The a16z vision, frequently highlighted in their publications and podcasts, shows that generative AI is fundamentally rewriting the way B2B software is built, sold and used.
For years we talked about SaaS — Software as a Service. What we are witnessing now, however, is a shift that runs far deeper. The arrival of powerful, accessible AI models, especially generative AI, is changing the entire architecture of B2B software. It is no longer a ‘‘feature’’ you bolt on, like a chatbot tucked away in the corner of your screen. It is the very foundation on which the next generation of companies is built.
In practice you often see companies struggle with this transition. They try to slap AI on top of their existing — often outdated — systems. A ‘‘thin layer of intelligence’’ over a dumb database, so to speak. That is a dead-end street. Tomorrow’s winners are building their products around AI from the very first line of code.
From ‘‘system of record’’ to ‘‘system of intelligence’’
A concept that sits at the heart of this shift is the evolution from ‘‘systems of record’’ to ‘‘systems of intelligence’’. Your system of record is your source data: your CRM, your ERP, your customer database. For decades the value of software lay in accurately keeping track of that data. Yet data on its own does nothing; it is passive.
A system of intelligence, by contrast, actively uses that data to assist, advise and automate tasks for the user. Think of a CRM that not only stores contact details but proactively suggests the next sales action based on email traffic, market sentiment and the account manager’s calendar. Or supply-chain software that not only tracks inventory but autonomously calculates the most optimal ordering moments and transport routes based on thousands of variables. That is the essence: the software becomes an active partner, a co-pilot.
The impact on the business model is enormous
And this has far-reaching consequences. The traditional B2B sales model — with long sales cycles, demos and fixed licence fees per user per month — often no longer fits. When the value of your product is directly linked to usage (the more data the AI processes, the more valuable the output), consumption-based pricing models suddenly make much more sense. You pay for results, not for access.
What stands out to me is how this also changes the nature of competitive advantage. In the past your moat may have been a technological lead or a strong sales team. Today your moat is increasingly the unique dataset your AI is trained on and the feedback loops from your users. The more people that use your product, the smarter it becomes — and the harder it is for a competitor to catch up. A powerful flywheel, provided you set it up correctly.