Software Stocks Extend Losses as AI Spending Doubts Deepen

The technology sector's brutal start to 2026 is accelerating, with software companies bearing the brunt of a second wave of selling as investors question whether artificial intelligence investments will ever deliver promised returns.

The renewed selloff comes as finance chiefs across the industry face mounting pressure to justify ballooning AI infrastructure costs while revenue growth remains elusive. For CFOs who spent the past year defending aggressive AI capex programs to skeptical boards, the market's verdict is increasingly harsh: show us the money, or watch your multiple compress.

The timing is particularly awkward. Many software companies are now locked into multi-year cloud computing commitments made during the AI euphoria of 2024 and early 2025, when the prevailing wisdom held that any company not "going all-in" on AI would be left behind. Those commitments are now hitting income statements just as investors demand proof of return on investment.

The pattern mirrors the post-pandemic software correction of 2022, but with a crucial difference: back then, companies could blame macro conditions and promise growth would return. This time, the issue is more fundamental. Investors are questioning whether AI-powered features command the pricing power that justified the spending spree, or whether they're becoming table stakes that customers expect for free.

The finance implications are stark. Software companies that previously traded at premium multiples based on AI positioning are seeing valuations compress toward their legacy peers. The implicit message from the market: AI capabilities alone don't justify a premium unless they're demonstrably driving incremental revenue or margin expansion.

For corporate development teams, the selloff creates both opportunity and peril. Valuations are more attractive for acquirers with cash, but integration risk is higher—it's harder to underwrite synergies when the target's AI investments may not pay off. M&A lawyers are already seeing more earnout structures and performance-based consideration as buyers hedge their bets.

The broader question for finance leaders is whether this represents a temporary reset or a more permanent repricing of software economics in an AI-saturated market. If AI features become commoditized faster than anticipated, the unit economics that justified years of investment may never materialize. That's a problem not just for software vendors, but for every CFO who's been asked to approve AI transformation budgets based on vendor promises.

The selloff also exposes a tension that's been building in finance departments: the gap between what AI vendors promise in demos and what actually ships. Every CFO has sat through the pitch where the software "practically runs itself" and "pays for itself in months." The market's current skepticism suggests investors are finally demanding the same proof of value that finance teams have been asking for all along.

What happens next likely depends on upcoming earnings calls. If software companies can point to concrete examples of AI driving pricing power or operational leverage, the selloff may prove temporary. If the narrative remains aspirational, expect further multiple compression—and more uncomfortable conversations between CFOs and their boards about sunk costs versus future commitments.