Observed Signal · Aug 19, 2026 · Market Signal · Source: Forrester · Impact: 4/5
Forrester Introduces AI Disruption Model To Assess AI’s Impact On Technology And Service Markets
With AI widening the divide across tech products and services, the model helps leaders identify the markets most likely to accelerate, transform, or face disruption According to Forrester’s(Nasdaq: FORR)AI Disruption Model,unveiled today, advancements in AI are disrupting technology markets at an unprecedented pace — enhancing the value of certain products and services while making others increasingly vulnerable to [...]
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AI Reshapes Software Landscape: 'Wartime' for Tech Investors
At Morgan Stanley's Tech, Media and Telecom conference, David Chen, head of global technology investment banking at Morgan Stanley, described the current software landscape as "wartime, not peacetime," arguing AI is reshuffling winners and losers in enterprise software. Investors are now asking whether AI benefits or threatens a company's core business rather than focusing on efficiency gains. Chen distinguished deterministic software (payroll, invoicing) that retains a moat from software that primarily organizes public data, which faces greater risk. He highlighted cybersecurity as a clear AI beneficiary and flagged next-generation semiconductors and systems addressing connectivity, compute, and energy bottlenecks. CNBC producer Jasmine Wu and Box CEO Aaron Levie were also cited; Levie suggested agents may become the primary customer base for surviving software.
AI's Biggest Opportunity: Creating New Value
The article argues that while most organisations use AI (88% per McKinsey), only a small share (6%) see significant enterprise-wide impact because companies mainly apply AI to existing tasks rather than rethinking business models. Only 23% of generative-AI users have redesigned workflows for the technology. The author contrasts a 'factory' (efficiency) mindset with a 'laboratory' (experimentation and effectiveness) mindset and recommends marketing operations lead experimentation to discover new revenue models. Examples include Pieter Levels' portfolio of experiments generating sizable monthly revenue and IKEA’s chatbot 'Billie', which resolved 47% of inquiries, triggered reskilling of call-centre staff into design advisers and produced €1.3 billion in new revenue in 2022. The piece emphasises deliberate, low-cost experimentation to move organisations into higher-value AI stages.
AI Raises the Floor — Discovery Unlocks Durable Value
Gale Robins (UX Collective) argues that most organizations are using AI to accelerate existing work (productivity) but are not realizing durable value because they are not changing the questions they ask during discovery. Citing McKinsey’s 2025 State of AI and an April 2026 McKinsey Quarterly model, the article summarizes three waves of AI value — productivity, differentiation, and transaction-cost reduction — and says durable returns come from the latter two. Empirical research by Brynjolfsson, Li, and Raymond is highlighted showing AI raised average productivity by 14%, with novice workers gaining ~34% while experienced workers saw little improvement. The piece urges teams to treat AI as a force that reshapes what is worth building (framing judgment) rather than only a tool to do existing work faster.
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