Higher education has spent years debating how artificial intelligence will impact teaching. But a more urgent issue is emerging: what happens when AI starts performing tasks historically done by university employees?
This shift transforms AI from an educational tool into a labor technology, raising complex questions. Who decides if AI can replace faculty work? How does it affect staffing, ownership of academic materials, and faculty evaluations? If AI speeds up work, who benefits from the saved time? These questions are now practical realities.
AI reaches the bargaining table
Labor unions are already addressing AI in collective agreements. At the City University of New York, the 2023-27 agreement between CUNY and the Professional Staff Congress mandates that only instructional staff can be the instructor of record, preventing AI from taking over teaching roles. It also establishes a committee to discuss AI‘s impact on employment.
Similarly, Miami University in Ohio signed a memorandum of understanding with its faculty alliance in June 2024, allowing both parties to propose guidelines for AI tools. These agreements highlight the growing recognition of AI as a labor issue.
When AI affects workload, job security, or intellectual property, it becomes a legitimate bargaining concern. For instance, the Community Colleges of Spokane’s 2025-28 contract acknowledges AI as a rapidly evolving issue, requiring ongoing discussions.
Internationally, academic unions are taking similar steps. The Canadian Association of University Teachers (CAUT) approved a policy on generative AI in November 2025, addressing job security, workload, and intellectual property. The University and College Union in the UK emphasizes that AI implementation should involve collective bargaining and protect staff-created intellectual property.
Redefining academic labor
The core labor question is whether AI can perform work traditionally done by faculty. Universities have long dealt with outsourcing, but AI introduces a new challenge: work may shift into computational systems rather than to other employees.
For example, AI can handle routine academic advising, generate instructional materials, and provide preliminary feedback. This doesn’t necessarily replace professors but reconfigures their roles. Faculty might design courses while AI handles routine tasks, with professional staff stepping in only when needed.
This shift is particularly relevant to contingent and contract academic staff, whose positions may already lack the employment protections afforded to permanent faculty. The CAUT policy highlights the vulnerability of contract academic staff.
The real question isn’t whether AI will replace professors, but which parts of academic work become easier to remove, reorganize, or devalue once machines can perform cognitive tasks.
Faculty must review and verify AI-generated materials, ensuring accuracy and assessing for errors or bias. This process can be time-consuming, raising questions about workload allocation.
For instance, a professor might save time by using AI to generate a teaching resource but then spend hours verifying its reliability. Instructors using AI-assisted feedback remain responsible for ensuring pedagogical appropriateness. This additional labor must be accounted for in workload models.
When AI reduces the time spent on repetitive tasks, it creates a productivity dividend. The distribution of this saved time is critical.
Intellectual property further complicates the issue. Universities possess vast amounts of faculty-generated materials, from lectures to research outputs. Using these to train AI systems raises questions about ownership. The CAUT and UCU policies emphasize that staff-generated materials should not be used without consent.
At the global level, Education International convened more than 200 union leaders, educators and experts in Brussels in December 2025 for its first global conference focused specifically on AI in education, with additional participants joining remotely. Its conference report shows that AI and the future of educational work are now part of the international trade-union agenda.
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