How SaaS Founders Can Use Isenberg's AI Scanner
For SaaS founders with existing products · Based on Greg Isenberg AI Opportunity Scanner
// TL;DR
If you're a SaaS founder with an existing product, the Greg Isenberg AI Opportunity Scanner helps you determine whether your product is at risk of being commoditized (the SaaS Graveyard), how to pivot from Vertical SaaS to Vertical AI to capture a 10x larger market, and whether your pricing model should shift from per-seat to outcome-based. Use it when revenue is plateauing, when AI tools are encroaching on your feature set, or when you're considering a strategic pivot. The framework gives you a concrete 12-step workflow to assess risk and identify your best move.
Is your SaaS product in the graveyard?
Greg Isenberg identifies a clear category of software products that AI will kill: generic CRMs, basic analytics dashboards, template marketplaces, scheduling tools, and basic customer support chatbots. These are the SaaS Graveyard — products where agents can natively replace the entire value proposition.
Run your product through the graveyard checklist honestly. If your product is generic (not built for a specific vertical), has no proprietary data moat, and charges per seat while agents increasingly do the work, you're in danger. The good news is the Scanner gives you three pivot options: become a vertical workflow tool, add a proprietary data or network moat, or pivot to an agent company that sells outcomes instead of software.
A scheduling tool for general use is a graveyard product. A scheduling tool built specifically for home care agencies that uses agents to handle rebooking, reminders, no-show follow-up, and caregiver matching — priced per confirmed appointment — is a Vertical AI business tapping a labor P&L.
Should you switch from seat-based to outcome-based pricing?
If AI agents in your product are doing the work humans used to do, charging per seat is leaving money on the table and capping your market. Seat-based pricing captures IT budget. Outcome-based pricing captures labor budget, which is 10x larger.
The Seat→Usage→Outcome framework makes the decision straightforward. Ask: what result does my customer actually care about? If you're a legal tech SaaS, the customer cares about contracts reviewed, not seats filled. If you're a support platform, they care about tickets resolved. Price the outcome.
Gartner projects seat-based pricing will decline from 21% to 15% of enterprise SaaS, while outcome-based pricing rises to 40% by 2030. Moving now means capturing the premium before the market commoditizes your seat-based model.
How do you pivot from Vertical SaaS to Vertical AI?
The pivot has three steps. First, narrow your focus to a specific vertical if you haven't already — pick the most boring, legacy-process-heavy industry your product touches. Second, add an agent layer that performs the work your customers currently hire humans to do. Third, restructure pricing around outcomes delivered by those agents.
Design your Ghost Team Org Chart: map which functions — sales outreach, customer support, onboarding, analytics — can be handled by agents. Keep human judgment for creative direction, relationship escalation, and edge cases. The target operating model is an ambient business where you check in every few days.
Validate the pivot using Micro Monopoly Math: can 100 customers in your narrowed niche, paying for outcomes at your new price point, generate meaningful profit with agent-run operations? If yes, you have your path. If not, adjust the niche, the outcome, or the price.
What should you do this week?
Audit your product against the SaaS Graveyard checklist today. Identify your narrowest, most valuable vertical. Run the Micro Monopoly Math on an outcome-based pricing model for that vertical. If the math works, use the 1-Hour Company Stack to prototype the agent-powered version and test it with your existing customers. The asymmetric window is estimated at 12–24 months — every week of delay is a week competitors gain.
// FREQUENTLY ASKED QUESTIONS
How do I know if my SaaS product will be killed by AI?
Run it through the SaaS Graveyard checklist: is it a generic CRM, basic analytics dashboard, template marketplace, scheduling tool, or basic chatbot? If it's generic with no vertical focus, no proprietary data moat, and seat-based pricing while agents increasingly do the work, it's at high risk. The escape routes are vertical specialization, proprietary data or network moats, and pivoting to agent-delivered outcomes.
Can I keep seat-based pricing on my SaaS product?
Only if your product is genuinely a human-operated tool where the user performs the work. If agents are doing the work that humans used to do, seat-based pricing means you're capturing IT budget instead of the 10x larger labor budget. Isenberg's framework and Gartner projections both point to outcome-based as the direction — 40% of enterprise SaaS by 2030.
What's the fastest way for a SaaS founder to test Vertical AI?
Pick your narrowest, highest-value vertical. Add an agent layer to one core workflow that currently requires human labor. Price it per outcome delivered. Test with 10 existing customers this week. If they pay for outcomes and the agents deliver, you've validated the pivot without rebuilding your entire product.