Will AI Eat IT Service Partners?

The entire reason a service partner’s role exists comes down to one thing: the upstream platform produces generic capability, while the downstream customer is staring at their own messy, specific business reality. There’s a gap between the two, and someone has to fill it. What a partner gets paid for is exactly the cost of filling that gap.

That “gap” isn’t one single thing — it splits into at least three kinds:

• Technical coordination — translating business requirements into system configuration. This is the piece AI can genuinely replace at scale.
• Trust coordination — who’s accountable when something goes wrong, whose job is on the line for this project. That’s not an information-processing problem; it’s a problem of how responsibility gets distributed between people.
• Ongoing coordination — both sides keep changing. The platform keeps upgrading, the customer’s business keeps evolving, and someone has to keep watching both sides stay in sync. That by itself requires a role that’s actually “present.”

Right now, AI is still mostly something with strong “technical substitutability,” and it will keep eating into that first layer. That means small and mid-sized customers with relatively standard, low-complexity needs will gradually stop needing a service partner.

But large customers — the ones with high complexity and multiple departments fighting over competing interests — will still need a service partner as the coupling agent between them and the platform.

There’s one more variable worth throwing in here: the upstream platform’s own incentives might be shifting too. In the past, the platform and the partner had aligned interests — the partner helped the platform reach further than it could on its own. But if AI lets the platform serve end customers well on its own, the platform itself now has an incentive to weaken, or even bypass, that partner layer entirely.

I’m not sure yet how viable that last variable actually is.