AI agents will transform software pricing

For years, SaaS has been the go-to model for software. Annual contracts, prepaid revenue, and predictable, per-seat pricing fueled its success.

The model was reliable, scalable, and easy to budget.

But with the rise of AI agents that can be 2-3 times more productive than human counterparts, the seat-based model is facing disruption.

The value AI agents bring to businesses goes beyond traditional metrics, pushing us to rethink how software is priced in a world where machines are doing the work.

🧡 P.S. Know someone ready to level up as a founder (or become one)? Share this newsletter and help their journey.

Seat-based pricing works because it aligns with human users: each person gets a license or "seat" to access software. But what happens when AI agents take over tasks?

If a single AI agent can match or exceed the output of several human employees, charging "per seat" no longer makes sense. It raises a fundamental question: how do we price software when the user isn’t human?

Rethinking pricing models for AI-powered software

As companies deploy AI agents to handle everything from customer support to data processing, several new pricing strategies are emerging. Each has its own set of challenges and benefits, and no single model will fit all use cases.

Here are three of the most promising alternatives:

1. Tripling per-seat pricing

   • Premise: If an AI agent is 3x as productive as a human, the simplest adjustment would be to triple the per-seat price.

   • Challenges: This could be a hard sell to clients who are used to stable, predictable costs. A sudden price hike could deter adoption in the short term.
     
     Easy fix: gradually increasing prices could ease customers into this change.

   • Potential Impact: Forces companies to consider AI-driven roles differently in their budgets and staffing plans. Scaling AI-driven operations under this model could become costly.

2. Usage-Based Pricing

   • Premise: Much like cloud storage or database services, AI-driven software could move to a usage-based model where companies pay based on how much compute power, data, or time their AI agents consume.

   • Benefits: Usage-based pricing aligns cost with actual value, letting companies pay based on the resources their AI agents use. This model could help justify high-performance AI since costs would scale with productivity.

   • Challenges: This model introduces cost unpredictability. If an AI agent suddenly needs more compute to handle a surge in tasks, the software bill could spike unexpectedly. Companies may need to educate customers on budgeting for fluctuating costs, and sales teams would need to adjust their compensation plans.

   • Potential Impact: Usage-based pricing could be ideal for companies that need flexibility, letting them ramp up AI use as needed without committing to a flat rate. But it would also demand a more sophisticated understanding of resource allocation and usage tracking.
     

3. Performance-Based Pricing

   • The Idea: Charge based on the outcomes AI agents achieve rather than simple access or usage. For instance, if an AI agent handles sales prospecting, the software company could charge per successful meeting or closed deal.

   • Benefits: Tying pricing to outcomes aligns cost directly with value, which is attractive to customers. If the AI delivers results, clients pay more; if it doesn’t, they pay less.

   • Challenges: Measuring performance is complex. If a company doesn’t use the software optimally, results could suffer, leading to unpredictable revenue. Performance-based pricing also risks disagreements over what constitutes "success."

   • Potential Impact: This model may appeal to companies focused on tangible, measurable results, like sales teams or customer service operations. However, it requires clear metrics and accountability for performance.

Implications for software vendors & customers

Moving away from seat-based SaaS pricing has major implications. Vendors must rethink revenue models, sales incentives, and customer education.

This shift requires significant adjustments in everything from sales pitches to contract structures. Customers, in turn, will need to adapt budgeting and usage strategies, likely making AI expertise a core part of strategic planning.

Vendor Side: The transition to a new pricing model is not just a pricing decision — it’s a strategic overhaul. Software companies need to develop customer education programs to help clients understand and manage costs. Sales teams may need restructured compensation plans to adapt to less predictable revenue. Product teams need to ensure transparency in usage or performance metrics, which will be essential for both usage- and performance-based pricing models.

Customer Side: Companies using AI-driven software will need to adopt new budgeting approaches. They’ll have to predict usage and performance, or even hire dedicated staff to manage AI consumption. For many organisations, this will be a mindset shift, requiring deeper integration of AI management into everyday operations.

New era of software pricing

AI agents are set to rewrite the rules of software pricing, much like SaaS disrupted traditional software licensing.

If AI continues its rapid productivity gains, pricing models will have to evolve to match its unique value. Startups could possess a strategic advantage, as they’re not locked into traditional SaaS structures and can experiment more freely with usage and performance-based models. Established players, meanwhile, may face tough choices about how to phase out or adapt seat-based pricing to stay competitive.

Just as Salesforce popularised the SaaS model by shifting away from perpetual licenses, today’s AI-focused startups might define the next standard by pushing beyond seat-based pricing.

In time, “No SaaS” could become a rallying cry for a new wave of companies using usage-based or performance-driven pricing models to attract clients and challenge incumbents.

How do you see this change playing out?

📩 Get a free pitch deck

Raising soon? I’ll send you over Passionfroot’s pitch deck that raised over $3M, just refer one friend via your personal referral link: https://foundersfuel.beehiiv.com/subscribe?ref=PLACEHOLDER

Additionally, I’ll add you to a private founder community where I post valuable resources daily.

✈️ How I Can Help