Glean just crossed $300M in annual revenue, tripling its numbers even as Microsoft, Google, and other giants piled into enterprise AI search. The key to their growth is positioning themselves as the tool that helps companies cut their AI spending, not add to it.
Instead of selling yet another AI product that inflates budgets, Glean is winning deals by showing how it consolidates other tools and reduces overall AI costs. It is a smart pivot in a market where CFOs are starting to ask harder questions about AI ROI. This approach highlights a critical reality for enterprise software. Companies no longer want to see clear cost savings and efficiency gains, not just capabilities.
This matters because it signals a shift in how enterprise AI tools need to sell themselves. The "AI will transform everything" pitch is wearing thin. As the original outlet noted, this shift forces vendors to prove they can replace three other tools while delivering better results. The next wave of winners will be those that demonstrate consolidation, not expansion.
The fact that Glean is growing this fast while tech giants flood the category shows there is still room for focused players who solve specific problems well. Enterprise search might not be sexy, but it is essential. Companies will pay for tools that actually work across their entire stack. This suggests that niche dominance is still viable against infrastructure giants.
For anyone building or buying AI tools, the lesson is clear. The next wave of enterprise AI winners won't be the ones with the most features. They will be the ones that prove they can replace three other tools while delivering better results. This is a definitive pivot from capability to utility.
What this means for you
Stop evaluating AI tools on feature lists. Evaluate them on consolidation potential. Try this prompt with your AI assistant to audit your current stack: "Analyze my top five monthly software subscriptions. Identify overlaps and suggest one AI tool that could replace at least two of them to reduce total cost while maintaining core functionality."
