Why talk of the 'SaaSpocalypse' misunderstands enterprise software

A current narrative sweeping parts of the tech sector claims AI agents will fundamentally replace enterprise software. Some say we are heading towards a ‘SaaSpocalypse’: a future where businesses rely on AI to generate workflows, applications and business processes on demand.

However, what we’re actually seeing is disruption, not complete annihilation. In particular, vertical, industry-specific SaaS will be essential for the reliability of autonomous AI.

The role of vertical and horizontal ERP

For years, the enterprise software market rewarded breadth. Platforms are broad enough to support almost every industry and use case. These horizontal ERP platforms serve many industries, providing general business functions such as finance, HR and procurement that are suitable for almost any organisation.

Vertical ERP systems, on the other hand, are built around the operational realities of specific industries, where workflows, compliance requirements and production logic vary enormously.

This distinction matters because AI becomes far more valuable when it operates within a rich operational context. Vertical platforms are encoded with deep logic and the workflow complexity specific to their industries. General-purpose AI models cannot easily replicate this level of specificity.

AI agents are only as good as their foundations

AI agents are only as useful as their foundations: data and context. Vertical SaaS provides years of operational history, enabling agents to make precise and reliable decisions. In enterprise environments, organisations cannot afford the mistakes that arise when AI operates without deep domain knowledge.

For example, a generic horizontal AI system might identify that a manufacturer is carrying excess inventory and recommend reducing stock levels to improve cash flow. On paper, this may appear rational. But a vertical industry system may understand that a particular component has long lead times, strict regulatory certification requirements or seasonal supply constraints. Cutting inventory in that environment could halt production for weeks or create compliance risks.

Similarly, in food manufacturing, a general-purpose AI agent might optimise production scheduling purely for efficiency, without understanding allergen segregation requirements, cold-chain constraints or batch traceability obligations. A vertical platform built for that industry already contains those operational rules and historical context. This ensures AI recommendations are relevant to the realities of the business.

Systems of record become systems of context

AI is not removing the need for enterprise systems but changing what those systems must become. ERP platforms were traditionally viewed as systems of record where organisations stored data and managed workflows. Increasingly, they are becoming systems of context for AI orchestration.

An AI agent cannot reliably optimise a manufacturing line without understanding production constraints, inventory dependencies, supplier relationships, maintenance schedules and regulatory requirements. It cannot make intelligent procurement decisions without understanding pricing models, logistics constraints and historical buying behaviour.

This context already exists within vertical ERP systems. As generative AI becomes increasingly commoditised, differentiation shifts towards proprietary workflows, embedded industry expertise and operational precision. The value no longer sits purely in the interface layer but in the depth of understanding underneath it.

What this means for Australian businesses

This is particularly relevant for many Australian businesses, as they operate in highly specialised, asset-intensive and operationally complex environments. Manufacturers, distributors, food producers and infrastructure operators are not simply looking for AI novelty. They want resilience, continuity and measurable improvement.

Organisations seeing successful AI outcomes have highly structured operational environments with industry-specific data models. They own the critical workflows. They understand their operations in depth. And they can embed AI into real-world business environments safely and reliably.

Where the real AI opportunity is

AI will unquestionably commoditise parts of the software stack. Generic interfaces, lightweight workflow tools and standalone AI wrappers are already becoming harder to differentiate. But systems embedded deeply inside industry workflows are moving in the opposite direction. As AI becomes cheaper and more widely available, the value shifts towards the quality of the operational context underneath it.

The future of enterprise software is not about replacing systems with AI. It is about making systems intelligent enough to operate in increasingly autonomous environments. The future of SaaS will not be defined by who has the smartest chatbot but by who owns the deepest operational context. *Geoff Thomas is the Senior Vice President for Infor Asia Pacific & Japan. Based in Sydney, Thomas leads Infor’s regional business and operations across the key markets of Japan, ASEAN, ANZ, Greater China, India and Korea.

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