AI Is No Longer a Pilot for FactSet. It Cut 10% of Its Tech Workforce to Prove It.

FactSet's Q3 FY2026 earnings call on July 1, 2026 was not a strategy update. It was a results report and the most commercially significant disclosure was the monetization gap between AI and non-AI clients. Quarter over quarter, ASP growth among clients using FactSet's AI solutions was 50% higher than for the rest of the book. More than 10% of ASV growth this quarter came directly from AI SKUs, up from virtually zero a year ago. Ninety percent of FactSet's top 50 clients now use four or more FactSet AI solutions. "One of the top 10 literally doubled their data subscriptions with us because of AI," said CEO Sanoke Viswanathan ." A top hedge fund grew 6x with us, again because of our MCP delivery." MCP Is the Growth Engine FactSet's Managed Content Processor (MCP) is a cloud-based infrastructure delivering content and analytics via APIs, the most operationally significant AI product in the earnings call. API call volumes grew 13x quarter over quarter. Over 450 clients are now actively engaged under contracts or trials and over 20% of the top 100 clients are using MCP on a paid basis. FactSet is available as a first-class data connector on all major frontier AI platforms including Anthropic, OpenAI, Google, and Microsoft, according to the report. Viswanathan said that whenever a deal involves an MCP component, 90% of the time FactSet sees contract value improvement. He also noted that AI consumption through MCP is leading to upsizing of existing products, describing it as a multiplier effect on the existing business. AI Is Cutting Headcount in Engineering and Data Operations Coding agents now author 27% of committed code in the engineering teams using these tools. Committed lines of AI-written code grew almost 10x quarter over quarter. Coding-related token use grew 5x in the same period. The consequence was seen. FactSet initiated a 10% reduction in its technology workforce during the quarter, directly citing AI-assisted coding productivity gains as the driver. In data operations, where new AI tools have been fully implemented, operator touch time for data table extraction has been reduced by more than 50%. The FactSet Fundamentals team, one of the company's largest datasets, was reduced by 5% after multiple data pipelines were consolidated into one using AI. In client services, approximately 4,000 bankers used digital onboarding tools in Q3. The capacity unlocked resulted in a 22% quarter over quarter increase in live user interactions by consultants and a 5-point increase in Net Promoter Score among the junior banker population. FactSet Intelligence and the Banking Workflow Transformation FactSet formally launched its AI solutions with FactSet Intelligence, a three-layer platform covering a trusted data ecosystem built on MCP, governed agentic infrastructure for the Workstation, and intelligent workflows for hybrid workforces. The most concrete product disclosure in the third layer is the capital markets intelligence suite for investment bankers. Senior bankers can now send a natural language email to an AI agent describing what they need and receive comparable company analysis and deal precedents built on current FactSet data, automatically generated and delivered back. What previously took hours or days now takes minutes. The suite is in active or pipeline trials at over 30 of the top 100 banking clients, according to the report. The Google Cloud partnership announced June 30 also received new details on the call that was not in the original announcement with FactSet now receiving preferential token pricing as part of the contract. Viswanathan described this as reducing the cost of AI delivery across FactSet's product suite, a commercially meaningful structural advantage as token costs have become a significant line item in FactSet's operating expenses. Average contract lengths also extended by roughly 30% during the quarter as clients shift from seat-based to enterprise agreements, with no price compression. Clients are paying more for longer, according to Viswanathan, because they are treating FactSet as mission-critical AI infrastructure.

AI Is No Longer a Pilot for FactSet. It Cut 10% of Its Tech Workforce to Prove It.

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