Is the stock market facing a ‘SaaS-pocalypse’? What implications could it have?

What’s behind the ‘SaaS-pocalypse’?

Since AI first grabbed public attention with the release of ChatGPT, investors have eagerly piled into tech stocks, driven by an excitement for its revolutionary potential. However, that enthusiasm faced a challenge last year as investors started to assess the impact of AI on software companies—an integral part of the technology landscape.

This anxiety escalated in early 2026, particularly when the US-based AI company Anthropic released capabilities that enabled users to interact with their computers through natural language for intricate tasks like data analytics and expense management.

Such features pose a considerable threat to high-cost SaaS applications that traditionally require users to navigate complex software interfaces. The risk of software becoming redundant is evident, echoing how digital photography led to Kodak’s decline and how touchscreen technology undermined Blackberry’s market dominance.

Investors are also voicing concerns about the viability of the “per seat” pricing model, commonly used in the SaaS industry, wherein companies charge fees based on the number of users accessing the software. As noted by investment firm Morningstar, in a future dominated by AI, “if one person can now perform the work of two, the number of required user licenses will decrease.”

Australia’s technology index, which includes numerous prominent software firms like Xero and WiseTech, has seen a decline of approximately 17% since the start of the year, and over 25% in the past six months. This sentiment has permeated multiple sectors as investors speculate whether functions like portfolio management, tax planning, insurance assessments, and data analytics could soon be automated by AI, potentially making specialized firms in these fields obsolete.

Are the concerns overblown?

Luke McMillan, head of research at Sydney’s Ophir Asset Management, believes that investors have “shot first and asked questions later,” hastily offloading SaaS businesses without fully understanding the ramifications.

According to McMillan, the next critical phase will involve discerning which companies will be adversely affected by AI developments. Investment experts frequently discuss “economic moats,” which are the protective measures a company employs to shield its profits from competitors and market fluctuations.

McMillan explains that some software firms possess unique advantages, such as proprietary data that AI cannot access—setting them apart from those based on publicly available information that could be easily replicated.

“Certain companies have established moats that could safeguard them from the disruptive capabilities of AI and may even harness AI to enhance their service offerings,” he asserts.

Lochlan Halloway, equity market strategist at Morningstar, acknowledges the knee-jerk nature of the mass sell-off but also warns of the risk that investors might downplay AI’s potential threats.

“In this evolving landscape, we will witness both winners and losers,” Halloway notes. He adds that firms with exclusive data, intricate systems that are tough to replicate, and integrated software that connects multiple stakeholders are likely to fare better amid disruption.

“While we want to avoid dismissing the risks posed by AI to the SaaS business model, our focus is on identifying companies that are more likely to withstand these challenges,” he affirms.

What happens next?

The current era marked by AI advancements and the potential return of Donald Trump to power has fostered a climate of volatility within global markets, characterized by frequent shifts between optimism and fears surrounding trade conflicts and technology bubbles.

These narrative-driven market fluctuations—where stories influence investment strategies—differ significantly from earlier periods when stock movements were more closely tied to the actual earnings of companies.

The “SaaS-pocalypse,” alongside the AI boom, “sell America” trends, and so-called “Taco” trades, which play on the notion that Trump tends to backtrack when facing tariff-related market turmoil, exemplify the narrative-driven nature of investment decisions.

Investment experts predict that markets will ultimately adjust to accurately reflect company valuations in an AI-centric world, similarly to how they recalibrated after the tech boom and crash of the late 1990s and early 2000s.

Halloway highlights the contradiction between apprehensions regarding a tech bubble and the plummeting stock prices of certain software companies. This paradox arises because fears about a bubble stem from the belief that AI’s promises may fall flat, while the latter hinges on AI’s potential to act as a significant disruptive force.

“It appears markets are grappling with fears of both insufficient AI and an overabundance of it simultaneously,” he points out.