Talk of a “SaaSpocalypse” has resurfaced, with generative AI cast as the latest disruptor threatening to gut the enterprise software stack.
According to Corlytics, for regulated industries, though, the reality is more nuanced: producing a slick answer, or even a working application, is no longer the hard part. The hard part is proving where the data came from, why a result applies, who signed off on it, and reconstructing that trail months later.
Corlytics recently discussed how the ‘SaaSpocalypse’ is here, and why AI will kill bad SaaS and why it matters.
That distinction should worry SaaS vendors whose value lies mainly in shuffling information between systems or charging for functionality that AI can now replicate in minutes. RegTech is not immune to this pressure either.
Clients increasingly ask why they can’t simply run a task through a general-purpose assistant instead of buying specialist software. Often, they can. Large language models can summarise dense regulatory text, compare document versions, draft impact assessments, and increasingly help build the workflows and agents around those tasks. That capability is genuine and growing.
But access to a powerful model is not the same as owning a controlled regulatory operating capability. A model can generate an impressive answer to a question about, say, recent regulatory changes affecting a lending business.
What it cannot do alone is guarantee every relevant regulator was monitored, confirm which document versions were used, show who validated the findings, or reproduce that evidence chain for an auditor a year later. Fluency is not provenance.
The harder, ongoing obligations, monitoring sources, owning context across jurisdictions and legal entities, controlling workflow approvals, and preserving independent audit evidence, do not disappear because the interface has become conversational.
Building version one of an AI-generated tool is getting easier; safely operating version 1,001 every day is where the real cost sits. Firms that build internally aren’t eliminating the platform, they’re choosing to become its operator.
Crucially, AI cuts both ways: specialist RegTech providers can use the same tools to sharpen classification, mapping, and delivery, raising the bar rather than lowering it. The likely shape of the next generation of RegTech is layered, with general AI assistants as the interface, specialist vendors supplying maintained regulatory intelligence underneath, and GRC platforms remaining systems of record for evidence and ownership.
Bad SaaS, built on thin workflow-wrapping, may well be finished. But platforms built on hard-to-reproduce assets, domain data, governance, and defensible process, aren’t going anywhere. AI makes software cheaper to build. It makes trusted, defensible operation more valuable, not less.
Read the full Corlytics post here.
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