The best quarter your SE team has ever had might be happening right now, for reasons that are temporary.
AI is making SEs extraordinary. RFP responses that used to take days come back in hours, with more depth and precision than before. Mutual action plans get built from call transcripts. Discovery questions get sharper. Meeting summaries arrive before the customer has even left the parking lot. An SE today can cover territory that would have required two people two years ago, and the work looks better than it ever has.
The edge is real. The reason it feels so large, though, is worth understanding clearly.
The gap is wider than it looks
The advantage SEs have right now isn't just that AI is powerful. It's that the advantage is lopsided. Most of the organizations buying complex technical software, particularly in industries where technology is a tool rather than the product itself, like retail, manufacturing, and financial services, haven't adopted these tools yet. When we fire back a comprehensive RFP response with AI-assisted depth, the team on the other side is still reading it by hand. When we follow up a discovery call with precise, tailored questions within the hour, they're working from handwritten notes.
We are years ahead in our use of AI and they are largely still operating manually. That gap makes our work look even better than the tools alone would explain. We can handle more accounts, move faster, and appear more prepared than the buying process seems to expect.
But we are designing solutions for a future that has at most a six-month shelf life.
The future is here, just not evenly distributed yet
When AI reaches the buyer side of the table, the math changes.
A procurement team with capable AI tooling can parse a 200-page RFP response in minutes. They can extract every qualified claim, cross-reference it against their evaluation criteria, identify the gaps, and come back with ten pages of precise follow-up questions your team wasn't expecting. The enterprise buyer who used to spend three weeks sorting through vendor submissions will soon spend an afternoon doing it more thoroughly than they ever could before.
The SE who used AI to go wider, covering more accounts than would have been possible otherwise, will be the most exposed when this shift arrives. Speed and breadth that worked beautifully against manual buyers won't hold up the same way against AI-assisted ones. The customer who used to be impressed by a fast, detailed response will simply expect it. And then they'll dig deeper than we prepared for.
Waiting carries its own risk
The obvious response is to extract maximum value from the asymmetry while it exists. Cover more accounts, move faster, take every advantage available, and worry about the new world when it arrives.
That logic has a real problem, and a similar situation in a different context makes it clear.
When I ask senior executives what metrics they track and report to their board or leadership team, the ones who say "they haven't asked for any, so we don't report any" believe they have it easy. In practice they are rolling the dice of disaster. Because the moment someone upstream decides to hold them accountable, whatever metrics get prescribed to them might be irrelevant to how they actually run their business, impossible to move in the timeframe given, or simply a poor measure of the work they do best. The executives who are protected are the ones who got there first: they picked their own metrics, made them meaningful, and started reporting them voluntarily before anyone asked.
Waiting for customers to develop their own AI buying practices carries exactly the same risk. When buyers get there on their own, the tools they choose, the frameworks they build, and the criteria they use to evaluate vendors will be shaped by whoever got to them first. That might be a competitor. It might be a consultant. It might be a template they found online that happens to favor the wrong things. If we say and do nothing, we have no influence over any of it.
Get there first
The better play is to be the ones who hand buyers their tools.
This is the same move as writing a customer's RFP when the relationship is strong enough. In trusted engagements, a vendor will sometimes offer to draft the requirements document for a customer who lacks the internal expertise or bandwidth to build it well. The customer knows the vendor has a perspective. They say yes anyway, because a well-structured RFP is genuinely hard to write and the vendor will make it thorough and comprehensive. Both sides benefit. The vendor benefits a little more.
SEs are in a unique position to do the same thing with AI adoption. We understand the products deeply. We know what a good technical evaluation looks like. We know which questions lead to productive conversations and which ones create noise. We can use that knowledge to build tools that genuinely help customers and that frame the evaluation in terms that reflect how we want to be measured.
In practice this could look like a few things. A maturity self-assessment that helps a prospect understand where they actually are, identify their real gaps, and arrive at a first conversation with more informed requirements than they would have built on their own. A prompt-based RFP generation skill built from their own answers to a structured set of questions, so the RFP they write reflects their real needs and maps cleanly to how you evaluate fit. A vendor scoring rubric that gives them a framework for comparing technical capability, built around criteria that honest products perform well on.
None of these are manipulation. They are useful. Customers benefit from having them. The fact that you helped build them means you already understand how they will be used, and you have designed your process around answering them well.
The window is the work
The asymmetry that exists today is an opportunity, but not the one most SE organizations are treating it as. The easy read is: use AI to go wider while buyers are still behind. The better read is: use this window to build the frameworks and tools that put you on the right side of buyer AI adoption when it arrives.
The teams that do this now will be the ones who are ready when the Super Buyer shows up. They will have already shaped what that buyer uses, what they ask, and how they evaluate. The teams that waited will be responding to a process they had no hand in building.
Skate to where the puck is going.