Your field-guide to AI — what it means for your job and what to do about it
College Professors & Instructors
AI is reshaping higher education from research to grading, challenging professors to rethink assessment, embrace AI-augmented research, and prepare students for an AI-driven workforce.
Current AI Tools
Turnitin AI Detection is deployed across most universities to identify AI-generated submissions, though its accuracy is debated and false positives remain a concern, particularly for non-native English speakers.
Gradescope (Turnitin) uses AI to assist with grading in STEM courses, grouping similar answers and suggesting grades. It is widely adopted in large lecture courses where grading hundreds of assignments manually is impractical.
Consensus is an AI-powered academic search engine that uses language models to find and summarize relevant peer-reviewed research papers, helping professors and students navigate the growing volume of published research.
Elicit is an AI research assistant that helps find relevant papers, extract key findings, and synthesize research across multiple studies. It is particularly useful for literature reviews.
ChatGPT, Claude, and Gemini are used by both professors and students for research assistance, writing feedback, coding help, and course material development. Many professors use AI to generate exam questions, discussion prompts, and lecture outlines.
NotebookLM (Google) creates study guides and podcast-style audio summaries from uploaded course materials, and is popular among students for exam preparation.
Essential Skills Today
Redesigning assessments for the AI era is the most pressing skill. Traditional take-home essays are no longer reliable measures of student learning. Professors need to design assignments that require original analysis, in-class demonstration, oral defense, or synthesis of personal experience.
Using AI as a research accelerator – for literature reviews, data analysis, and hypothesis generation – is becoming standard practice. Understanding AI’s limitations in academic contexts (hallucinated citations, statistical errors, lack of domain expertise) helps you use these tools effectively.
Setting clear, constructive AI policies for your courses is expected. Students need guidance on when and how AI use is acceptable, what constitutes academic integrity in an AI world, and how to cite AI assistance.
12-24 Month Outlook
AI is accelerating the pace of research. Labs that adopt AI tools for data analysis, literature review, and experimental design will produce results faster. Professors who integrate AI into their research workflows gain a competitive advantage in publishing and grants.
Curriculum development needs to evolve. Preparing students for AI-augmented workplaces means teaching them to use AI tools effectively, critically evaluate AI output, and understand AI limitations – regardless of the subject area.
Assessment innovation will continue. Expect more emphasis on oral exams, portfolio-based assessment, collaborative projects, and in-class demonstrations. The challenge is scaling these assessment methods for large courses.
5-Year Outlook
The professor role is not at risk of AI displacement, but it is under significant pressure to evolve. The value shifts from information delivery (lectures can be AI-generated or replaced by online content) to mentorship, critical thinking development, research supervision, and helping students navigate an AI-transformed world.
The BLS projects 7% growth for postsecondary teachers from 2024 to 2034 – much faster than average – with approximately 114,000 annual openings [1]. Postsecondary teachers held about 1.4 million jobs in 2024 [1].
Adjunct and lecturer positions focused primarily on delivering introductory courses face more pressure as AI tutoring systems improve. Tenured professors focused on research and advanced instruction face minimal displacement risk.
The broader challenge for higher education is demonstrating value in a world where AI can teach many subjects effectively. The human elements – mentorship, intellectual community, credentialing, research collaboration – remain the differentiators.
Action Items
Redesign one assignment this week to account for AI. Modify an existing essay or homework assignment to include elements AI cannot easily replicate: personal reflection, in-class presentation, or analysis of local or current events that AI models may not have data on.
Try using AI for your research. Use Elicit or Consensus for your next literature review. Compare the AI’s findings to your manual search. Understanding how AI research tools work helps both your productivity and your teaching.
Develop an AI policy for your courses. If you do not have one, write a clear, constructive policy on AI use. Explain what is allowed, what is not, and why. Share it with students on the first day of class.
Attend a workshop on teaching in the AI era. Many universities and organizations like EDUCAUSE offer workshops on AI in higher education. If your institution does not offer one, propose hosting one.
Incorporate AI literacy into your curriculum. Regardless of your subject area, consider adding a module on how AI applies to your field. Students need to understand how AI is changing every profession, not just computer science.
Sources
- BLS Occupational Outlook: Postsecondary Teachers — employment projections, annual openings, and job counts for postsecondary teachers, 2024-2034
- Turnitin — AI detection and academic integrity tools
- Gradescope — AI-assisted grading platform
- Consensus — AI-powered academic search engine
- Elicit — AI research assistant for literature reviews
- NotebookLM — Google’s AI research and study tool
- EDUCAUSE — higher education technology organization