Agents are popping up all over as we shift from a subscription economy to an agent first economy. One example is the pricing software sector (PROS, Pricefx, Vendavo, Zilliant) where PROS and Pricefx are leading the drive to agents. Let’s compare the agent strategies of these four companies, see where there are overlaps and differentiation, and where there are gaps that innovators could drive through. How are (will) these agents be priced?

There are two different visions emerging for the role agents will play in B2B software. One view is that agents will be add ons to larger standard enterprise applications. The other view is that agents will become the main point of interaction and value creation. Both have quite different implications for pricing. We polled our LinkedIn communities to get additional insights into this. Of course there are multiple possible futures here and all may emerge in different B2B software sectors.

There has been a lot of discussion of how to price AI agents. But the busines senvironment is changing and the question has changed. Business leaders are now asking how agents are changing pricing. The rapid emergence of an AI driven agent economy is changing how we think about pricing of all B2B software and is leaking into many other conversations. This post explores these critical questions.

Agents are popping up everywhere. Vibe coding and good tooling have made it easy to develop agents. Users and buyers are looking for simple solutions that leverage AI. Agents are the result. There are two broad trends: net new agents and agents built to access functionality and data in existing apps. How do pricing approaches differ in these two cases?

One emerging strategy for designing and pricing a family of agents is the team. Agents are being designed as complements or replacements for well established functional teams. An example of this in the data space is Brighthive. They have designed their agents to reflect well established roles on a data team.

Over the past three months there has been a sea change in packaging and pricing for AI. The biggest change has been the rise of agents. But there has also been a shift to making AI the default. We can see that in recent moves by some of the world’s leading software companies: Intercom, Adobe and Gong.

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 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.

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.

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.

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.

Many agents are being introduced to the market to help with the saes process. There are AIs for Sales Development Representatives, for crafting sales content and for analyzing calls. Most modern CRMs use AI to predict what will close and when. What will happen when these agents encounter agents acting for the buyer? This is happening today and the world is about to get a lot weirder. We offer case studies for buyers of CRMs and sales intelligence.

The Ibbaka AI Monetization in 2025 survey report is getting a lot of interest as it has the deepest data on how AI-enabled B2B SaaS and B2B AI are being monetized. On January 23 Ibbaka will have a webinar with pricing and monetization experts Mark Stiving and Michael Mansard to go deep into the findings and recommendations.

Ibbaka’s second Annual report on AI Monetization is now available. The report is based on a survey of more than 300 B2B companies that are bringing AI enabled or AI applications to market. It includes four mini case studies, proposes four emerging packaging patterns and defines three different approaches that companies are taking. The report is essential reading for anyone in the B2B AI applications space.

OpenAI has released its newest reasoning model o3. How will it be priced? Will OpenAI move from token pricing to task pricing? How would task based pricing work for o3? How would it impact pricing of agents and applications using o3?

Commercialization of B2B generative AI is coalescing around four patterns: Co-Pilots, Agents, Generators and Service as Software. Which pattern will dominate in 2025? How does one price each of these patterns? Prepare for change in 2025.