In 2026, AI will become a routine part of technology transfer operations. Many TTOs already use AI to support disclosure intake, prior art review, drafting assistance, portfolio analysis, and commercialization outreach. The challenge is no longer whether these tools work, but how to integrate them into institution-wide workflows that support accountability, preserve faculty trust, and hold up over long time horizons.
This report examines how university tech transfer operations are likely to evolve as disclosure volumes grow, staffing remains constrained, and expectations for transparency and proof of diligence increase. It argues that high-performing TTOs will move away from isolated AI uses and toward repeatable, well-documented workflows that span disclosure, patenting, commercialization, and licensing.
Inside the report you'll learn: