The Software Seat Is Dying...What Comes Next?
What do you do when your software's best customer isn't an actual person
For years I signed enterprise software contracts at one of Europe’s largest banks. I managed over 20,000 engineers and technology budget of roughly $5 billion a year. I know what procurement looks like from inside.
Every year the same vendors came in with the same pitch: you’re growing, you need more seats. And it was true. We hired people, those people needed tools, we bought licenses. The vendor’s revenue scaled with our headcount. Expansion revenue accounted for 40% to 67% of new ARR for SaaS companies at scale. Nobody questioned it because it worked.
I think about that math a lot now. Because from where I sit today, as an investor backing software companies, I can see both sides of a problem that is just starting to become visible. The unit that the entire software industry was built on, the human seat, is losing its meaning.
The most productive user of that software no longer needs a login and every vendor who built their financial model on counting humans in front of screens is about to learn what happens when those humans step away but the work keeps getting done.
The billing unit broke
Here is what is actually happening inside enterprises right now.
Companies are deploying AI agents across support, sales operations, and back-office workflows. And they are seeing that entire functions can run with 20% to 90% fewer human seats after those agents go live. The work still gets done (and often better) but the humans aren’t logging in.
I know exactly what happens next because I used to be the buyer. You open your renewal spreadsheet, you see 3,000 licenses, then you check the usage data. 1,200 people haven’t logged in for ninety days. Your procurement team calls the vendor. The conversation is uncomfortable for everyone.
Multiply that across thousands of enterprises and you get what the market delivered in early 2026: an estimated $1 to $2 trillion in software market capitalization, gone. Analysts called it the “SaaSpocalypse.” The name sounds dramatic but the cause was simple. Investors realized that per-seat revenue was structurally compromised.
No one has figured out how to price AI software yet
When I was the buyer, I never questioned per-seat pricing bc it felt fair. You use the tool, you pay for the tool…simple. But fairness depended on the assumption that a human being would always be the one using it.
Remove that assumption and the whole contract structure starts to feel arbitrary. You are paying for access to system that your AI agent consumes through an API. The agent doesn’t need the interface. It doesn’t need onboarding. It doesn’t need a password reset at 2 AM. Why does it need a seat?
This is the question every enterprise procurement team is now asking and no vendor has a good answer yet. Some are trying.
Intercom charges $0.99 per support ticket its AI agent resolves
Zendesk charges $1.00 to $1.50 per automated resolution.
Salesforce now runs three different pricing models simultaneously for Agentforce. Three models at once. And it’s probably the right posture when you don’t know what comes next.
Outcome-based pricing sounds clean in press release but in practice it’s really hard. You need to define what “resolved” means in a contract that will survive your customer’s legal team at renewal.
I have been on that side of the table and know what happens when a vendor promises an outcome that procurement can interpret six different ways. It creates a new category of negotiation that most sales organizations are not ready for.
Consumption-based pricing, pay for API calls or tokens processed, has opposite problem. It is transparent. Customers like it until they get a bill from AI processes nobody was monitoring. And vendors lose the revenue predictability they spent a decade building.
The finance team that used to forecast next quarter with 95% accuracy now stares at a usage curve that could go anywhere.
Hybrid models, a base platform fee plus variable AI charges, are where most large vendors have landed. ServiceNow replaced its legacy pricing with AI-native tiers. Workday launched Flex Credits. Everyone is hedging. Nobody has arrived.
My honest read - the industry is in the early phase of a transition that will take years to settle. The companies pretending they have the answer are probably the ones most at risk of getting it wrong. Running three pricing models at once tells you where the industry stands. Everyone is searching. Nobody has found it.
The infrastructure layer is where the real value will be built
And the pricing question sits on top of a deeper structural problem that most people are not talking about yet. AI agents don’t click buttons, they call APIs. Software that was designed for human eyes and human hands is being bypassed entirely.
89% of developers now use AI in their work, but only 24% are designing APIs specifically for AI agent consumption. That gap is enormous and tells you where the next generation of infrastructure companies will be built.
Anyone who has managed large-scale enterprise IT knows what happens when systems can’t talk to each other. I lived that reality for years across dozens of platforms. The cost is staggering and mostly invisible until you try to do something that crosses system boundaries.
Now imagine that problem multiplied by thousands of autonomous agents, each needing credentials, permissions, guardrails, and the ability to communicate with other agents across your entire infrastructure.
This is the part that keeps me up at night as an investor. The identity problem. Machine identities already outnumber human users by orders of magnitude in most enterprises. Every agent needs access policies.
Traditional identity management was built for people with logins and passwords. It is fundamentally inadequate for governing fleets of autonomous software agents making API calls across your entire stack.
When I was running technology for a bank that processed a significant share of an entire country’s transactions, interoperability between systems was already one of the hardest problems we faced. And that was with humans driving the workflow.
Add thousands of autonomous agents operating at machine speed, each with its own credentials and permissions, and you start to understand why the infrastructure layer underneath all of this is where the real value will be created. The plumbing. The boring, essential, deeply defensible work that nobody talks about at conferences.
Fifty-seven percent of companies had AI agents running in production by late 2025. For large enterprises with over 10,000 employees, that number was 67%. These are not pilots. These are production systems handling real workflows. And most of them are operating on infrastructure that was never designed for this kind of load.
Where humans still matter and why there will be fewer of them
Before you assume the human seat is dead everywhere, it’s worth pausing. In regulated industries like finance, healthcare, legal, accountability still requires a person. An AI agent can prepare 99% of a compliance review, but someone with a license and legal liability has to sign off. I dont think that’s going away.
And strategic, creative, relational work resists automation in ways that are genuinely structural. The C-suite executive, the design lead, the key account manager. Their value comes from judgment and relationships, not from workflows that can be scripted.
But the nature of oversight is changing. The old model, where a person manually approves every AI action, creates bottlenecks and leads to rubber-stamping. People get desensitized and stop genuinely reviewing.
The smarter approach is tiered: low-risk tasks run fully automated, high-stakes decisions require mandatory human approval. Fewer humans, more powerful roles. More expensive seats, but far fewer of them.
I managed teams large enough to see this pattern. The most valuable person is rarely the one doing the most work. It is the one making the hardest calls with the least information. AI doesn’t change that. It amplifies it.
The per-seat era is over and three models will replace it
So what does all of this add up to?
The entire SaaS era was built on elegant assumption that the number of people using software was a good proxy for the value it delivered. And for thirty years that assumption held while creating enormous wealth for the companies and investors who understood it.
It doesn’t hold anymore.
At its core, this is business model story. The technology is the catalyst, but the real disruption is in how value gets measured, priced, and captured. Every pricing experiment, every valuation reset in the public markets, every startup building agent governance infrastructure. It all traces back to one structural fact: the billing unit changed.
Some companies will figure out how to charge for outcomes.
Some will build the infrastructure that agents depend on.
Some will hold onto seats in domains where human judgment is genuinely irreplaceable.
I think those are the three paths forward.
I spent years buying software for one of the largest tech organizations in European banking. I know what makes a vendor irreplaceable at renewal and what makes them a line item that gets cut without a second thought.
The irreplaceable ones were never the prettiest tools but the ones so deeply embedded in our workflows that ripping them out would cost more than keeping them in. They were the plumbing. The rails, not the trains.
That has not changed. What has changed is that the workflows themselves now run on machine logic instead of human habits. The vendors who understand this will reprice, rebuild, and survive. The ones who keep counting seats that nobody is sitting in will slowly compress until there is nothing left to compress.
The billing unit changed and the strange thing is, the software itself is fine. It still works. It still solves problems. It might even solve them better now than it did a year ago. The only thing that broke is the assumption about who would be using it.
Thirty years is a long time for an assumption to hold. Long enough that people stopped seeing it as an assumption and started treating it as a fact.
That is always how these transitions catch people off guard. The fact was never a fact. It was a convenience but now the convenience is over.