SaaS companies are not equally vulnerable to AI. Some (like Zendesk) tie seats to work AI can replace. Others (like Workday) use seats as a proxy for company size and are safer. Markets are currently failing to differentiate, creating a valuation gap worth understanding.

While AI expands software's capabilities, vendors may not capture the value. Companies could use AI to build solutions in-house more cheaply. Furthermore, traditional "per-seat" pricing models are undermined when AI reduces the number of employees required, potentially shrinking revenue even as the software delivers more value.

Traditional SaaS companies are trapped by their per-seat pricing model. Their own AI agents, if successful, would reduce the number of human seats needed, cannibalizing their core revenue. AI-native startups exploit this by using value-based pricing (e.g., tasks completed), aligning their success with customer automation goals.

SaaS companies face an existential threat not just from AI commoditizing their features, but from its shift from a workflow augmentation tool to a labor replacement tool. This fundamentally breaks traditional per-seat pricing models, which are tied to human headcount, creating a pricing crisis.

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.

Contrary to the narrative of AI startups destroying incumbents, established enterprise software companies will likely absorb and 'domesticate' AI. They will integrate AI capabilities into their existing platforms, leveraging deep customer relationships and distribution advantages to maintain their market position.

The fundamental business model of many SaaS companies is based on per-user pricing. AI agents pose an existential threat to this model by enabling smaller teams to achieve the same output as larger ones. As companies wonder why they should pay for 100 seats when 10 people can do the work, the entire economic foundation of the SaaS industry faces a crisis.

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.

As AI agents perform more work and human headcount decreases, the traditional seat-based pricing model becomes obsolete. The value is no longer tied to human users. SaaS companies must transition to consumption-based models that charge for the automated work performed and value generated by AI.