There's a question I think every IT leader should be asking when they evaluate their next ServiceNow partner:
Why am I still paying for headcount instead ofoutcomes?
The traditional SI model is built on a pretty simple equation. More work means more people. Need 200 catalog items configured? Staff up a team of admins. Building an app? Bring in an architect and a handful of technical consultants. The SI bills for time and materials, and the client ends up managing a small army of resources just to keep things moving.
It works. It has worked for years. But it's not the only way anymore.
The problem with billing for bodies isn't just the price tag. It's where the attention goes.
When you staff a large implementation team, your most experienced architects and platform experts end up spending their time on resource coordination, status updates, and tweaking slide decks instead of doing what you actually hired them for. You brought them in to understand your business and design solutions that move the needle. Instead, a chunk of their week goes to operational overhead.
Meanwhile, a team of administrators is doing repetitive configuration work that, while necessary, doesn't require deep knowledge of your organization. You're paying for strategic talent, but a good portion of their energy is going somewhere else entirely.
Here's what I've seen shift when you bring purpose-built AI tooling into ServiceNow delivery. Not as a buzzword, but as a genuine part of the workflow.
Take catalog item creation. This is traditionally a volume game. You gather requirements, you assign admins, and they configure items one by one. It's straight forward work, but it's time-intensive and it scales linearly. Twice the catalog items means roughly twice the effort.
With the right AI tooling, catalog item creation can be fully automated. Not partially. Not "AI-assisted with human review at every step." Fully automated, with human oversight focused on quality and business logic rather than manual data entry. That frees up your team to focus on the things that actually require human judgment, like whether the catalog design reflects how your employees actually work.
Now consider custom-scoped app development. Traditionally, this requires an architect to design the solution and multiple technical consultants to build it out. It's skilled work, and the architect often becomes a bottleneck because they're splitting time between design decisions and managing the build team.
AI tooling changes the ratio. When architects have access to tools that accelerate development, they can deliver the same integration with a smaller team in a fraction of the time. The architect stays focused on architecture. The tools handle the heavy lifting that used to require additional hands.
I'm not saying that large implementation teams are never the right call. Complex enterprise transformations still require experienced people, deep platform knowledge, and strong project governance.
But I do think the way you evaluate partners is shifting. Here are a few questions worth asking your next ServiceNow partner:
"How does your team actually use AI in delivery?" If the answer is vague or limited to "we use Now Assist," dig deeper. The partners who are genuinely AI-enabled have built internal tooling and workflows that change how work gets done, not just how it gets described in proposals.
"What's the ratio of senior architects to junior resources on my project?" An AI-enabled partner should be able to put more senior talent on your engagement because they're not relying on volume staffing to get the work done.
"Where does your team spend its time?" The answer you want to hear is: understanding your business, designing solutions, and ensuring quality. Not managing spreadsheets, coordinating resources, and configuring items by hand.
The real promise of AI-enabled consulting isn't fewer people. It's better-utilized people. It's your architect spending their day understanding your HR service delivery challenges instead of managing a build team. It's getting to production faster because the repetitive configuration work isn't holding up your timeline.
The consulting model isn't broken beyond repair. But it is ready for an upgrade. The partners who figure this out first will deliver better outcomes, faster. And the ones who don't will find themselves competing on the only thing they have left: head count.