Your Next Solution Engineer May Be AI

In this IMPACT Summit research spotlight, I sit down with John Grispon to explore a part of enterprise selling many assumed would be “last touched” by AI: complex, multi-stakeholder technical sales. John’s research shows the opposite—AI is already augmenting and accelerating the most painful parts of enterprise cycles, especially in solution engineering. He explains the two big use cases: in-the-moment expertise (instant answers to tough technical questions that normally stall calls) and the heavy preparation work in technical validation stages (custom demos, security questionnaires, RFPs, architecture diagrams). With SE-to-AE ratios often at 1:4 or worse, these bottlenecks slow every enterprise motion.

We then bring in four builders shaping this emerging category. Adil from Hey Sam shows how Gainsight used AI SEs to sell across five products—even after losing original SE talent from acquisitions—by putting “SE expertise in a box” and enabling multi-product conversations without dragging five humans into every deal. Manisha from Sifthub walks through how Sirion Labs unified scattered knowledge across SharePoint, Slack, Q&A banks, and deal notes into a single brain that powers agents for discovery, RFPs, battle cards, and competitive decks—cutting turnaround times by 60% and giving SEs their weekends back. Gerard from Vivun demonstrates how Coder’s team used an AI teammate (Ava) to handle the messy middle of deals—deal reviews, qualification logic, technical detail retrieval—allowing reps to spend 90% of their time actually talking to customers instead of assembling content from 12 tools. And Arjun from Docket shares how ZoomInfo scaled from 30 pilot users to 1,300 sellers using their AI SE, compressing response times from hours to seconds, raising win rates 12%, shortening sales cycles 10%, and increasing revenue per seller by 22%.

We close by stepping back: what does this mean for SEs, sellers, and CEOs? SEs shouldn’t fear replacement—the trust-building human work remains—but they must learn to wield these tools the way the last generation learned to wield Salesforce. For CEOs, AI SEs are a rare chance to accelerate pipeline already in motion, lift SE productivity by 40–60%, remove “let me get back to you” delays, increase coverage, and make every rep more confident and more capable. Enterprise selling may be the last frontier for AI—but it’s clearly happening now, and “first movers” are already pulling ahead.

00:00 — Why enterprise sales felt untouchable
Dave and John open with the assumption that enterprise, multi-stakeholder selling would be the last GTM motion AI could impact.

00:01:15 — Enterprise sales = fewer at-bats, higher pressure, more complexity
John frames why delays, friction, and technical blockers matter so much in long cycles.

00:02:28 — Two core use cases for AI in technical sales

1. Instant, real-time technical answers

2. Heavy-lift preparation during technical validation (demos, security questionnaires, RFPs)

00:03:42 — AE vs SE: how the partnership works
AEs orchestrate; SEs drive technical validation and credibility.

00:05:41 — The bottleneck: 4–6 AEs per SE
Scarcity, scheduling delays, and stalled deals set the stage for AI augmentation.

00:06:33 — The insight: this isn’t cost-cutting—it’s a growth catalyst
AI increases capacity, speed, accuracy, and meeting-to-meeting compounding.

00:08:12 — What AI can already automate
40–60% of SE tasks: discovery questions, technical demos, RFPs, solution designs, proposals, ROI analysis, handoff docs.

00:09:22 — Yes, this is happening today
Vendors have shipping products that customers are already using.

00:11:39 — “SE in a box” for multi-product companies
Gainsight’s challenge: five acquired products, SE expertise walking out the door.

00:13:51 — AI enabling multi-product selling without five humans
Reps and SEs can converse intelligently about products they aren’t experts in.

00:15:24 — Augment, don’t replace
SEs remain the trust layer; AI handles the menial, repetitive work.

00:17:46 — Enterprise SE work spans discovery → implementation
Buyers want depth early; SE workload is heavier than ever.

00:19:53 — Sirion Labs case: CLM, global teams, complex cycles
Huge deal complexity, multiple stakeholders, thousands of RFP questions.

00:21:10 — Unifying scattered knowledge into a searchable brain
SharePoint, Slack, Q&A banks, call notes, CRM—merged into one graph.

00:21:49 — Multiple agents across the deal lifecycle
Buyer IQ, RFP agent, answer agent, battle card agent.

00:22:26 — Results
60% faster turnaround, fresher content, SEs reclaim weekends.

00:24:07 — Focus: the messy middle of B2B sales
AI captures all context and expertise and shares it with everyone.

00:25:27 — Coder case: highly technical product, junior reps, 1:5 ratios
AI teammate Ava gives reps full product context and eliminates busywork.

00:26:18 — Ava handles deal reviews, qualification, context retrieval
Reps spend 90% of their time talking to customers instead of assembling artifacts.

00:27:30 — Human impact
Less fear, more confidence, and no more 2 a.m. pings to an SE.

00:29:37 — AI SEs already deployed for 12+ months
Thousands of active users across ZoomInfo, Demandbase, WhatsApp, Spotify.

00:30:44 — ZoomInfo case: from 30 → 1,300 sellers
Viral adoption by embedding into Slack, Teams, Chrome, and Zoom.

00:31:58 — Solving the data prep problem
Unifying structured + unstructured data into a sales knowledge lake.

00:33:12 — Results

• Response time: 5 hours → 3 seconds

• Sales cycle: 10% faster

• Win rate: +12%

• 3–6 hours saved per seller per week

• +22% revenue per seller

00:34:11 — Product evolution
Real-time “ride along” SE in Zoom; stealth mode widely adopted.

00:37:00 — The spectrum of AI SE tools
Task tools → content assistants → workflow enablers → strategic teammates.

00:38:06 — Should SEs worry?
No—SE trust and relationship work remain irreplaceable. But they must learn AI now.

00:40:00 — Advice to SEs early in career
Learn the craft, master relationship-building, and adopt AI as your “calculator.”

00:40:53 — Why CEOs should care
AI SEs accelerate pipeline, cut cycle time ~20%, remove friction, add capacity, and lift quality of execution.

00:42:14 — Scaling expertise without scaling headcount
SEs are expensive and scarce; AI gives every AE an expert at their elbow.

00:42:49 — The frontier moves fast
Capabilities will continue shifting rightward into strategic teammate territory.

00:43:34 — Closing
Thanking the vendors, previewing the report, and reiterating: recurring revenue isn’t just earned—it’s architected.