Something I've noticed working with scaling B2B SaaS and tech businesses: when AI starts threatening growth, the response is often aimed at the product.
New AI features. A repositioned roadmap. More functionality. The instinct is understandable. If AI-native competitors are gaining ground, surely the answer is to close the product gap.
But in most cases I see, the product isn't where the primary gap is. The gap is commercial. The GTM strategy, the messaging, the pricing, the sales motion, these were all built for a market that AI has already fundamentally changed. And while founders are staring at the roadmap, their buyers have quietly moved on.
I've written in the previous article about how most growth problems are actually clarity problems. This is a specific and urgent version of that same challenge. AI isn't just disrupting products and categories. It's disrupting the conditions under which buyers find, evaluate, and choose vendors, and most go-to-market strategies haven't caught up.
Markets evolve faster than most strategies, the question is how quickly we can adapt
The pace of change is worth sitting with for a moment.
Enterprise spending on generative AI grew 3.2x in a single year, from $11.5 billion in 2024 to $37 billion in 2025, according to Menlo Ventures' State of Generative AI report. AI-referenced deals comprised 72% of all SaaS transactions in 2025, a 12x increase since 2018, according to Software Equity Group's 2026 Annual SaaS Report. High Alpha's 2025 SaaS Benchmarks Report puts it plainly: building with AI is no longer a differentiator, it's the baseline. Intelligence is now infrastructure.
The competitive window has compressed so dramatically that what was a 12-month product advantage two years ago is a matter of weeks today. And here's what makes that genuinely dangerous for scaling businesses: it creates pressure to ship more, add more, and move faster, exactly the conditions under which product quality erodes and customer value gets diluted.
Meanwhile, the buying journey for software has structurally changed. According to a G2 survey of over 1,000 B2B software buyers conducted in March 2026, 71% now start their vendor research inside AI chatbots, not Google, and 69% chose a different vendor than they had originally planned based solely on what an AI recommended, with one in three buying from a company they had never previously heard of. The vendor shortlist is being formed in conversations your sales and marketing teams will never see. Yet only 14% of B2B SaaS marketers have a mature strategy for AI search visibility. The gap between where buyers are looking and where most SaaS businesses are investing their commercial energy has never been wider.
Three traps I see scaling businesses falling into
I don't think there's a single way founders misread the AI threat. In my experience, there are three compounding failure modes and most businesses I work with are caught in more than one simultaneously.
Trap one: pricing and value proposition erosion, the one no one sees coming
This is the trap I find founders most blind to, and in my view the most dangerous.
When AI commoditises a category of task, for example copywriting, data analysis, workflow automation, customer support, it doesn't just create new competitors. It resets the perceived value of everything in that category. Buyers who once paid comfortably for a tool that automated a process they can now get 80% of the way through with a fraction of the cost, start asking a question they never asked before: why are we paying this much for this?
The pricing and value proposition that worked in 2022 may have been quietly undermined, not because a product got worse, but because the market's frame of reference shifted around it. ICONIQ's research describes AI-native competitors absorbing budget that once defaulted to incremental seat expansion, with customers recalibrating what value means faster and with more options than at any point in the last decade.
It goes further than competitive pressure. Gartner estimates AI agents could replace 35% of point-product SaaS tools by 2030. And multiple SaaS vendors confirmed in their Q4 2025 earnings that AI tools are already giving buyers the leverage to negotiate better terms for the same level of service, compressing the per-seat economics that have underwritten SaaS pricing models for two decades.
The question I ask clients first isn't "how does your pricing compare to competitors?". It's "does your value proposition still land the way it did, and if not, what changed in the buyer's world that made it land differently?" Most haven't formally asked that question since they set their original pricing. That's the gap.
Trap two: a go-to-market motion built for a buyer who no longer exists in the same form
Forrester's research shows 89% of B2B buyers now use generative AI for self-guided research before engaging a vendor. Buyers are arriving at conversations with a shortlist already formed, a point of view already established, and questions that are sharper and more specific than they were two years ago.
If your messaging was written to educate a buyer who needed to be guided through the category, it now lands with someone who knows as much as your sales team, and your pitch feels like it's explaining things they've already figured out. Gartner's latest research confirms that B2B buying is becoming more digital, more self-directed, and more AI-influenced, with many buyers preferring to progress through most of the buying journey before a sales rep ever enters the picture.
This has a direct implication for where you can invest. Pouring budget into lead generation for a buyer who has already formed their shortlist independently and didn't put you on it is one of the most expensive mistakes a scaling SaaS business can make right now. The question isn't only who you're targeting. It's whether your brand is present and credible in the places buyers are forming their views before they contact you.
Which connects directly to the sales motion problem. Gartner's 2025 survey of 646 B2B buyers found 67% prefer a rep-free buying experience, up from 61% the prior year, still accelerating. And 39% of B2B buyers are now willing to spend over $500,000 through a purely digital, self-serve process. The businesses expanding their sales teams to solve a pipeline problem rooted in a misaligned GTM motion are making an expensive bet on a model the market is incrementally moving away from.
Trap three: mistaking AI product activity for AI product value
This is where I want to offer a perspective that cuts against the pressure founders are under.
The race to add AI features is real and understandable. But in that race, something important gets lost: the discipline to ask whether each addition genuinely deepens the value your product delivers to the customer it was built for or whether it's noise that makes your product harder to use and your value proposition harder to articulate.
Feature bloat is a well-documented killer of SaaS products. When a product tries to do everything for everyone, it loses its core identity. Its value proposition becomes muddy and hard to communicate. The very features that originally attracted customers become harder to find beneath layers of additions that nobody asked for. AI is now accelerating this risk specifically - the ability to generate and ship new feature ideas faster than ever creates pressure to confuse volume with value.
The SaaS companies that will win this period are not necessarily those with the most AI in their product. They are those with the clearest answer to what problem their product solves and the discipline to use AI to solve that problem more deeply, more intelligently, and more elegantly, not just more extensively. Proprietary data that compounds, integration depth that creates structural switching costs, product intelligence that genuinely learns from customer behaviour: these are the AI-powered advantages that are difficult to replicate. A feature list is not.
Where real AI impact actually comes from
McKinsey's State of AI 2025 has a finding that deserves far more attention than it gets in founder conversations. Of 25 attributes tested, the single factor with the biggest effect on an organisation's ability to see EBIT impact from AI is the fundamental redesign of workflows, not the addition of AI features. Only 6% of organisations qualify as AI high performers generating 5%+ EBIT impact, and what separates them is not how much AI they've added but how creatively they've rethought how their business runs.
I think the same principle holds in the product itself. The businesses using AI to genuinely rethink how their product creates value for the customer, including how customers onboard, how quickly they reach meaningful outcomes and how intelligently the product adapts to their behaviour, are building something defensible. The businesses using AI to accelerate feature output are building a more complex product that may be easier for a competitor to replicate tomorrow than it was yesterday.
The question isn't how much AI is in your product. It's whether the AI you're building with is making your product measurably better for the customer it exists to serve.
A different kind of urgency
The AI disruption conversation in most SaaS businesses is happening in the product team and the boardroom. It needs to be happening with equal urgency in the commercial function, and with equal rigour in the product strategy.
The companies I watch falling behind aren't failing because their product lacks AI. They're failing because their go-to-market was built for a world that has moved on, and their product strategy has confused activity with value.
The window to adapt is open. And for those willing to ask harder questions about their commercial strategy, not just their product roadmap, the opportunity ahead is significant.
Sources:
Menlo Ventures, "2025: The State of Generative AI in the Enterprise" (survey of ~500 US enterprise decision-makers)
Software Equity Group, "2026 Annual SaaS Report / AI in SaaS Survey" (survey of ~450 SaaS CEOs, PE and strategic buyers)
High Alpha, "2025 SaaS Benchmarks Report"
McKinsey, "The State of AI 2025: How Organizations Are Rewiring to Capture Value," mckinsey.com (primary report)
ICONIQ, "2026 State of AI Bi-Annual Snapshot"
Forrester, "The State of Business Buying 2024" (survey of 16,000+ global buyers)
Forrester, "Predictions 2025: Younger Business Buyers and GenAI Will Upend The Status Quo," forrester.com
Gartner Newsroom, "Gartner Sales Survey Finds 67% of B2B Buyers Prefer a Rep-Free Experience," gartner.com, March 2026 (survey of 646 B2B buyers)
Gartner, “AI agents replacing 35% of point-product SaaS tools forecast” (via Grey Journal 2026)
Levera Partners, "AI's Implications for SaaS in 2026: Why Moats Matter More Than Ever," leverapartners.com