An emergent pattern in the agent economy is for companies to provide their customers with the ability to build custom agents that sit on their platforms and help the customer get more value. These are often called User Built Agents. How is value created for customers with this new functionality? How will it be priced? Ibbaka used it value model generation AI to explore these critical questions.

On April 24 Ibbaka published some important research on pricing and billing in the agent economy. This is the first in depth report on the emergent Agent Economy. Agents are becoming one of the primary ways that generative AI functionality is being brought to market. The report is rather long, more than 80 pages, and in today’s high paced world not everyone will want to invest the time to read in depth We get that. Here are a series of prompts, and responses from Perplexity, that give different entry points into the report.

Pricing of agents is a hot topic in business circles. As we move to an agent economy how will pricing change? We explore this question by using the concept blending technique to create concept blends of Jobs to be Done and B2B SaaS and then Jobs to Be Done and Agent AI in the context of pricing. We then compare the two.

Pricing AI Agents is a critical challenge for pricing and innovation in 2025. Two approaches have emerged so far, the Ibbaka Agent Pricing Layer Cake and the Growth Unhinged Agent Pricing Matrix. Let’s look at how these work and how they can be used to price AI agents. As credit based pricing is becoming common for AI agents the two approaches are combined to address this.

The Agent Economy is rewriting the rules for B2B software and launching a revolution as important as the one Salesforce launched back at the beginning of the 21st C with its ‘No Software’ SaaS business model. Ibabka has compiled extensive research, including primary research, on the implications of agents for value, packaging, pricing and billing. This extensive report will help you execute on the changes we all need to make.

AI and AI agents are emerging as a dominant form of economic activity. How we price these agents has deep implications for the kind of economy we live in. Series 7 Episode 1 of the UK science fiction series Black Mirror asks us to think about the ethics of subscription models and what kind of world we want to live in. We need a framework for ethical decisions in pricing AI agents.

The agent economy will replace the subscription economy and most value currently captured within enterprise software will be delivered by agents. This will require new approaches to pricing. By combining the Jobs to be Done approach to pricing with the Ibbaka AI agent pricing layer cake there is a path forward for Agentic AI companies.

2025 is shaping up to be an interesting year, and a lot has already happened. In Q1 we have seen some important developments.

Join Steven Forth from Ibbaka, Marcos Rivera from Pricing I/O, and Karan Sood for a dynamic webinar on "What Happened in Pricing in Q1 2025". Marcos, Karan, and Steven are all informed, opinionated and outspoken.

Historically, SaaS companies have used ARR or Annual Recurring Revenue as their key metric. As pricing models diversify and access, usage and outcomes are combined with subscriptions to build hybrid pricing models ARR becomes less relevant. At the same time, more volatility in churn numbers is undermining the utility of ARR as a predictor of future revenue. We need a new metric. Ibbaka proposes that this be APR for Annual Predicted Revenue.

AI is playing a growing role in the buying process. One of the things these AIs look at is the pricing page. How do the pricing pages of some well know B2B SaaS companies perform when looked at by a buyer AI?

Our customers often come to us with a standard set of question about value and pricing. To help everyone answer these questions and to show how Ibbaka goes about answering these questions we are sharing a series of LinkedIn carousels. Here are the first six.

Do you need hybrid pricing?

Will your pricing become transparent?

Should you increase prices?

Good & bad discounting

Best practices in introducing new pricing

Quantify differentiation to capture more value

Once upon a time it was enough to have a simple ROI calculator that you kept in a spread sheet or pushed to the web. Those days are gone.

Today we need dynamic value models that adapt to market conditions and competitor actions.

These value models are used across the customer experience, for pricing, value based sales and customer success.

OpenAI is testing a new framework for packaging and pricing AI agents. One that resets the anchor prices for AI from tens or hundreds of dollars per month to thousands or tens of thousands of dollars per month. What is happening here? Will it work? What does this mean for other types of agent?

Tokens and credits are becoming a popular way to price AI agents and applications. Why is this? They offer a unique combination of predictability that is important when pricing early stage general purpose technologies or when there are too many use cases for conventional value based pricing. Design of credit or token based pricing requires special attention to balancing the different pricing incentives.

B2B SaaS companies are all over the map when it comes to sharing their pricing online. Will the incursion of AI into the buying process change that? In this post we explore how buyers might use prompts to estimate price and value. And then we test it in our own category of value based pricing and customer value management. We end with some predictions and recommendations on if, when and how to present your price so that generative AI can use it in recommendations.

How will AI agents restructure the B2B SaaS sector? One frame for this is Clayton Christensen’s framework of disruptive innovation. Are B2B AI agents an example of sustaining or disruptive innovation? How does this impact go-ot-market strategies? What are the implications for pricing?

What are the key trends that will impact pricing in 2025? What decisions will SaaS leaders need to make on pricing? Join this PeakSpan master class with Edward Wong and Steven Forth to prepare for change and get practical advice on how to lead pricing in a year of transformation. The shift to consumption and usage based pricing, outcome based pricing, hybrid pricing models will all be covered.

There are three key axes for B2B AI applications that are leading to six basic approaches to application development. The three axes are: is use episodic or ongoing, does it support decisions or make decisions, and is the application intended for defined problems or open problems. This has a big impact on value and pricing models. Understanding where your application is placed frames value and pricing design.

AI agents have emerged as a key pattern to package AI functionality. 2025 is being called the year of agentic AI! How will all these agents deliver value? How will they be packaged and priced? How will billing work? Subscription building leader Maxio and customer value management leader Ibbaka are partnering to answer these questions.

Ibbaka is leveraging its value model generation AI to generate a series of Category Value Reports. These reports combine value models and generative AI to get new insights into the structure of B2B software markets. Our first report is on Learning Solutions. In this report we generated value models for six category leaders and then combined them to get a feel for what drives value in the category.