After years of speculation about the impact of artificial intelligence (AI) on the market, a new concern has emerged among investors: the possibility that the hype surrounding AI is not just a fleeting trend. The phenomenon, referred to as the “SaaS-pocalypse,” stems from fears that rapidly advancing AI technologies could render many software-as-a-service (SaaS) applications obsolete. This shift raises a fundamental question: why would businesses continue to invest in specialized software solutions for accounting, sales analytics, logistics, or project management when they can simply utilize advanced AI tools like ChatGPT, Claude, or Gemini?
The ramifications of this concern are already being felt, particularly in Australia, where the sell-off has erased billions from the valuations of leading software firms, including accounting giant Xero and global operating system provider WiseTech. In the U.S., Atlassian Corp, known for its collaboration tools, has seen its shares plummet by 50% since the beginning of the year, resulting in a staggering loss of nearly $US8 billion in wealth for its co-founders, Mike Cannon-Brookes and Scott Farquhar.
The roots of the “SaaS-pocalypse” can be traced back to the introduction of AI technologies into public discourse, notably through ChatGPT, which sparked investor enthusiasm for tech stocks due to the potential transformative power of AI. However, this optimism began to fade last year as concerns mounted around how AI advancements could significantly disrupt the software industry—a key player in the tech sector.
These fears intensified in early 2026 following the launch of new AI tools by the U.S.-based Anthropic, enabling users to execute complex tasks like data analysis and expense tracking through natural language interactions. This development poses a serious threat to conventional SaaS products that traditionally require users to navigate complex software interfaces and programming languages.
Historical comparisons suggest that some software could potentially meet a fate similar to that of Kodak with the advent of digital photography, or Blackberry when touchscreens emerged. Moreover, the viability of the prevalent “per seat” charging model in SaaS—where companies charge for each individual user—has come under scrutiny. As noted by Morningstar, in an AI-optimized future, the model could falter, as a single employee may accomplish the tasks of multiple individuals.
The technology index in Australia has suffered, dropping approximately 17% since the year’s onset and over 25% in the past six months. This unease has permeated other sectors as well, with investors contemplating the feasibility of automating tasks typically managed by specialists in portfolio construction, tax planning, insurance, and data analytics.
However, some experts caution against overreacting. Luke McMillan, head of research at Ophir Asset Management, emphasizes that the mass sell-off of SaaS enterprises may not be warranted. He suggests that a more measured approach is needed to identify which companies might genuinely be adversely affected by emerging AI technologies. McMillan refers to the concept of “economic moats,” which protect a company’s profits from competition and disruption. He points out that companies leveraging proprietary data inaccessible to AI tools could maintain a competitive edge.
Lochlan Halloway, equity market strategist at Morningstar, concurs, noting that while the rush toward selling was impulsive, there remains a real danger of underestimating the threat posed by AI. Halloway identifies firms that possess unique data, complex systems, and software that effectively connects multiple stakeholders as better suited to navigate potential disruptions.
Looking to the future, the combination of the AI era and geopolitical factors, such as the second term of Donald Trump, has created a climate of heightened volatility in global markets. Investors have been oscillating between optimism and anxiety, influenced by the narratives surrounding AI, trade wars, and the tech bubble.
Market analysts believe that, similar to the tech boom and subsequent bust in the late 1990s and early 2000s, the markets will ultimately adjust to appropriately value companies in an AI-driven landscape. Halloway highlights a puzzling contradiction in the current market climate, where fears around both insufficient and excessive AI simultaneously drive investment decisions, indicating a complex interplay of risk and opportunity moving forward.
