Unleashing Generative AI: 3 Strategies Designed for Impact

Generative artificial intelligence (AI) is one of the most rapidly adopted technologies in history.^Footnote1 Like other fast-growing disruptive technologies, AI has become a subject of ethical and technical dialogues across the higher education landscape: administrators, faculty, staff, and students are debating, discussing, and discovering the impacts of these tools on life, learning, and work. Nearly every discussion can be distilled into one foundational question: How do we realize the potential of generative AI while effectively forecasting the yet-unknown impacts of its use? The last eighteen months have revealed that integrating AI into plans for executing institutional missions is no longer optional for colleges and universities. Trustees, presidents, and chancellors around the country are exploring generative AI strategies and seeking to leverage the technology to gain a competitive advantage in the complex higher education landscape.

1. Don't Wait. Grow Your Own!

Education leaders have described generative AI as critical to their transformation efforts but have expressed concerns about its safety, security, liability, and cost. These issues have slowed institutional exploration efforts and discovery processes. Respondents of an April 2024 EDUCAUSE QuickPoll survey reported that concerns about privacy and ethics have been raised by committees and leaders at their institution, impeding any forward progress on developing a strategy to adopt AI tools.^Footnote2 Investing in the development of the dedicated teams that make up the fabric of the institution is critical for cultivating a culture that embraces innovation. Faculty are well positioned to identify emerging opportunities to apply generative AI with a high impact value across campus.

Institutional leaders should foster a culture that authentically offers space for "thinking big" and responsibly taking risks. One way to accomplish this is to intentionally pair technical and mission area practitioners (e.g., IT and student affairs) in collaborative teams charged with identifying and evaluating opportunities for using generative AI to positively impact institutional strategic priorities. Such teams should be encouraged to deconstruct how their work gets done and consider new possibilities enabled by generative AI. Focusing cross-functional teams on strategic institutional objectives can naturally deconstruct silos and foster a common understanding of the inherent potential of combining emerging technology, institutional expertise, and a shared purpose. Leaders should embrace diverse perspectives, including those of contrarians who are concerned about generative AI disrupting or devaluing their role. Promoting an open dialogue and fostering a culture of continuous, adaptive learning are critical. Generative AI will continue to evolve in rapid iteration, and colleges and universities must be agile to respond to emerging needs. Don't wait. Invest in your technical and functional teams to build the capacity and capabilities necessary to leverage this technology for the betterment of your institution.

2. Prioritize Mission-Aligned Opportunities

This is an exciting (albeit exhausting) time to work in higher education. Technological advances are providing college and university leaders with more nuanced insights about their business than ever before—opening a world of possibilities for engaging communities, students, and alumni in new ways, accelerating research findings, and improving efficiencies across campus operations. With all this exploration under way, maintaining focus is important.

Institutional leaders should create mechanisms for identifying and prioritizing mission-aligned opportunities that can generate measurable impacts on institutional objectives. Leaders can engage the entire institution by brainstorming and capturing ideas for integrating generative AI with stakeholders across the college or university. For example, AI tools could be used to generate content for marketing and outreach to prospective students; intelligent document processing could be used to simplify admissions and financial aid processes; academic advising could be augmented through course and program recommendations; and multilingual virtual assistants could help communities that have historically been excluded from higher education to participate more fully. Leaders should evaluate and prioritize ideas quickly. Once a bank of possible use cases has been generated, a structured framework can be employed to prioritize ideas based on their alignment with institutional priorities, resource allocation needs, estimated return on investment, and the level of complexity needed to launch and sustain them.

While the capabilities of generative AI can be fun to imagine and explore, institutional leaders should prioritize mission impact over technical complexity, focusing on proofs-of-concept that can scale and directly contribute to the quantifiable measures of strategic institutional goals. The greatest value of generative AI comes from its application across multiple use cases with similar characteristics. For example, the automation of business processes and intelligent document processing could benefit many areas of an institution, including human resources, student enrollment, space and resource allocation, research grant administration, and even accounting practices. This technical adaptability demonstrates the unique business value of generative AI when applied to high-value use cases. For example, one institution used the lessons learned from designing and building a course recommendation model for advisors to resolve a fraudulent application problem, generating quick value.

One way to identify proof-of-concept use cases is to find early adopters—champions from around campus who are always interested in trying something new. They enjoy problem solving and can partner quickly to identify and scope a proof-of-concept that demonstrates the power of the technology to internal stakeholders and creates an opportunity for technical teams to acquire and apply generative AI builder skills. By identifying and prioritizing clear, mission-aligned use cases in partnership with key stakeholders, higher education leaders can leverage generative AI for high impact across the institution.

3. Go Big: Insist on an Enterprise Approach to Generative AI

Given the rapid advancement of generative AI technologies, higher education leaders must take a comprehensive, enterprise-wide approach to responsibly integrating these technologies in service of their mission. An enterprise approach provides consistent review processes to expose and mitigate biases, safeguard data privacy, promote the transparency of information sources, and uphold responsible AI principles. Institutions must establish robust governance structures, rigorous testing protocols, and clear accountability mechanisms to maintain internal and external stakeholder trust.

While generative AI promises transformative benefits—including personalized learning and expanded access—its responsible implementation hinges on diligent planning, cross-functional collaboration, and an unwavering commitment to ethical practices that align with institutional values.

Developing an enterprise strategy requires a comprehensive understanding of institutional preparedness. EDUCAUSE and AWS have collaborated to develop the Higher Education Generative AI Readiness Assessment, a holistic framework to support higher education leaders in assessing their institutions. Authored by innovative thought leaders from across the country, this tool can empower higher education institutions to assess their preparedness for the responsible integration of generative AI technologies across twenty-four domains in three core areas: (1) strategy and governance, (2) capacity and expertise, and (3) infrastructure.

Higher education leaders can strategically position their institutions within the emerging generative AI era by adopting an enterprise-wide approach. This approach is not a quick fix but rather a call to build the transparent, flexible institutional framework needed to foster ongoing cross-functional alignment, consistent engagement of diverse stakeholders in envisioning the emerging role of generative AI, and co-creation of responsible AI governance models.

Conclusion

Higher education institutions have an incredible opportunity to achieve significant mission impacts through the adoption of generative AI tools. At the same time, the unrelenting complexity of adopting this transformative technology remains a barrier for leaders. In this context, devising an enterprise strategy paired with practical tools is essential for navigating the ever-changing higher education landscape. This endeavor requires courageous leadership focused on cultivating a culture of innovation, committing to talent development, and enforcing responsible AI adoption. The time to act is now.

Notes

1. Jenay Robert and Nicole Muscanell, 2023 EDUCAUSE Horizon Action Plan: Generative AI, research report (Boulder, CO: EDUCAUSE, September 2023). Jump back to footnote 1 in the text.↩
2. Sean Burns and Nicole Muscanell, "EDUCAUSE QuickPoll Results: A Growing Need for Generative AI Strategy," EDUCAUSE Review, April 15, 2024. Jump back to footnote 2 in the text.↩

Kristi Wellington-Baker is Business Development Manager, Student Experience, at Amazon Web Services.