There’s a shift happening in the software industry – one that could have major implications for how companies buy, use, and think about technology.
For the past two decades, Software-as-a-Service (SaaS) has been the dominant model for delivering business software. It replaced expensive on-premise installations with cloud-based subscriptions, unlocking access and scalability. For a time, it looked like the final evolution in software delivery. But today that model is being tested by something new: agentic AI.
This isn’t just about adding smarter features to existing platforms. It’s about a different way of thinking – one that’s built on automation, intelligent workflows, and outcomes rather than access. And it’s catching on fast.
The Structural Limits of SaaS
I’ve seen first-hand how SaaS models can both unlock value and introduce friction. Over time, several structural issues have emerged.
First, there’s SaaS sprawl. Large organisations now deploy hundreds of applications, many with overlapping or highly specialised use cases. Managing this landscape is both expensive and operationally taxing. Licences go unused, tools get abandoned, and integration becomes a persistent challenge.
Second, the common per-seat pricing model increasingly feels misaligned with how value is actually delivered. A business might be paying for access across an entire team when, in reality, only a handful of users rely on the tool. That creates waste and encourages cost-cutting rather than value optimisation.
Then there’s integration fatigue. SaaS platforms often don’t talk to each other natively. Businesses end up cobbling together workflows across different tools, leading to duplication and data silos. One recent study suggested knowledge workers spend around 12 hours a week reconciling information between systems. That’s lost time and lost opportunity.
Finally, there’s a limit to how far traditional SaaS platforms can go in reducing manual effort. AI has been added around the edges – smart suggestions, simple bots – but the core structure remains reliant on human input.
A New Model: Agentic AI
Agentic AI represents something more fundamental. Rather than providing a platform for users to do tasks, it can do the tasks itself. These systems rely on autonomous agents – software programs that can take action, make decisions, and improve over time without constant human oversight.
There are a few key characteristics that differentiate agentic platforms from traditional SaaS:
- Outcome-Driven Automation: These systems are designed to execute tasks from start to finish – whether it’s processing invoices, resolving customer issues, or conducting due diligence. The value lies in completion, not access.
- Cross-Platform Functionality: Agentic systems can pull from multiple sources, navigate between tools, and act as an orchestration layer across different data environments. They don’t require everything to be under one roof.
- New Pricing Models: Rather than charging for user licences, agentic systems are shifting toward usage- and outcome-based pricing. You pay for what the AI does, not just for using the software.
- Continuous Learning: These agents aren’t static. They adapt and refine their outputs over time, meaning they can grow more valuable the longer they’re used.
- Cultural Shift: Adopting this kind of technology often comes hand-in-hand with a broader move toward data-driven, leaner, and more adaptive organisational cultures.
Implications for SaaS Companies
To compete with the rise of AI, SaaS providers will need to evolve their services to better meet customer expectations. This means rethinking not just product features but the entire delivery model – from pricing and integration to automation and long-term value creation
For traditional SaaS businesses, this shift represents both a threat and an opportunity. It’s no longer enough to be the best dashboard or the most user-friendly UI. The next wave of competition will be measured by who can remove friction, automate outcomes, and offer tools that disappear into the background.
Some SaaS firms are already responding – embedding more advanced automation, shifting towards outcome-based pricing, and opening up APIs to play nicely with agentic platforms. Others may find themselves disrupted unless they reposition their offering.
There’s also room for partnership. Not every SaaS company needs to become an AI company overnight. But aligning with platforms that enable agentic behaviour – through interoperability, shared data layers, or white-labelled intelligence may be key to remaining relevant.
Looking Ahead
It’s too early to declare the end of SaaS. But it’s clear that the model is being redefined. The market is beginning to demand something beyond access – a shift towards tools that think, act, and deliver.
From an investor and operator’s perspective, this opens up exciting territory. The companies that succeed will be those that reduce complexity, lower operational overheads, and price according to actual value delivered.
As this space evolves, expect to see a growing divide: between tools that assist and tools that act. The former will still have their place – but the latter may well define the future of enterprise software.