Software Stocks: A Behavioral Selloff Driven by AI Fear, Not Fundamentals

The market is sending a clear message: fear is overriding value. Software stocks are off to their worst start since 2022, with a key group of SaaS companies down 15% so far this year. This follows a 11% drop in 2025, creating a pattern of selling that defies basic financial logic. The trigger was a new AI tool from startup Anthropic, released just last week. Its quick development and capabilities reignited deep-seated anxieties about disruption, sparking a sharp, herd-like selloff. This is a textbook case of how new, uncertain information can trigger panic, causing investors to sell regardless of underlying fundamentals.

The disconnect is stark. While the stocks are tumbling, their valuations are hitting record lows. The Morgan Stanley basket of software companies now trades at just 18 times earnings projected over the next 12 months. That figure is well below its own historical average of more than 55 times. In other words, the market is pricing these companies as if their future growth is in serious doubt, even as their core business models-recurring revenue, high margins-remain intact. This is a classic manifestation of loss aversion and herd behavior: the fear of missing out on a potential AI-driven collapse is outweighing the rational appeal of buying a beaten-down asset.

Analysts note the psychology at play. Many investors are now entrenched in bearish positions, assuming zero catalysts for a re-rate exist right now. They see no reason to buy, no matter how cheap the stocks get. This cognitive dissonance-holding onto a negative view despite mounting evidence of bargain pricing-creates a self-reinforcing cycle. The recent selloff has only widened the gap between software and other tech sectors, where fundamentals and growth visibility are clearer. For now, the market's collective behavior is driven by uncertainty and fear, not by the numbers on a balance sheet.

The Psychology of the Selloff: Loss Aversion and Herd Behavior

The market's reaction is a textbook case of two powerful behavioral biases colliding. First, there's loss aversion. The pain of potentially losing money to AI disruption is psychologically twice as powerful as the joy of a comparable gain. For investors, the fear of being caught holding software stocks as AI renders them obsolete outweighs the rational appeal of their current bargain valuations. This isn't about today's profits; it's about the perceived risk of tomorrow's catastrophic loss.

This individual fear quickly becomes collective action through herd behavior. The sell-off isn't isolated. It's broad and synchronized, with leaders like Adobe and Salesforce down more than 20% of their value in the last year. When a few investors start selling, others see the movement and follow, not because they've done new analysis, but because they fear being left holding the bag if the narrative shifts. It's the financial world's version of a crowd rushing to the punch bowl, assuming the stampede must be for a reason.

The result is a dangerous feedback loop. Selling begets more selling. As stocks fall, the fear of further losses intensifies, driving more investors to exit. This dynamic is amplified by the current narrative, where skepticism over early-stage AI products and rising competition makes the future look murkier. The market is pricing in a worst-case scenario, not because the fundamentals have changed, but because the collective psychology is now dominated by the fear of loss and the instinct to follow the crowd.

Sector Divergence: Winners and Losers in the AI Narrative

The AI fear narrative is not a monolithic force. It is carving out distinct winners and losers within the software sector, exposing a deep behavioral split. The selling pressure is concentrated where AI disruption is perceived as most direct: front-office applications. Companies like Adobe and Salesforce, whose core products are in creative and customer relationship management, have been hit hardest. Their stocks are down more than 20% of their value in the last year, as investors worry that AI-driven productivity tools will reduce demand for traditional services. This is a classic case of threat perception driving valuation, regardless of current profitability.

By contrast, back-office and infrastructure software appears more resilient. These businesses often provide essential, less-expendable services, and their financials can look robust even in a downturn. Fortinet stands out, for instance, with a 228% return on equity and 32% profit margins. Its stock may be down 17% over the past year, but its fundamentals remain "rock solid," offering a stark counterpoint to the narrative of universal decline. This divergence shows that the market's fear is selective, focusing on specific business models it sees as vulnerable.

Analysts are responding with a clear barbell strategy, reflecting this selective optimism. Morgan Stanley, for example, is not betting on a broad sector rebound. Instead, it is combining vendors it sees as well positioned within its "AI Success Framework" with companies showing idiosyncratic growth acceleration. This means favoring firms like HubSpot and BlackLine, while also highlighting niche players like Navan. The message is that in a fearful market, the path to outperformance lies in identifying the few companies where the AI story is already playing out positively, not in buying the entire sector at a discount. The behavioral split is now a strategic one.

Catalysts and Risks: When Will the Narrative Shift?

The behavioral selloff hinges on a single, unproven thesis: that AI will destroy software business models. The market's fear is a self-fulfilling prophecy that can only be broken by a visible counter-narrative. The primary catalyst for a shift is clear: tangible, company-specific AI-driven revenue upside. As Morgan Stanley notes, the burden has shifted to proving that application software will act as the primary delivery layer for AI, expanding total addressable markets and lifting growth. Until incumbent vendors demonstrate this monetization in their quarterly results, the fear narrative will persist. The market needs to see the bull case in the numbers, not just in management presentations.

The key risk, however, is that the market's struggle to process AI change will prolong the volatility. The recent sell-off, triggered by a new AI tool, shows how quickly sentiment can swing on uncertain news. Some analysts warn the selloff is "silly," driven by investors stubbornly clinging to the AI bear thesis. This cognitive rigidity means the market may overshoot again if any new AI development-positive or negative-fuels fresh uncertainty. The risk isn't just a slow grind lower; it's a series of sharp, irrational swings as the collective psychology grapples with an unprecedented pace of technological change.

This sets up a near-term test. The coming quarters are critical. Investors must watch for two things: first, whether companies can demonstrate tangible AI monetization in their financials, and second, whether they show margin resilience amid the fear. The divergence is already visible, with winners like Fortinet showing 228% return on equity and 32% profit margins while others struggle. If the market sees a pattern of AI-driven growth and profitability, the narrative could flip. But if earnings reports merely confirm the fear of disruption, the behavioral selloff could deepen. The catalyst is visible upside; the risk is continued narrative volatility. The next few earnings seasons will reveal which force wins.