As artificial intelligence becomes embedded in professional tools across industries, universities are recognizing that the skills taught in liberal arts classrooms may be more valuable than ever. The University of South Dakota is leading this shift by positioning humanities education as a strategic advantage in the AI era, arguing that critical thinking, ethical reasoning, and contextual understanding are precisely the capabilities that distinguish human learning from machine learning.

What Skills Can AI Actually Not Replace?

While generative AI systems excel at processing patterns in large datasets and generating content based on statistical probabilities, they struggle with the nuanced, contextual reasoning that defines liberal arts education. The University of South Dakota's 15-member AI steering committee spent the last school year surveying faculty, students, and staff to develop institutional guidelines for responsible AI use. A key finding emerged: humanities disciplines teach capabilities that remain fundamentally difficult for machines to replicate.

"AI cannot fully interpret and advise relational communication because it cannot think contextually. This thinking is what our discipline often describes as understanding the difference between a twitch and a wink," explained Leah Seurer, interim associate dean of the College of Arts and Sciences and associate professor and chair of the Department of Communication Studies at USD.

Leah Seurer, Interim Associate Dean, College of Arts and Sciences, University of South Dakota

Seurer's observation highlights a critical distinction: machines can recognize patterns but cannot grasp the subtle contextual shifts that humans navigate intuitively. Reading literature, studying history, and learning about different cultures provide insights into human ambiguity and uncertainty that AI systems built on statistical probabilities cannot easily match.

How Are Universities Integrating AI While Protecting Liberal Arts Value?

Rather than viewing AI as a threat to traditional education, USD is taking what it calls a "thoughtful and measured approach" to ensure students develop both practical AI fluency and critical judgment. The university's AI resource guide emphasizes human-centered learning, where AI tools supplement rather than replace human activity. This framework recognizes that students will graduate into a world where AI is embedded in professional software, but they must understand its role, limitations, and ethical implications.

The Center for Teaching and Learning at USD offers faculty workshops on integrating AI into classroom instruction, assignment design, and accessibility. The goal is intentional adoption that aligns with discipline-specific learning objectives rather than blanket implementation. Young Ae Kim, a professor of art and member of the AI steering committee, noted that different academic fields have vastly different relationships with AI technology.

"What stood out most during the committee discussions was how differently AI is understood across disciplines. In some areas, the focus was on possibility and integration, while in others, it centered more on concerns around authorship, academic integrity and the boundaries of student work," said Young Ae Kim, Professor of Art at USD.

Young Ae Kim, Professor of Art, University of South Dakota

Kim's experience designing graphic design courses illustrates how faculty can treat AI as a collaborative tool rather than a replacement for human creativity. In her classroom, students learn to use AI-enabled design tools while maintaining focus on developing their own creative judgment and critical thinking. This dual approach prepares students for professional environments where AI is already standard while preserving the human skills that differentiate expert practitioners.

Why Access and Equity Matter in an AI-Fluent Workforce

One concern that emerged from USD's institutional discussions was equity. If AI fluency is increasingly shaping career trajectories, and if AI tools are already embedded in professional software across industries, then differences in student access, familiarity, and confidence with these technologies become critical barriers to opportunity. Not all students or faculty start from the same place, which means universities must intentionally address these gaps.

USD's emphasis on close faculty-student interaction makes it easier to weave AI into the curriculum in intentional ways. This personal engagement allows instructors to identify where AI meaningfully supports learning objectives, particularly in areas such as ideation, drafting, and critique, while ensuring the emphasis remains on extending student thinking rather than replacing it.

Steps Universities Can Take to Balance AI Adoption With Liberal Arts Education

• Establish Institutional Governance: Create a cross-disciplinary committee to survey stakeholders, develop AI guidelines, and ensure policies reflect the values and learning goals of different academic disciplines rather than applying one-size-fits-all rules.
• Provide Faculty Professional Development: Offer workshops and training that help instructors think critically about where AI fits into their teaching, assignment design, and discipline-specific learning objectives without requiring comprehensive AI expertise before implementation.
• Emphasize Contextual and Ethical Reasoning: Strengthen humanities programs that teach critical thinking, interpretation, ethical reasoning, and contextual understanding, as these remain among the few skills not being outpaced by AI systems.
• Address Equity Proactively: Recognize that students have different levels of access and familiarity with AI tools, and design interventions to ensure all learners develop practical expertise and critical understanding regardless of their starting point.

The broader implication of USD's approach is that higher education serves students best not by simply teaching them how to use AI, but by helping them understand its role, limitations, and implications. As Kim emphasized, preparing students for a future shaped by AI means equipping them with the judgment, adaptability, and intellectual independence to engage with it thoughtfully, both in their careers and in their broader lives.

This strategy reflects a shift in how universities are thinking about their mission in the AI era. Rather than competing with machines on their own terms, institutions are doubling down on what humans do best: reasoning about context, navigating ambiguity, and making ethical judgments. The South Dakota Board of Regents published strategic objectives this spring designed to position the state's public universities as leaders in adopting AI in higher education, and USD's emphasis on liberal arts as a complement to AI fluency offers a model for how that leadership might look.