A CEO’s Perspective: Why Most 2026 SaaS Predictions Will Fail in Practice

Every year, the conversation about what’s coming next gets louder.
More AI. Fewer people. The end of seats. The end of SaaS. The end of everything we thought we knew.

If any of that were fully true, running a company would already feel simpler.

It doesn’t.

What 2025 actually exposed is not a technology gap. It exposed a systems gap. Teams adopted more flexible pricing, more consumption models, more AI-driven products. But the organizations behind them did not evolve at the same pace. Contracts, billing, revenue recognition, forecasting, and reporting were stretched beyond what they were designed to handle. Not because the ideas were wrong, but because execution across the full lifecycle was never trivial to begin with.

The result is a quiet kind of friction. Products that sell well but are painful to operationalize. Finance teams that are asked to support innovation with tools built for predictability. Founders who hear that “seats are dead” while still closing their books manually at the end of the month.

The real shift heading into 2026 is not about replacing people or ripping out SaaS. It’s about whether companies are willing to design systems that reflect how value is actually created, measured, and delivered. That work is less visible than a demo. It’s also where most companies are already feeling the strain.

What actually broke in 2025

What stood out to me most over the past year wasn’t a single pricing model or technology shift. It was how often teams underestimated the operational cost of flexibility.

I’ve sat in conversations where a new pricing model made perfect sense at the product level. Usage-based components, hybrid contracts, value-based elements. All reasonable. All defensible. And then, a few weeks later, the questions started piling up. How do we bill this? How do we reconcile it? How do we explain revenue to the board when usage isn’t linear and contracts aren’t clean?

None of this showed up in the original decision. Not because teams were careless, but because the system was never built to carry that kind of complexity end to end.

What broke in 2025 wasn’t execution effort. Teams worked harder than ever. What broke was alignment. Product moved faster than finance. Sales sold flexibility that operations had to manually untangle. Finance became the place where every unresolved assumption eventually landed. Not as a strategic partner, but as the clean-up crew.

That pattern repeated itself across companies of different sizes and stages. The specifics changed. The friction didn’t.

Why the Pricing Model Isn’t the Problem

Most of the debate I hear still circles around the same question.
Are seats dead? Is everything moving to consumption? Is usage the only model that makes sense going forward?

I don’t think that’s the right argument.

On paper, both models work. I’ve seen seat-based pricing that’s clean, predictable, and easy to operate. I’ve also seen consumption models that align beautifully with how customers actually use a product. The problem usually isn’t the model itself. It’s what the company assumes will happen after the model is chosen.

Consumption sounds simple until usage becomes uneven. Until customers consume value in bursts. Until contracts include minimums, overages, exceptions, and commitments that don’t map neatly to a single metric. That’s the point where theory meets reality, and where most systems start to show their limits.

What teams often underestimate is that flexibility at the pricing layer multiplies complexity everywhere else. In billing. In reconciliation. In revenue recognition. In forecasting. Someone still has to explain the numbers. Someone still has to close the month. And when that work isn’t designed into the system, it doesn’t disappear. It just becomes manual.

The real issue isn’t whether seats are relevant. It’s whether the system behind the pricing reflects how value is actually created and measured over time.

The part AI cannot remove

There’s a version of the future that gets a lot of attention. One where agents run everything. Where decisions are automated end to end. Where humans are mostly out of the loop.

I don’t see that version playing out in the parts of the business that actually matter.

AI is extremely good at accelerating decisions. It’s not good at owning accountability. In complex revenue environments, there are tradeoffs that no model can fully resolve. Edge cases. Exceptions. Judgment calls. Those don’t disappear when you add automation. They just surface faster.

What I’ve seen in practice is that the more flexible and dynamic pricing becomes, the more important human oversight gets. Not because teams don’t trust automation, but because the cost of being wrong is high. Revenue is not a sandbox. It touches customers, auditors, boards, and cash flow. There is very little room for silent failure.

The idea that you can remove humans entirely from these systems assumes the problem is execution. Most of the time, it isn’t. It’s decision-making under uncertainty. And that’s still very much a human responsibility.

Why build vs buy stopped being the right question

I still hear this question framed as a binary decision. Should we build this in-house, or should we buy a solution?

At some point, that framing stopped being useful.

There are things that make sense to build. Point solutions. Isolated capabilities. Areas where the scope is clear and the blast radius is limited. In those cases, building can be faster, cheaper, and more aligned with how a team wants to work.

But once a problem cuts across teams, the calculus changes. Pricing that affects product, sales, finance, and operations. Revenue flows that touch contracts, billing, reconciliation, reporting, and forecasting. At that point, you’re no longer building a feature. You’re rebuilding a process.

That’s where build vs buy becomes a distraction. The real question is how much organizational energy it will take to make something reliable. Not to launch it. To live with it. Maintain it. Explain it. Audit it. Close the month with it.

I’ve seen teams move fast by building something clever, only to slow themselves down later because every edge case required another fix, another person, another manual step. Speed doesn’t come from owning the code. It comes from removing bottlenecks the organization shouldn’t be carrying.

What actually matters heading into 2026

When I look ahead, I don’t see a clean break from SaaS. I see a pressure test.

Companies are being asked to support more dynamic pricing, more flexible contracts, and more real-time usage, without increasing operational risk. That’s not a tooling challenge. It’s a systems challenge.

The teams that will handle this well are not the ones chasing the loudest narratives. They’re the ones willing to design revenue systems that reflect reality. Systems where automation and human judgment coexist. Where flexibility is intentional, not accidental. Where finance is part of the conversation early, not brought in to clean things up later.

The shift isn’t about replacing people or declaring old models dead. It’s about taking responsibility for how value moves through the company. From how it’s defined, to how it’s measured, to how it shows up in the numbers.

That work isn’t flashy. It doesn’t demo well. But it’s the difference between selling innovation and being able to operate it.

A Belief Worth Getting Comfortable With

If there’s one belief I think companies need to get comfortable with, it’s this: flexibility without operational ownership is not innovation. It’s deferred work.

Every decision to introduce a new pricing model, a new usage metric, or a new contract structure carries downstream consequences. Someone will have to make it real. Someone will have to explain it. Someone will have to stand behind the numbers when they’re questioned.

That responsibility doesn’t go away because the idea is sound. And it doesn’t get solved by adding more tooling after the fact. It has to be designed into the system from the start.

Companies that accept this early move faster with less friction. Companies that don’t spend their time reacting to problems they already created.

A Pattern That Keeps Repeating

What’s striking is how consistent this pattern is.

It shows up in early-stage companies experimenting with new pricing before they’ve hired a finance lead. It shows up in growth-stage companies layering flexibility on top of systems built for subscriptions. It shows up in larger organizations where complexity is spread thinly enough that no one owns it end to end.

The details change. The root cause doesn’t.

Whenever flexibility outpaces operational design, the same symptoms appear. Manual work increases. Confidence in the numbers erodes. Teams slow down not because they lack ambition, but because they’re compensating for systems that were never meant to behave this way.

By the time this becomes visible at the leadership level, it’s usually already expensive to fix.

Where the Narrative Meets Responsibility

There’s no shortage of narratives about where software is going. Some of them will be directionally right. Many won’t survive contact with reality.

What matters more than being early to a narrative is being honest about the work it creates. Especially in areas that touch revenue, customers, and trust.

The companies that will navigate the next phase well are not the ones chasing replacement stories. They’re the ones willing to take responsibility for how their systems behave under pressure. When usage is uneven. When contracts are messy. When automation reaches its limits.

That’s not a rejection of progress. It’s a commitment to making it operable.

And that’s the part of the future that rarely fits into a headline, but always shows up in the numbers.