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Generative AI is rapidly transforming the landscape of higher education. EDUCAUSE's latest QuickPoll reveals the evolving attitudes and adoption patterns of this emergent technology among institutional leaders, technology professionals, and staff. This summary captures key insights from the poll, highlighting the benefits, challenges, and potential future impact of generative AI in higher education.

“Attitudes toward generative AI have improved over just the past few months, and these technologies are becoming more widely used in day-to-day institutional work.” (McCormack, 2023)

Question

How are institutions preparing to integrate generative AI into their operations, and what steps are needed to ensure effective and appropriate use?

What is Generative AI in Higher Education?

Generative AI refers to technologies that can create content, ideas, or solutions autonomously. In higher education, these tools are used for tasks such as drafting administrative documents, creating course materials, and developing strategic plans. By automating routine tasks, generative AI allows educators and administrators to focus on more strategic activities.

Why is Generative AI Important?

Generative AI has the potential to significantly streamline and enhance educational processes. It can reduce the workload of faculty and administrative staff, provide innovative teaching and learning methods, and support data-driven decision-making. However, its implementation also raises concerns about job displacement, ethical risks, and the need for robust governance structures. As the QuickPoll highlights, 83% of respondents believe that generative AI will profoundly change higher education in the next three to five years.

How is Generative AI Being Adopted?

According to the QuickPoll, 67% of respondents have used generative AI tools during the 2022-23 academic year, and another 13% plan to use them in the future. This leaves only 20% of respondents who reported that they have not used and do not anticipate using generative AI in their work. Adoption varies by role, with senior-level and instructional technology leaders being the most involved. Common uses include brainstorming, drafting documents, and designing course materials.

Generative AI use in higher education is categorized into four main areas:  

• Dreaming (brainstorming and asking questions)  
• Drudgery (drafting administrative documents and sending emails)
• Design (creating presentations or course materials)
• Development (drafting policies and developing strategic plans).  

These areas represent a broad spectrum of applications, indicating that generative AI is being integrated into both creative and operational tasks.

The Challenges and Promising Practices

Institutions face several challenges in adopting generative AI, including the need for clear policies, role clarity, and effective collaboration among departments. Only 34% of respondents reported that their institution has implemented or is in the process of implementing new or revised policies to guide the use of generative AI. This lack of clear guidelines can lead to inconsistent adoption and increase the risk of security and ethical issues.

Respondents also highlighted responsibilities that align with senior-level and instructionally focused positions, such as developing policies and guidelines for appropriate uses of generative AI, serving on institution-wide committees, advising and educating faculty, and assessing generative AI integrations with third-party tools. Effective adoption requires collaboration across different departments and clear delineation of responsibilities.

Conclusion

The integration of generative AI in higher education is accelerating, with positive attitudes and widespread usage reported among early adopters. Institutions must develop appropriate staffing, governance structures, and clear policies to harness the benefits while mitigating risks. As generative AI continues to evolve, hands-on experimentation and targeted use cases can guide institutions toward more effective and innovative applications of this technology.

Reference

EDUCAUSE QuickPoll Results: Adopting and Adapting to Generative AI in Higher Ed Tech