Every product roadmap conversation with a technology vendor now runs through one filter that has nothing to do with the roadmap itself: does the company have an AI story that a buyer's finance team would actually underwrite.
Forrester Research just gave that gut check a formal structure. Its newly introduced AI Disruption Model evaluates 17 technology and service categories, spanning more than 200 individual markets, against nine factors including AI substitutability, labor intensity, and switching costs.
The finding that should reorder tech vendor strategy conversations this quarter is not which markets grow. It is how few of them do, and what that scarcity means for everyone else.
Only Three Categories Get an Unambiguous Green Light
According to the research, infrastructure providers such as cloud platforms, data centers, and storage; data and AI providers spanning models, platforms, and governance tooling; and cybersecurity and identity providers covering zero trust and AI agent security are the only three categories Forrester places in the clear growth column.
Everything else in the 17-category framework faces some combination of transformation pressure or outright disruption as enterprises shift from AI experimentation to production-scale deployment.
Forrester's Craig Le Clair puts it plainly: no market is exempt from an AI overhaul, and the gains are landing unevenly across the landscape.
The Disruption Exposes Service Provider's Worst Quarter
Transformation services, technology implementation, software development, creative services, localization, and training are the categories facing the steepest pressure, as AI substitutes for coding, content creation, translation, and other tasks that have historically depended on billable human expertise.
These are not niche categories. They represent a meaningful share of the professional and technology services economy, and Forrester's model treats them as structurally exposed rather than disrupted only at the margins.
If your tech firm sits inside one of these IT service categories and cannot point to a differentiated AI capability, the model is describing your near-term reality, not a hypothetical one.
Reshaped Value is Not the Same as Safe
Business applications, governance and compliance, process automation, customer experience, and marketing technology land in a middle category Forrester describes as reshaped rather than displaced.
Embedded workflows, regulatory requirements, and switching costs buy these vendors time that the disrupted categories do not have. That grace period is not permission to stand still.
Fellow Forrester analyst Ted Schadler frames the real challenge as understanding how AI changes the economics of a market, not just where AI is technically capable of operating.
Tech vendors in this middle tier that treat their AI roadmap as a feature checklist rather than an economic repositioning will still lose the account, just more slowly than vendors with no AI story at all.
What a Missing AI Narrative Actually Costs
This is where the model has teeth for vendor leadership specifically.
A vendor without a credible AI-related offering is not simply behind on a feature; it is misaligned with the primary lens buyers now apply to every renewal and every competitive evaluation.
Enterprise customer procurement teams have started asking AI-specific diligence questions before technical evaluation even begins. A vendor with no answer is effectively asking a buyer to underwrite another budget cycle without the productivity story its competitors can already tell.
That is a difficult position to hold even in a durable, high-switching-cost category, and an untenable one in a disrupted category like B2B SaaS offerings.
Four Moves Worth Making Before the Next Renewal Cycle
Start by using a framework like this one, or an equivalent built internally, to locate your own category honestly rather than optimistically, since most tech vendor leadership teams overestimate how defensible their current position really is in practice.
Next, resist the instinct to bolt AI features onto an existing product narrative and call it a strategy, because buyers can tell the difference between an AI wrapper and an AI-native economic case within a single sales cycle.
Then, put the harder dollar into data, workflow, and trust infrastructure rather than only the model layer, since Forrester's own findings suggest the durable value creation is concentrating there.
Finally, if your product or service category sits closer to the disrupted end of the spectrum, treat partnership and platform strategy as seriously as product strategy, because an organic AI development timeline may not survive the window this research describes.
Tech vendors that move on all four fronts now will still have a growth story to tell in the next planning cycle. The ones waiting for more certainty will be negotiating from a position the market has already priced in.
Key point: enterprise customer decision makers are totally focused on an AI investment that helps them achieve their desired business outcome. Vendors who continue to create their value proposition around product or service feature/function drivel will not be credible in those AI solution considerations.