Gartner cut its 2026 revenue forecast to $6.46 billion, missing Wall Street expectations of $6.71 billion, as enterprises scale back spending on external advisory services. The company's stock dropped 22% following the announcement.
The consulting segment took the hardest hit: Q4 2025 revenue fell 13% year-over-year to $133.6 million. The company attributes the decline to enterprises using internal AI tools for planning and performance assessments, work previously handled by external consultants.
The forecast caps a difficult stretch for Gartner. The stock is down 47% year-to-date, the worst performance in 20 years. The company cut $100 million from its non-research "Insights" unit in August 2025 and executed layoffs in India in September.
What's driving the pullback: 78% of CEOs are cutting costs amid recession concerns, according to recent surveys. U.S. federal spending cuts through DOGE initiatives have reduced government consulting demand. Tariffs and economic uncertainty are delaying contract renewals.
The broader context matters here. Enterprise AI spending is forecast to hit $2.5 trillion in 2026, up 44% year-over-year. But MIT research found 95% of organizations saw zero ROI from generative AI projects in 2025. Companies are choosing to build internal capabilities rather than pay for external guidance on unproven technology.
Gartner's core business model depends on multi-year subscriptions for advisory research sold to Fortune 500 firms. If clients can generate similar insights using their own AI tools, the value proposition weakens.
The company forecasts adjusted earnings of $12.30 per share for 2026, below analyst expectations of $13.53. The Insights unit, which represents the bulk of revenue, is projected at $5.19 billion versus estimates of $5.3 billion.
UBS analyst Joshua Chan noted investors will watch closely to see if contract value growth accelerates: "The softer Insights Revenue guide could suggest that the pace remains somewhat challenging."
For CIOs evaluating research vendors: this is a reminder that internal AI capabilities can reduce dependence on traditional advisory relationships. The trade-off is building that capability versus buying it. Gartner's struggles suggest more enterprises are choosing to build.