Enterprise AI Business Models – pure economics!
It’s Economics not technology, that kills software
When OpenAI and many other companies warn SaaS companies about their end, this is only fair. And it’s not just about SaaS, it’s about ERP, CRM, SCM, and other Enterprose Solutions. The risk doesn’t only come from a technological perspective. But as so often, the real killer of old technology comes from a disruptive business model. And this post is about the new business models that go VERY DEEP INTO ENTERPRISE IT.
My Legacy
I founded a SaaS company in 1999 right in parallel to Salesforce. The term SaaS didn’t even exist back then. So I should fight for my own legacy – but I don’t. I can’t – not anymore. We started an Enterprise AI company as a SaaS Model in 2021, then stopped after just a few months. It just did not make sense anymore.
Our path to Pay-for-Gain
License Shelfware, reducing users because of subscriptions, reducing licenses because of price, and unclear usage patterns. This is at odds with the new world of maximizing productivity and opening the floodgates to growth, innovation, a better customer experience, and operational excellence. How could we increase productivity while ensuring that not all employees are part of it? It was clear that the SaaS business model is not only outdated but also counterproductive to what we all try to achieve. We looked for what would be ideal for businesses and still economically viable for producers.
1) No More User Subscriptions
So we started with the customer side: Wouldn’t it be ideal if they could add every single employee onto the platform at no cost? For us, the cost of a user entry in the database is too low to even calculate. So this was doable.
2) No more application licenses
Then what about licenses? We could charge separately for using individual applications. This would be in addition to pay-per-consumption. But we all hated selling shelfware. If we go with pay-per-use, it doesn’t matter which application customers use; they can try it or not. This model was also economically advantageous for both sides. Moreover, it brought an entirely new opportunity to the game: We could build applications that may be used only once a year, or even just once at all.
3) Measurability of Agentic AI
Yet pay-per-use was still not ideal. We were fighting for productivity gains and for the ability to measure AI productivity. The final idea was Pay-per-Gain. Imagine you pay for the AI performance. Obviously, we had to observe every step the AI took and measure how much time it saved. But this is what we had designed in from the very beginning. In a way, we caught two birds with one stone. Measurable AI and payments relative to the AI’s productivity.
Pay-for-Gainhas become the most attractive business model we’ve ever seen.
The full extent of the business model was even shocking to us when we finalized it.
Enterprise customers called it the ultimate killer of CRM, ERP & Co. No subscription, no licenses, measurable instant ROI, no update fees, and no upgrade costs – just consumption is hard to beat – even for the biggest SaaS or Software companies. This realization was far more devastating for conventional IT.
- AGENT DEVELOPMENT: Building Agents with agents makes the creation processes extremely efficient. We created an enterprise-grade* Multi-Agent Compliance Management Application in 8 hours, not 2 years. No conventional software company can sustain that disadvantage. This makes Enterprise AI vendors a cost leader.
- ADAPTATION: Enterprise AI adapts to user behavior – not the other way around. Shifts from Software-based solutions to Native-AI are far less cumbersome than people think. Adaptation cost plummets to near zero.
- MASSIVE SAVINGS: When conventional software companies generate $25B in revenue, Enterprise AI vendors would generate only $10B. IT solutions cost cuts in half: Enterprise AI administration is far easier and can be distributed across an enterprise.
- IT MANAGEMENT COST: The notoriously under-budgeted and over-loaded IT teams see a light at the end of the tunnel. AGENTIC-IT is more demanding but far less frustrating. 50% cost reduction is not a dream, nor is it marketing.
- AGANT GIGA FACTORY: In 2026, the AGF will produce thousands of AI Agents for free of charge. Why free? It’s the business model that allows us to do that.
Software or SaaS companies with millions of lines of code cannot just glue on Agents. They would need to rebuild their foundation to stay competitive. And at a speed the AI market is growing and evolving at the same time, that is the hard part and the reason why many don’t believe that SaaS or general software won’t stay in the market.
What do you think?
Do you work for or own a SaaS / Software company? Doyou believe you can compete?
Do you work with conventional software and believe it will not change?
NOTE:
* = enterprise-grade means a platform-based AI Enterprise Solution for managing hundreds or thousands of users across departments, business units, or countries. Scalable, save data backend, department-based cost accounting, rights and roles definition, access control, third-party solution integration, and more.
