AI’s Impact on SaaS Will Be Uneven. Here’s What Leaders Need to Know.

The “SaaSpocalypse,” or early-2026 software selloff, has reinforced a tempting through-line for leaders: If AI can build or automate software, most SaaS should be rebuilt internally or shopped to a new vendor with a cost structure that reflects lower building costs with AI tools. But executives are overgeneralizing AI’s impact. Generative tools lower the cost of building deterministic, internally focused software, making many workflow and record‑lookup systems ripe for consolidation or in‑house replacement. But SaaS that combines pooled, proprietary data with predictive tasks is structurally different. These “operational intelligence” vendors embed judgment, not just documentation, capturing long‑tail edge cases that single‑firm data and frontier models cannot easily replicate. Their economics are anchored in avoided risk and expert labor, not license fees. Leaders should map their portfolios against a matrix: are SaaS conducting deterministic or predictive tasks and powered by internal or pooled context, to decide what to rebuild, renegotiate, or double down on today’s realities.