SaaS vendors must adjust pricing models as agentic AI transforms the industry

Software as a service (SaaS) is experiencing a fundamental shift as the concept of hiring software to do work will soon surpass the practice of buying software for professional use.

This will force SaaS vendors to change their pricing structures to adapt to an environment in which artificial intelligence evolves from a tool that assists humans to an autonomous agent that performs work independently.

As a result, the subscription-based model of charging a fixed, monthly fee per user—which created predictable recurring revenue and propelled software valuations—is about to break.

This shift from paying for access to paying for results presents an existential challenge for traditional SaaS vendors; if a provider sticks to per-seat pricing while its product successfully automates the tasks of human users, it is effectively engineering its own revenue decline.

Businesses must pivot toward outcome-based pricing to survive in the technology industry—but not all sectors will shift at the same speed, and change will likely be gradual as agentic AI usage increases over time.

Hybrid pricing models may also make sense in specific use cases, especially for SaaS vendors that provide a foundational platform and add-ons with measurable value.

However, the long-term trend is clear—and Bloomberg estimates that subscription-based pricing could decline from 60% of software pricing models toward 30% over the next decade, while outcome-based pricing is expected to shift from 10% to 60%.

Disruptions and opportunities

The immediate disruption will occur in high-volume, measurable workflows such as customer support, back-office finance functions and software development. In these areas, the unit of work is easy to define—such as a resolved ticket or a deployed feature.

Businesses that successfully leverage proprietary data and develop AI agent-powered SaaS add-ons or personalized content engines to enhance the user experience will see gains in customer retention.

This, in turn, can lead to expanded product offerings through customized software, configurations and add-ons.

SaaS vendors moving to outcome-based pricing will also unlock new opportunities in critical areas, including:

• Uncapped revenue: Under the subscription model, revenue is artificially capped by the customer's head count. Outcome-based pricing removes this ceiling and allows revenue to scale with the volume of work—like invoices processed or code generated—rather than the number of employees.
• The cost of inference: Unlike traditional software, agentic AI carries significant variable costs. Every task an AI agent performs requires computational power, application programming interface (API) calls and token processing; running these agents is more expensive than hosting and maintaining software code. Outcome-based pricing aligns revenue with these rising variable costs and protects vendor margins.
• Valuation premiums: The market is beginning to distinguish between legacy SaaS and AI-native businesses. Vendors that successfully transition to monetization models that capture the value of AI will likely command higher valuation multiples than their slower-moving competitors.

SaaS buyers also have reason to prefer a change in the pricing model. For them, shelfware—licenses that are paid for but rarely used—is a long-standing issue with the subscription model.

The shift to outcome-based pricing aligns SaaS user costs with value creation by:

• Eliminating waste: Customers will pay only for the specific outcomes they need, rather than a bundle of features they may never touch. That way, every dollar spent correlates to a business result.
• Increasing flexibility: In uncertain economic climates or seasonal industries, outcome-based pricing offers a variable cost structure. Businesses can scale their software spend up or down instantly based on demand, rather than being locked into fixed annual contracts for a set number of users.

Critical revenue considerations

This transition introduces significant hurdles from a revenue perspective, as private equity and public markets historically prefer the predictability of annual recurring revenue (ARR).

Revenue becomes inherently more variable the closer it is tied to outcomes, which makes valuations harder to determine. Defining what constitutes a successful outcome is also contractually difficult, creating potential friction and disputes between vendors and clients.

Investors have already taken notice; private equity SaaS deal count steadily decreased on a year-over-year basis from 2021 to 2025, while the deal count related to AI and machine learning drastically increased. Additionally, 2024 marked the first time that the AI and machine learning deal count was higher than the SaaS deal count.

But there is still an appetite for SaaS-based investments; capital invested in SaaS more than doubled from 2024 to 2025, in line with AI and machine learning capital invested.

It is important for SaaS leaders and private equity firms with SaaS portfolios to start preparing for the transition to outcome-based pricing.

The following strategic considerations are critical:

• Assessing valuation risk: Private equity firms must evaluate their portfolios for risks to the disruption in ARR, particularly in valuations heavily tied to the quality of revenue. Investors need to model the effects of future cash flows as they shift from fixed to variable streams.
• Redefining revenue recognition: Finance leaders must redraft revenue recognition policies. The move from ratable subscriptions to variable, outcome-based revenue requires robust new frameworks to ensure compliance and forecast accuracy.
• Running sensitivity analyses: Businesses should run shadow pricing models now to analyze how revenue flows would change if current users were billed on outcomes rather than seats. This helps identify customers who receive high value from automation but pay low subscription fees.
• Establishing new KPIs: The health of a SaaS business can no longer be measured by user retention alone. Key performance indicators must evolve to track outcome success rates as the primary metric of business health.

The takeaway

Agentic AI will fundamentally change how businesses interact with software by emphasizing outcomes and consumption. This is not just a technological upgrade—it is a fundamental business model reset.

SaaS vendors must adapt to avoid obsolescence; those that embrace this new era of outcome-based pricing will be better prepared for the next generation of the software industry.