Futurecasting benefits from mingling multiple insights. Here we share a map (dare we say a concept blend) of 2026 predictions from Kyle Poyar at Growth Unhinged, Jason Lemkin from SaaStr, Tom Tunguz at Theory Ventures and Steven Forth from valueIQ and Ibbaka. By combining these four perspectives we came up with four new predictions.

1: The Rise of "Synthetic PLG" (Product-Led Growth)

2: The "Bifurcated" Sales Organization

3: "Dynamic Value Stacking" as the Foundation for Pricing

4: Corporate Branded Content as a "Data Moat"

What will happen in B2B pricing in 2026? Our predictions.

1. API pricing is generalized

2. Credit based pricing becomes the dominant model

3. Credit wallets become standard

4. Synthetic data becomes the normal way to explore

5. Pricing and value become transparent

6. Pricing of all enterprise applications goes down

7. Pricing of chatbots goes down

8. Pricing of agents goes up

9. Costs go up

Pricing decisions often require us to resolve contradictions, like higher price vs. higher market share or revenue optimization vs. profit optimization. Roger Martin’s approach to the ‘opposable mind’ suggests that such trade-offs are not always inevitable and that we can find more creative (integrative) solutions. By operating in markets with low cross price elasticity and low price elasticity of demand, and where what we sell has the characteristics of a Giffen good we can resolve the price/volume tradeoff and get higher volume with higher prices.

One of the open questions for SaaS and AI pricing in 2026 is the fate of user based pricing. In 2025 there was a lot of interest in credit based pricing. Towards the end of the year there has been pushback, with people as prominent as Marc Benioff from Salesforce predicting that user based pricing will prevail. We disagree. Credit based pricing provides a better answer to the questions of price predictability and price flexibility than does user based pricing. Over the long term, credit based pricing models will push out user based pricing.

How have AI pricing models changed in 2025?

Our 2024 post ‘The Evolution of AI Pricing Models: From Consumption to Hybrid and Generative Approaches’ has had more than 4,000 views! 3,000 of these in 2025.

AI is evolving rapidly. We test our predictions from 2024 to see what has happened in 2025.

The big trends that shaped pricing in 2025 were the emergence of vibe coding, the adoption of agents as a common way to package AI functionality and credit based pricing to price them. Ibbaka covered these trends in its most popular blog posts of 2025. Here are the top five for 2025 plus our top performing post overall.

Good Better Best packaging models remain common, even in the agentic AI space. At the same time, they are being priced using credit based pricing models. How do Good Better Best and credit based pricing interact? What are design approaches are emerging? We explore this critical pricing design question in this post.

Credit based pricing models are common for AI and agenticAI companies. Design of these models is becoming a critical skill for go-to-market and pricing teams. One of the key question when designing this model is how granular to make the credits. There is a tension between tracking cost and value and between simplicity and precision. Managing these tradeoffs is critical to the design of credit based pricing models.

Generative AI has up the stakes on pricing transparency. But there is more than one type of transparency. There is pricing transparency, pricing model transparency. and pricing process transparency.

With generative AI in the buying process companies will have explicit, machine readable, information on value, price and the process used to set prices publicly available.

Some companies have a pricing process and a pricing model.

Others make do with just a pricing model or just a pricing process.

And then there are those companies that make do with some form of ad-hoc pricing, sometimes very smart and adaptive, often more like a frozen accident.

Most of us need to have a pricing process that leads to a pricing model.

Pricing model - a system of equations used to set price.

Pricing process - a set of algorithms and heuristics used to set price.

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.

OpenAI has been the defining company of the AI era and this applies to pricing as well. OpenAI has provided anchor points of $20 per month for basic generative AI and $200 per month for more advanced solutions. They have also signaled that price will increase exponentially as models get smarter. Other companies have followed suit. How does this frame pricing for AI app and agent companies? Can you price higher than OpenAI? What is needed to achieve premium pricing?

Witness the strategies shaping the future of B2B SaaS with exclusive access to our 5 most essential recent webinars—with our VIP decks now available for download. These sessions bring together the latest thinking from the industry’s top pricing and monetization experts, covering everything from Q1 2025’s biggest pricing shifts and the evolution of agent-based packaging, to actionable frameworks for AI pricing, mid-year trend analysis, and what’s really happening in B2B SaaS monetization.

Our Wrapped 2024 webinar and podcast recap of cutting-edge strategies in AI monetization, Net Revenue Retention (NRR), and value generation for B2B SaaS. From expert tips, industry leader conversations and interviews - content to make you and your customers a sales and value creation powerhouse.

AI agents are emerging as a standard way to deliver AI functionality, especially in B2B. This has been underlined by Salesforce’s recent Agentforce announcements. Agent pricing is evolving from inputs and number of agents to actions and outcomes. This evolution is framing how we think about pricing generativeAI.

AI agents are emerging as a standard way to deliver AI functionality, especially in B2B. This has been underlined by Salesforce’s recent Agentforce announcements. Agent pricing is evolving from inputs and number of agents to actions and outcomes. This evolution is framing how we think about pricing generativeAI.

Adobe is investing heavily in generative AI and has begun to signal how it will approach pricing. It is taking an incremental approach. Price remain anchored in a per seat price, but plans are becoming more flexible, and more expensive!

Conventional approaches to pricing are not fit for purpose when it comes to pricing generative AI applications for B2B. A new process is needed. Ibbaka is proposing generative pricing, a mashup (or concept blend) of dynamic pricing and value based pricing.

Salesforce has announced that it will use consumption pricing for its AI agents going forward. Why is Salesforce taking this approach? What are the implications for other Vertical AI companies? Results of our LinkedIn poll.