Forrester’s AI Disruption Model reframes vendor strategy: only three categories show clear growth, many services face structural pressure, and buyers now screen vendors on AI economics before technical fit.
Only three vendor categories—infrastructure, data/AI platforms and tools, and cybersecurity/identity—are placed in clear growth by Forrester’s AI Disruption Model.
Four practical moves—honest category mapping, economic-focused AI narratives, investment in data/workflow/trust infrastructure, and serious partner strategies—reduce renewal risk.
Forrester introduced an AI Disruption Model that evaluates 17 technology and service categories across nine factors such as AI substitutability, labor intensity, and switching costs. The model's core implication for tech vendors is straightforward: procurement and finance teams now apply an AI economic lens to buying decisions. A vendor's survival depends less on technical capability or roadmap items and more on whether its AI story can be underwritten by a buyer.
Forrester identifies three categories that receive an unambiguous green light.
Categories facing disruptive pressure
Reshaped categories: time but no immunity Business applications, governance and compliance, process automation, customer experience and marketing technology sit in a middle tier that Forrester calls reshaped. Embedded workflows, regulatory baggage and switching costs grant vendors a window to adapt. That window is not permanent. Vendors that treat AI as a cosmetic feature list rather than a repositioning of economics will still lose accounts, albeit more slowly than those with no AI story.
Four moves to take before the next renewal 1) Map your category honestly. Use Forrester's framework or an internal equivalent to identify where your product or service sits along the disruption spectrum. Optimism biases are common and costly. 2) Build an economic narrative, not a feature wrapper. Buyers distinguish between AI-marketed features and AI-native economic cases in a single sales cycle. Make the value measurable in dollars, headcount, throughput or risk reduction. 3) Invest beyond models. Allocate budget to data infrastructure, workflow integration, and trust/governance layers. Forrester's findings show durable value concentrating there rather than at the model layer alone. 4) Treat partnerships as product strategy when necessary. For vendors in highly exposed categories, an organic AI development timeline may miss the market window. Platform and partnership strategies can preserve account access and accelerate delivery.
The Boring Truth About AI Everyone and their grandmother is talking about AI, and it’s just not interesting anymore. Let’s face it, once a technology topic becomes kitchen table conversation fodder, tech pros grow weary of discussing it. Yet, every vendor has a “game-changing” solution you should buy, every staffing fi
why-telling-your-story-matters-in-the-age-of-ai
AI is no longer the competitive advantage. The post Every Agency Says They’re Using AI Today. So How Can Businesses Tell Who’s Actually Delivering Results? appeared first on DollarsAndSense.sg .
Simply adding AI language to your brand does not automatically make your company more relevant or more compelling.
Sponsored content Artificial Intelligence has quickly moved from future concept to boardroom priority. Across Ireland, organisations are exploring how AI can improve productivity, automate processes, enhance customer experiences and unlock new insights from their data. For many resellers, the conversation naturally sta
Like us, you’ve probably noticed that over the past two years, most discussions about AI in manufacturing have focused on what LLMs can do for engineers, planners, and other knowledge workers. Vendors have showcased copilots that summarize documents, answer questions, and generate content. Those capabilities matter, bu
Loading more related stories...
Open the app view to save this story, compare related coverage, and continue from the same source.