Unlike mobile or cloud, which were sustaining innovations that enhanced existing SaaS models, AI is a disruptive force. It fundamentally challenges seat-based pricing and requires a difficult, full-stack pivot of a company's business model, culture, and organizational structure.

Traditional SaaS companies charging on a per-seat basis are highly vulnerable to disruption. Paul Bricault warns that AI-native companies can offer superior functionality at lower costs, leading to a "rip and replace" cycle that will put immense pressure on incumbent, non-AI-native software businesses.

The biggest threat to incumbent software companies isn't a new feature, but a business model shift. AI enables outcome-based pricing, which massively favors agile newcomers as incumbents struggle to adapt their entire commercial structure away from seat-based subscriptions.

Workday itself was born from a platform shift, creating a cloud-native version of on-premise software like PeopleSoft. The current AI platform shift is creating the exact same opportunity for a new generation of startups to displace today's cloud incumbents, demonstrating a recurring cycle of technological disruption.

As AI agents reduce the number of human "seats" required to use software, vendors are accelerating their move from seat-based licenses to usage-based models. The revenue lost from fewer users is expected to be offset by higher consumption, as automated workflows interact with platforms far more intensively than human employees.

The dominant per-user-per-month SaaS business model is becoming obsolete for AI-native companies. The new standard is consumption or outcome-based pricing. Customers will pay for the specific task an AI completes or the value it generates, not for a seat license, fundamentally changing how software is sold.

The current moment is ripe for building new horizontal software giants due to three converging paradigm shifts: a move to outcome-based pricing, AI completing end-to-end tasks as the new unit of value, and a shift from structured schemas to dynamic, unstructured data models.

The next major business model shift in software is from seat-based pricing to outcome-based pricing (e.g., paying per task completed). This favors AI-native newcomers, as incumbents will struggle to adapt their GTM and financial models.

The "horrific" user experience of Salesforce CPQ stems from a fundamental architecture problem. It was built for a simple "one seat, one license" world. The explosion of SKUs, consumption models, and complex discounting in modern SaaS has broken its underlying data model, creating a massive opportunity for AI-native challengers.