Forrester Maps AI Disruption Across Technology Markets
Forrester introduced its AI Disruption Model on August 19, assessing AI's likely effect across 17 technology and service categories containing more than 200 markets. The firm identifies infrastructure, data and AI, and identity and security as broad growth areas, while reporting greater exposure for labor-intensive services including software development and technology implementation.
Forrester introduced its AI Disruption Model on August 19, assessing AI's likely effect across 17 technology and service categories comprising more than 200 markets. The research firm categorizes markets by whether AI is likely to accelerate, disrupt, reshape, or have limited impact on them, according to its news release.
The model identifies infrastructure, data and AI, and identity, access, and network security as the three groups broadly positioned for growth as enterprises expand AI applications and autonomous-agent deployments. Forrester's release lists cloud platforms, data centers, storage, AI models, AI platforms, data management, governance, Zero Trust, and AI-agent security among the relevant markets.
By contrast, Forrester reports that labor-intensive knowledge-work industries face the greatest disruption, including transformation services, technology implementation, software development, creative services, localization, and training. The Register reported that Forrester singled out application development and software tooling as being "directly in the path of genAI-code development."
"Every technology and service market is facing an AI overhaul," Craig Le Clair, Forrester vice president and principal analyst, said in the firm's release. "Our research shows that AI's benefits will not be distributed evenly across technology markets. Only markets in three categories - infrastructure; data and AI; and identity, access, and network security - are broadly positioned for clear growth. Technologies in the other categories will be forced to adapt."
How the model evaluates markets
According to Forrester, the framework weighs AI substitutability, labor intensity, support for agentic workloads, commercial models, data and trust advantages, AI-focused R&D investment, regulatory friction, asset intensity, and switching costs. IT Brief similarly reported that the resulting classifications indicate a fragmented market transition rather than a uniform outcome across software and services.
The model's distinction is consequential for practitioners because it separates tasks AI can directly substitute from products whose value is tied to data, governance, integration, security, or deeply embedded workflows. In comparable enterprise technology transitions, those characteristics often determine whether AI changes a product's interface and cost structure or replaces a discrete unit of human work.
Enterprise software is not treated as a single category
Forrester does not characterize all enterprise software as facing direct displacement. Its release states that business applications, governance and compliance, process automation, customer experience, and marketing technology are more likely to be reshaped.
The Register quoted the report's rationale: embedded workflows, regulatory requirements, switching costs, and demand for data, orchestration, governance, and trust capabilities can sustain these categories' relevance even as AI changes workflows and user experiences. That is a narrower conclusion than the "SaaSpocalypse" narrative discussed in Forrester's accompanying blog, which argues that seat-based revenue compression is only one of several disruption factors.
For ML engineers and platform teams, the findings place particular emphasis on the operational layers around models: data management, governance, identity, and security. As organizations deploy agentic systems, these layers govern access, data handling, auditability, and integration with existing business systems, areas that Forrester places among the markets with clearer growth prospects.
Services and development work face direct substitution pressure
Forrester attributes the higher exposure of skills-based services to AI taking on tasks traditionally performed by people, including coding, content creation, and translation. The Register reported that the firm expects direct AI substitution to reduce core implementation work in IT services.
The report does not establish that AI will eliminate every role or product within the affected categories. Instead, its market-level framework highlights that exposure differs according to task substitutability and the surrounding technical and commercial constraints. For teams buying development tools or external implementation services, that distinction makes workflow-level evaluation more informative than broad claims about AI replacing software or services wholesale.
Key Points
- 1Forrester evaluates more than 200 markets, finding that AI disruption varies by substitutability, labor intensity, trust, and switching costs.
- 2Software development and technology implementation face greater reported pressure because AI can substitute for coding and other human-performed knowledge-work tasks.
- 3Comparable enterprise transitions often preserve products anchored in governance, embedded workflows, data, security, and integration even as AI reshapes interfaces.
Scoring Rationale
Forrester's market framework is notable for organizations assessing AI's effects on development, IT services, enterprise software, and supporting infrastructure. It is an analyst research release rather than a product launch or regulatory action, but its conclusions are directly relevant to technology procurement and platform strategy.
Sources
Primary source and supporting public references used for this report.
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