The AI wave won't necessarily kill major SaaS players like Salesforce. Instead, the competitive battleground is shifting to who can build the best new agentic interface for their existing platform. Incumbents are adapting quickly, challenging AI-native startups.

The current AI-driven downturn in SaaS valuations will primarily eliminate low-end, commoditized tools. Large enterprise platforms are protected because implementing AI effectively is complex and requires the deep, trusted C-suite relationships and integration capabilities that incumbents possess.

AI companies are selling large, seat-based contracts based on hype and experimental budgets, inflating current ARR. Investors are skeptical because, like early SaaS, customers will eventually demand usage-based or outcome-based pricing, challenging the long-term revenue stability of these startups.

Initial AI market skepticism was based on a SaaS model of selling limited-value subscriptions ('seats'). The new reality is a utility model based on consumption ('tokens'). In an agentic era, a single user can drive thousands of dollars in token usage, creating a virtually uncapped revenue stream that justifies massive infrastructure investment.

Current AI pricing models, which pass on expensive LLM costs to users, are temporary. As LLM costs inevitably collapse and become commoditized, the winning companies will be those who have already evolved their monetization to be based on the value their product delivers.

Contrary to fears that AI will destroy enterprise software, Jensen Huang predicts the opposite. He argues that enterprise software companies are poised to become a massive value-added reseller channel for foundation models from companies like Anthropic and OpenAI, leading to a logarithmic expansion of the AI market through their existing go-to-market channels.

The AI market has cleared its first ROI hurdle: model revenue has justified massive infrastructure investment. Now it faces a second, harder test. Enterprises spending billions on AI tokens must demonstrate tangible financial benefits, like higher margins or revenue, to sustain the flywheel.

Foundation models like OpenAI won't dominate the enterprise application layer. Similar to how AWS became infrastructure for a software explosion, LLMs will do the same for AI apps. Their core business and GTM motion is fundamentally different from what's required to sell complex enterprise solutions.

The business model for AI is pivoting away from SaaS-style subscriptions. Enterprise-focused labs like Anthropic see massive revenue not from adding users, but from the immense token consumption of API power users. A single developer can be 100x more valuable than a subscriber, forcing a shift to consumption-based pricing.