Actually Look for in Emerging AI Vendors

SIs evaluate early-stage vendors differently than enterprise buyers do.

Yes, they care about:

• Technical differentiation

• Architectural fit

• Clear use cases

• Supportability

• Commercial flexibility

But above all, they care about reliability, predictability, and trust.

Innovation is valuable—but predictability is critical. SIs don’t expect a seed-stage company to be perfect, but they do expect it to be very close to finished.

The fastest way a startup builds confidence is through:

• Strong demos

• Free trials

• Well-run POCs that show real-world behavior, not just promise

I’ve seen startups win SI support without large reference customers—but almost always because:

• They had a strong internal sponsor at the SI, or

• They came recommended by someone the SI already trusted

Why “Partnership” Is the Wrong Word (Early On)

When founders say, “We want to partner with SIs,” they usually mean:

“We want the SI to help us sell to end customers.”

That framing often fails because early on, SIs want to remain the expert and own the customer relationship. They tend to keep new vendors at arm’s length until trust is earned. Their priority is protecting delivery quality and client relationships, not accelerating a startup’s sales motion.

What early-stage companies should focus on instead is de-risking the SI’s choice to work with them.

That means:

• Making it easy to evaluate the technology

• Being flexible in early engagements

• Investing time and resources before expecting scale

“Technology enablement” or “delivery support” tends to resonate more than “partnership” language at this stage.

A true partnership only makes sense after the software has proven it can reliably create value for both the SI and their clients.

Practical Advice for Founders

If you’re a seed-stage founder selling AI into the contact center, here are a few concrete takeaways:

• Build a deliberate SI GTM plan. Identify which SIs are a fit, why they should care, and how you’ll approach them. Ad hoc outreach rarely works.

• Stop treating SI sales like enterprise sales. These are long-term, collaborative relationships—not transactional deals.

• Get comfortable with the timeline. SI-driven revenue can be powerful, but it takes time. Plan for that upfront.

• Avoid the anti-pattern. Dribs and drabs of SI activity usually go nowhere. This is closer to an “all-in” strategy than most founders realize.

Closing Thought

If you’re building conversational AI for contact centers and you’re not engaging systems integrators deliberately, you’re likely leaving enterprise deals on the table—not because your technology isn’t strong, but because your go-to-market approach doesn’t match how the market actually works.

If you want to compare notes or sanity-check how you’re thinking about SIs, I’m always open to a conversation.