How agents are changing pricing
Steven Forth is CEO of Ibbaka. Connect on LinkedIn
Key Points
The emergence of agents will impact the pricing of legacy apps in three ways.
Downward pressure on prices as legacy applications are seen as data stores to be mined by agents. As the agent becomes the primary user interface, it will be seen to be delivering most of the value.
Accelerated shift to usage based pricing, provided that the usage can be tied to value.
Greater focus on API pricing, as many agents will interact with legacy apps through APIs. The days of free API access to data are likely over (and charging for access is. better approach than denying access).
There has been a lot of interest in AI agents and how to price them. Ibbaka has shared one approach to this in Agents everywhere, but what kinds, and how to price them? Manny Medina has shared his approach on Kyle Poyar’s Growth Unhinged, and Michael Mansard’s COMPASS approach is informed by and relevant to agent pricing.
In this post, we want to look at this from the other side and ask how agents and agent pricing impact approaches to B2B software pricing.
How agent-based approaches are changing B2B software pricing
Heard on a webinar on July 8.
We look at legacy applications like Salesforce, Workday, and Cornerstone on Demand as dumb databases. We are cancelling subscriptions to any advanced functionality, as there are now agents that do it better.
Think about that for a moment, the iconic software platforms of the SaaS era are seen as ‘dumb databases’ with the value coming from agents that operate on top. Those agents could be:
Built by users for their own needs
Provided by the legacy app provider itself (think of all the agents that Salesforce is introducing)
Generic co-pilots and assistants (Google, Microsoft, OpenAI, Anthropic, Perplexity, Cohere, and so on)
Specialist agents built by companies like Ibbaka
The point is that value is shifting from the underlying application to the agents, and where value goes, pricing power follows.
As value creation moves to agents pricing power will follow
The shift to an agent economy is changing more than pricing power; it is also changing pricing models. Even today, the majority of pure SaaS pricing models are user or seat based based or have that as a component in a hybrid pricing model. Agents are, finally, upending this. There are several reasons for this.
AI agents:
Replace people or make them more efficient, in either way reducing the number of seats long term - given this feedback loop per per user pricing is not attractive
Have clear jobs to do, making approaches like Jobs to be Done easier to apply to pricing
Can track their own use and outcomes making value based and outcome based pricing easier to execute
Agent-era disruption of user based pricing is leading to a new pricing logic
The result is that agent pricing is seldom user-based. It can be based on the number and types of agents deployed, and is more likely to include a usage or task completion metric. Actual outcome-based pricing is still rare, with about 5% of the agents being deployed.
Aside: What is the difference between value-based pricing and outcome-based pricing?
Value-Based Pricing:
A strategy where prices are set according to how much value customers believe a product or service delivers, often based on unique features, brand, or perceived benefits rather than production costs or market rates.
Outcome-Based Pricing:
A model where the price is directly linked to the results or outcomes achieved by the customer, such as increased revenue, cost savings, or other measurable business improvements. Payment is contingent on the provider delivering specific, agreed-upon results.
Key Difference:
Value-based pricing is about what the customer thinks the product is worth, while outcome-based pricing is about what the customer actually gains from using the product or service. Outcome-based pricing typically involves more risk-sharing and requires clear, measurable outcomes.
Some of the emerging agent pricing models are summarized in the table below.
Some emerging agent pricing models (as of July 2025, expect this to change)
What does all this mean for conventional SaaS?
Downward pressure on prices as legacy applications are seen as data stores to be mined by agents. As the agent becomes the primary user interface, it will be seen to be delivering most of the value.
Accelerated shift to usage-based pricing, provided that the usage can be tied to value.
Greater focus on API pricing, as many agents will interact with legacy apps through APIs. The days of free API access to data are likely over (and charging for access is. better approach than denying access).
Conclusion
AI agents aren’t just another feature to up-charge—they convert software from a tool you rent to labor you buy. As that reality sets in, the winners will be vendors who master pricing mechanics that feel fair, scale with value delivered, and still protect margins in a world where compute costs are racing to zero. Your blog can position readers at the forefront of that transformation—before their seat revenue disappears.
Navigating the new pricing environment brought by AI agents? Contact us @ info@ibbaka.com