Artificial intelligence has received enormous attention in higher education, with universities investing in new AI tools and making them available to faculty and students. However, recent data suggest that AI has not yet become deeply integrated into everyday college teaching. A report from Instructure, the company behind Canvas, analyzed deidentified data from 19.5 million U.S. higher education users between September 2025 and April 2026. The findings show that traditional educational technology tools continue to be used far more widely than dedicated AI tools.

The most widely used learning technology tools included McGraw Hill, Watermark Course Evaluations and Surveys, Zoom, Kaltura, and Panopto. McGraw Hill reached more than 11.3 million users, while Zoom reached more than 9 million. By comparison, Google Gemini, the most widely adopted dedicated AI tool in the analysis, reached about 87,800 users across 211 institutions and did not rank among the 100 most widely used tools. This suggests that providing access to AI does not necessarily mean that faculty are integrating it into their courses.

One important challenge is the limited amount of AI training available to instructors. Separate data from Instructure show that only about 11 percent of higher education instructors have received comprehensive AI training. As faculty members gain more experience, however, some are beginning to explore how AI can move beyond concerns about academic cheating and become a tool for creating more engaging and interactive learning experiences. Sharing successful classroom practices may help institutions develop more effective approaches to AI integration.

Universities must also consider issues such as accessibility, data privacy, security, interoperability, cost, and evidence of educational effectiveness before adopting AI tools on a larger scale. About 90 percent of the 40 most widely used learning technology integrations were designed specifically for higher education, showing that established educational technologies still play a central role. Most of these tools support course content, collaboration, video instruction, administration, or productivity.

The current evidence suggests that higher education is still in the early stages of AI integration. The important question is no longer simply whether universities have adopted AI, but whether these technologies are being used effectively to improve teaching and student learning. As faculty receive better training and institutions gain more experience, AI may become a more meaningful part of the college learning environment. Ultimately, its value will depend on whether it helps students engage more actively, learn more effectively, and achieve stronger educational outcomes.