Glean Must Prove Concrete ROI

This churn signal shows that enterprise AI is shifting from easy pilot money to harder operating budgets. Glean can no longer win by being an interesting search and chat layer alone. It has to prove that deployments change a measurable workflow, cut software spend, or remove manual work. That is especially important because Glean sells into broad, cross company rollouts that touch many systems and can stall if usage stays shallow.1 2 3 4

• Glean’s own product arc reflects that pressure. It moved from enterprise search into no code agents for SDR, compliance, and finance workflows, because simple search savings are soft while replacing separate tools or automating a task creates a cleaner budget case.2 3
• This is also why implementation matters so much. Horizontal AI tools often need data connectors, permissions, and workflow setup across Slack, Jira, Salesforce, SharePoint, and other systems. Hebbia describes enterprise AI adoption as operational change management, not just software provisioning.4 5
• The closest comparables point the same way. Zapier says many enterprises get stuck at one shot prompting, then need playbooks and deterministic workflows to reach deeper adoption. Hebbia sells fewer seats at much higher prices for narrow, high stakes work where ROI is easier to tie to output.4 5

Going forward, the winners in enterprise AI will look less like chatbot vendors and more like workflow vendors. Glean is already moving there with agents, ROI tooling, and a cost reduction pitch. If it can tie deployments to retired software and completed work, the budget gets stickier and churn should fall.2 6 7