Management consultant Michelle Miller, a partner and managing director at AlixPartners and co-lead of its enterprise software practice, warned in April that generative artificial intelligence would fundamentally pressure traditional software business models. She now links the recent plunge in software and software-as-a-service stocks to the same forces identified in that earlier work, arguing that investor expectations for high growth are colliding with artificial intelligence driven disruption, outdated pricing models, macro uncertainty, and skepticism about artificial intelligence based valuation premiums. She says valuation multiples are decreasing as artificial intelligence tools such as Anthropic’s Cowork lower barriers to entry and disrupt incumbent workflows.
Miller stresses that artificial intelligence will not remove the need for software companies, but insists that vendors must prove they can still deliver on their growth agendas in a world of different economics. She argues that artificial intelligence is forcing simultaneous changes in software development, artificial intelligence governance and data security, go-to-market operations, pricing, valuation frameworks, and overall business structure, and that the companies mastering these transitions will define the next era while slower rivals are sidelined. New agentic systems such as Moltbot, Moltbook, and the tool now called OpenClaw are described as early experiments in agent-to-agent interaction that show the increasing productive power available to single users, while also amplifying unresolved questions around trust infrastructure, open-source risk, shadow artificial intelligence usage, and enterprise governance.
Enterprises are already piloting artificial intelligence tools across product, engineering, sales, pricing, and back-office functions, using them for accelerated coding, conversational interfaces, trust infrastructure, sales enablement, and automation in finance, HR, and IT. According to Miller, more than 30% of tech company workflows already include AI tools today, and that is expected to increase substantially over the next 5 years, yet she says a majority of generative artificial intelligence proofs of concept are stalling, with 75% of all AI deployments expected to fail. She forecasts that winning companies in 2026 will stop running incremental pilots and instead reinvent how work gets done. All software and SaaS sectors are seen as exposed, with mid-market, general-purpose productivity and workflow automation vendors facing an imminent existential threat. Miller predicts that in 2026, AI disruption will force major consolidation in the mid-market enterprise software industry, with M&A deal volume increasing 30-40% YoY, while incumbents with proprietary data, entrenched platforms, or deep vertical focus in regulated sectors, such as HIPAA-compliant patient data platforms, are expected to fare better if they help customers turn static data into actionable context.
