AI is undermining traditional software. But it is forcing companies to reinvent themselves.
The software sector is at a structural turning point, with the relative importance of traditional software steadily declining. Once the dominant segment in technology, software has lost market weight and investor confidence, with the IGV index (iShares Expanded Tech-Software Sector ETF) alone shedding around USD 1.5 trillion in market value year-to-date. This reflects growing concerns that enterprises may increasingly build solutions internally using AI rather than relying on external vendors. At the same time, SaaS (Software as a Service) growth has been slowing even before AI disruption, as cloud adoption matures and markets become saturated, reinforcing the idea that legacy software is entering a lower-growth, more commoditised phase.
A key driver of this shift is the rapid rise of large language models (LLMs), particularly from companies like OpenAI and Anthropic. These models are evolving into a central “intelligence layer” within enterprise systems, effectively replacing parts of traditional software functionality. OpenAI and Anthropic have already reached USD 25bn and USD 20bn in annualised revenue, scaling much faster than any leading SaaS companies, which signals a major redistribution of value away from traditional software vendors.
To remain relevant, legacy software companies will need to fundamentally rethink their business models. The traditional SaaS model, based on per-employee subscription pricing, is increasingly misaligned with a world where AI agents perform tasks autonomously. SaaS needs to shift toward usage-based or outcome-based pricing, where customers pay for results rather than access. At the same time, vendors will face pricing pressure as IT budgets are reallocated toward AI capabilities. Smaller, single-function software providers are particularly exposed, while even large incumbents must integrate AI deeply into their offerings to defend their position.
This disruption is already having a significant impact on valuations. The sector’s underperformance is driven primarily by valuation multiple compression rather than deteriorating fundamentals, with SaaS valuation multiples falling well below historical averages (around 5.8x EV/sales vs. ~9.6x long-term average). Investors are reassessing the durability of software growth in a world where AI could replace or commoditise many applications. While traditional SaaS names have de-rated, software companies tied to AI infrastructure - such as cloud databases, cybersecurity, and observability - are seeing renewed growth and stronger market positioning.
"Investors are reassessing the durability of software growth in a world where AI could replace or commoditise many applications."
Despite these challenges, AI is expected to deliver substantial productivity gains across the economy. The report estimates that a 10% reduction in global operating expenses by 2030 could generate around USD 2 trillion in savings, driven by automation of tasks such as coding, customer service, and content generation. Early evidence already shows significant efficiency improvements, with companies like Microsoft growing revenue strongly while keeping headcount nearly flat. Overall, while AI is disrupting legacy software and compressing valuations, it is simultaneously unlocking a new wave of productivity and reshaping where value is created within the technology stack.
"Despite these challenges, AI is expected to deliver substantial productivity gains across the economy."
The opinions expressed herein are correct as at 20 March 2026 and are subject to change without notice. This information should not be relied upon by the reader as research or investment advice regarding any particular fund, strategy or security. Past performance is not a guide to current or future results. Any forecast, projection or target, where provided, is indicative only and is not guaranteed in any way.
