Research and advisory firm Forrester has now officially introduced its AI Disruption Model, an analytical tool designed to measure how artificial intelligence is transforming world technology markets. The two principal reports, The Forrester AI Disruption Model: How AI Disrupts Or Accelerates Technology And Service Markets and The Forrester AI Disruption Model: Category Analysis, elaborate on these results. They show that the rapid developments in generative and agentic systems have caused a significant increase in demand for platform services enabling AI while simultaneously putting traditional, skill-based professional services at high risk of being replaced.
As the large businesses of the world move from small-scale AI trials to enterprise-level self-driving deployments, the new research model will enable leaders to obtain insights that are based on solid data and so they will be well-equipped to deal with market changes, valuation fluctuations, and the reorganization of their operations.
Highlights for Each Service and Technology Segment
The Forrester AI Disruption Model assesses 17 major technology and service categories covering over 200 different sub-markets. The analysis looks at ten central operational criteria to ascertain whether specific segments may accelerate disrupt reshape, or stay mostly as they have always been: substitutability with AI, labor intensiveness, support of agentic workload, commercial models, advantage in data and trust, focus on AI of R&D investments, regulatory challenges, asset intensiveness, and switching costs.
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The model highlights three major industry shifts:
High-Growth Trajectory for AI Infrastructure: Infrastructure platforms (cloud computing, physical data centers, and storage), data and AI enablement tools (foundational models, development platforms, governance solutions), and cybersecurity architectures (including Zero Trust models and agent security layers) represent the only three categories positioned for universal, sustained growth.
Severe Disruption in Labor-Heavy Knowledge Work: Service sectors heavily reliant on manual expertise—such as technology implementation, digital transformation consulting, custom software engineering, creative marketing, content localization, and corporate training—face structural pressure as autonomous AI agents handle coding, translation, and asset generation.
Evolutionary Reshaping of Enterprise Software: Core enterprise applications, including process automation platforms, business software suites, compliance tools, marketing technology, and customer experience solutions, will be reshaped rather than outright replaced. High switching costs, regulatory frameworks, deep workflow integrations, and the need for trustworthy orchestration safeguard their operational relevance.
“Every technology and service market is facing an AI overhaul,” said Craig Le Clair, vice president and principal analyst at Forrester. “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.”
“The challenge for technology and service providers is not simply understanding where AI is advancing but how it will reshape the economics of their markets,” said Ted Schadler, vice president and principal analyst at Forrester. “Forrester’s AI Disruption Model gives providers a practical framework to evaluate where AI is likely to accelerate their growth, transform their market dynamics, or replace existing sources of value. Providers can use the model to anticipate change and prioritize investments to thrive in the AI era.”
Strategic Framework for Technology and Service Leaders
By applying the AI Disruption Model, chief technology officers, IT decision-makers, and software vendors can proactively diagnose vulnerabilities across their portfolio offerings. The predictive tool equips organizations to reallocate research and development capital toward high-demand infrastructure layers while modernizing legacy business software before traditional revenue streams decline.