- If AI can help anyone create and ship a single-purpose tool, businesses built around one use will find it harder to sustain long-term value and are at risk.
- While DIY AI tools can fix specific issues quickly, they don’t naturally deliver scale, security, governance, or the broader capabilities that businesses rely on as they grow.
- AI may lower the barrier to creating software, but it will lead to an increase in demand for trusted companies that can help organisations manage that software.
- The companies that succeed will be the ones that have platforms to help businesses manage the complexity AI creates.
Earlier this year, advances in AI agents triggered yet another SaaSpocalypse moment. SaaS stocks fell across the UK and US as markets began questioning whether businesses would continue paying for software when AI has removed the barriers to building it.
This concern is understandable; if AI makes the creation of software cheaper and easier, won’t the value of software companies fall?
To the contrary, in just a few months the SaaSpocalypse is already over. Recent market movements suggest investors have come to a different conclusion. AI will change what is considered valuable for SaaS businesses. Safe operations at scale retain tremendous value where mere feature creation has been commoditised.
AI is exposing SAAS’ weaknesses
AI is exposing a reality many are starting to recognise: not all software businesses are created equal.
Prior to the AI revolution, software companies were built around the development of features to solve a specific problem. Replicating those capabilities called for substantial engineering effort, creating barriers to competition. Features were a moat, forcing competitors to replicate and spend. That portion of the cost of goods has effectively been driven to zero as AI has lowered those barriers.
If AI can help anyone create and ship a single-purpose tool, businesses built around one use will find it harder to sustain long-term value and are at risk.
Features that used to require dedicated engineering teams and hours of effort can now be built, copied, or recreated by AI, sometimes in less time than it takes to make a cup of tea. This revelation has left many questioning whether most software businesses will stand the test of time. It has created a distinction between software features and software platforms. Features solve specific problems; platforms manage complexity.
Building software is easy, running it is not
The SaaSpocalypse was fuelled by the assumption that if AI made building software easier, businesses would stop buying software altogether. However, building software and operating it are completely different things.
While DIY AI tools can fix specific issues quickly and pragmatically, they rarely go beyond that. They don’t naturally deliver scale, security, governance, or the broader capabilities that businesses rely on as they grow.
Organisations that go beyond narrow functionality and have built out platforms can thrive. Customers want entire ecosystems ranging from integrations and experimentation to compliance and operational resilience. In other words, they are purchasing an enduring capability rather than a tool.
Take a customer relationship management system as an example. It isn’t valuable because it stores customer data. Its value lies in the controls, integrations, and governance frameworks that make entire organisations dependent on it.
It’s the same principle for software companies. While AI may lower the barrier to creating software, it will lead to an increase in demand for trusted companies that can help organisations manage that software. The challenge for businesses is whether they can operate what they build safely and effectively at scale.
Trust is the new competitive advantage
As organisations adopt AI, they face new challenges around data privacy, regulatory compliance, and model behaviour. Organisations need visibility into how AI systems are making decisions and confidence that changes can be deployed safely, as well as assurance that innovation is not introducing unnecessary risk.
Increasingly, customers are evaluating companies on their ability to manage risk, maintain control, and operate at scale. Capabilities such as audit trails, security controls, and proactive monitoring are just as important as the features themselves.
This need is only becoming more pronounced as AI accelerates software development. Whilst the technology enables teams to develop and deploy faster than ever before, it also leads to an increased risk of outages and compliance issues.
The SaaS providers best positioned to succeed will be the ones who have ecosystems set up to enable customers to innovate quickly while continuing to maintain trust, visibility and control.
Which software categories will succeed?
Following the ‘SaaSpocalypse’ there are software businesses that will emerge stronger from the AI boom than others.
The winners of sustainable value include data platforms, security platforms, observability tools, and developer infrastructure providers. Each serves a different purpose, but they all have one thing in common: they have broader, stronger ecosystems which allow organisations to govern AI systems as well as manage risk and deploy new capabilities safely at production scale.
As AI adoption increases, these providers will only become more valuable. With each new development, the need for secure data, reliable monitoring, and safe rollout only grows. Fundamentally, the more AI that organisations adopt, the greater the demand for the platforms that keep those systems running reliably.
What AI means for the future of SaaS
Reports of SaaS’ demise have proven premature, yet AI is undoubtedly causing a market shake-up. However, instead of the extinction event expected, AI has merely caused the landscape to shift. While some software categories will face pressure as capabilities become easier to replicate, others will thrive as AI increases demand for platforms that help organisations operate more effectively.
The companies that succeed will be the ones that have platforms to help businesses manage the complexity AI creates.
Cameron Etezadi is the CTO at LaunchDarkly.
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