The Job Gets Bigger When the Team Gets Faster
AI is giving Solutions teams real time back. There are three ways to spend it. And doing nothing quietly costs you the most.
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We’ve used this stat before in previous issues of this newsletter, but it’s worth repeating. 88% of organizations claim they have adopted AI. 6% report it showing up on the bottom line. (McKinsey, The State of AI)
We stand behind what we said the first time, in the Modern Solutions Mandate: the tools are not what make the difference. You have to redesign the work before you layer AI on top of it, or all you have done is make the old process faster.
What is new is that we are starting to see the redesign pay off. One leader in our network cut POV prep from 2-3 days down to minutes once the workflow itself changed. There is real impact to be found with AI, but the next question is: what happens to that time that is saved?
It goes back to “high value work.” That’s what we all say. But not enough leaders are showing what that means in practice. So as teams find these efficiencies, what is the most valuable thing you can do with the time AI gives back?
Broadly, there are three ways to spend that time.
1) Hand it back as reduced headcount.
2) Expand coverage so the same team carries more.
3) Or point it at bigger, higher value work that grows what Solutions owns.
Your personal version might look a little different, but that’s the gist. What matters is that each one is a deliberate choice.
The reflex is to cut. The opportunity is to grow.
Let’s take each of these moves in turn.
Reduce headcount. It’s the lever some CFOs might reach for. Fewer people, same revenue, lower cost per deal. In a function that is genuinely shrinking, it can be the right call. But everything we are hearing says the job is getting bigger, not smaller.
Expand coverage keeps the remit where it is and asks each person to carry more of it. Same headcount, more deals per SE, a different coverage ratio. One Senior Director of Solutions Engineering at a content and knowledge repository platform described a small RFX team now clearing more than 500 questionnaires with AI support and no new hires.
Push upmarket points the same team at fewer, bigger, harder deals: more of the customer lifecycle, deeper strategic accounts, the technical problems only Solutions can own. This is the move that comes out of the moment with a larger mandate instead of a leaner team. It is also the hardest, because it means saying no to the volume you used to absorb.
Each rewires the function differently, and each carries a different political cost with your CRO, your CFO, and even your own team. The fastest way to tell which one you should be considering is to look at where your pipeline is already constrained. If deals are lost on price or timeline more than on a missing technical capability, the case is for pushing upmarket, not adding volume. If the constraint is coverage, too many deals and not enough qualified hands, expand is the honest answer.
The default outcome is not neutral.
When a Solutions leader doesn’t pick one of the three moves, the extra hours get absorbed and it feels like progress… until someone comes asking what that time saved actually did for the business.
Gartner recently published some research that put a fine point on the issue. Surveying 210 CSOs and senior sales leaders earlier this year, Gartner found that AI is saving sellers an average of 4.8 hours a week, and that 72% of sales organizations show low reinvestment of that time into higher value work. The organizations that do reinvest it are 2.2 times more likely to beat their customer growth goals and 3.1 times more likely to beat lead to opportunity conversion targets.
Hear us say, Solutions is not the sales org, but the same math is playing out for us as well. And the stakes aren’t any smaller. Dan Gottlieb, the Gartner analyst who led the study, put it well when he said: “AI is not the hero of this story, AI is the accelerant.” Productivity does not stall, he said, because reps forget how to sell or support. “It stalls because the system quietly caps them.”
We are seeing the SolutionExec version of the same pattern. At a recent roundtable on rewriting the SE playbook for AI native GTM, eighteen Solutions leaders compared notes across different companies and different stages of AI adoption. The one thing they had in common: not one of them was doing a smaller job than they were a year ago.
AI is creating efficiency, but that efficiency is quickly getting absorbed and not always strategically. More deals per SE without a coverage ratio change. More ad hoc requests the team says yes to because they technically have the bandwidth. More scope, but often none of it chosen.
A VP of Customer Solutions overseeing pre and post sales at a CMS platform named a sharper version of this problem. AI fluency is not evenly distributed across a team, and the SEs who picked it up fastest are the ones getting pulled into everything. It is the old rock star SE problem, except the skill gap that creates it is now AI. As they put it: “Certain sales reps don’t want to work with certain SEs. They want the one who’s doing all the really cool new stuff.”
Some leaders are refusing to let someone else decide where their team’s time goes. A Solutions leader at a network observability company described pushing back on sales reps who wanted their SEs to vibe code a stopgap feature the same week a prospect asked for it: “Sure, we could prototype something, but is it going to scale, who’s going to support it, what’s day two look like on all that kind of stuff.” And they aren’t wrong to ask. Saying no to work the team could technically deliver is how you keep the freed-up time from being spent for you.
To be clear: it’s not about doing less work, it’s about making sure your team is absorbing the right work. More activity has never been the same thing as more impact. The leaders getting this right are the ones making sure the capacity AI gave back goes to the harder, higher value problems, not just the next thing someone hands them.
Some leaders are not waiting for the CFO email to force the question. A Solutions Consulting leader at a corporate spend management fintech described building a cross functional joint operating plan before their team took on any AI driven pilot work, specifically so sales and the other functions involved already knew what supporting that work at scale would require: “We’re trying to tie it back to a joint operating plan. If we’re going to be doing something that we think brings value early on in the sales cycle, having their buy-in that when we start trying these things, they’re also going to be there to support how this becomes something that we can scale and grow and take to other customers.” They were not waiting to be handed a decision about what the extra capacity was for, rather they built the plan first.
While at ServiceNow, Jeff made a similar move. He told his CRO, sales ops, and CFO that his org would not ask for more headcount as AI took hold: “We’re not going to ask for more resources. We’re going to change what we do with what we have.”
Some leaders decide what the time is for. Others let the decision get made somewhere else, usually in a budget review they’re not in the room for. AI will give your team back the time, but the difference is whether you direct how that saved time is spent.
If your team is faster this year than it was last year and you cannot say in one sentence what that speed is for, someone else is about to decide for you.
Jeff and James
P.S. In case you missed it - Off The Record is back! The premier event for Solutions leaders is coming to the Bay Area on October 8. Applications are open at: solutionexec.com/offtherecord