As artificial intelligence reshapes higher education at breakneck speed, North Carolina State University’s Chief Information Officer Marc Hoit is taking an unconventional approach that prioritizes widespread access over centralized control. In an era where many institutions are still debating AI governance frameworks, Hoit has already moved to implementation, betting that democratizing these powerful tools across campus will yield better outcomes than restricting them to select departments or research labs.

According to InformationWeek, Hoit’s strategy centers on making AI accessible to faculty, staff, and students alike, rather than maintaining it as the exclusive domain of technical specialists. This philosophy represents a significant departure from the traditional IT leadership model, where new technologies are carefully controlled and rolled out incrementally. “The democratization of AI is critical,” Hoit explains, emphasizing that broad adoption requires removing barriers to entry and ensuring that users across the institution can experiment with and benefit from these emerging capabilities.

The approach reflects a broader shift in how university IT leaders are thinking about their roles. Rather than serving as gatekeepers who determine which technologies are appropriate for campus use, leaders like Hoit are positioning themselves as enablers who provide the infrastructure, training, and support necessary for widespread innovation. This transformation is particularly crucial in higher education, where faculty autonomy and academic freedom have long been sacrosanct principles that can clash with centralized technology mandates.

Building Consensus Through Collaboration Rather Than Mandate

Hoit’s emphasis on collaboration as the pathway to technology adoption represents a sophisticated understanding of organizational change management in academic settings. Unlike corporate environments where C-suite executives can mandate technology adoption from the top down, universities require buy-in from multiple stakeholder groups, each with distinct needs and concerns. Faculty members, in particular, tend to resist initiatives that feel imposed rather than co-created.

The NC State CIO has made stakeholder engagement a cornerstone of his technology strategy, recognizing that successful implementation depends less on the technical merits of a solution and more on whether the campus community feels ownership over the decision. This collaborative approach extends beyond simple consultation; it involves bringing faculty, researchers, administrators, and students into the decision-making process early and giving them genuine influence over outcomes. By doing so, Hoit has been able to move faster on AI initiatives than many peer institutions still mired in committee debates.

The Technical Infrastructure Behind Democratized AI

Democratizing AI access requires more than philosophical commitment—it demands substantial investment in technical infrastructure and support systems. NC State has had to build out computing resources, develop user-friendly interfaces, and create training programs that make sophisticated AI tools accessible to users without deep technical backgrounds. This infrastructure challenge is particularly acute in higher education, where budget constraints often limit the ability to make large-scale technology investments.

The university’s approach involves creating multiple pathways for AI engagement, from simple chatbot interfaces for basic queries to more sophisticated machine learning platforms for research applications. This tiered approach allows users to engage with AI at their comfort level while providing clear pathways for those who want to develop more advanced skills. The strategy acknowledges that not everyone needs to become an AI expert, but everyone should have the opportunity to leverage AI capabilities in ways that enhance their work.

Navigating the Governance and Ethics Minefield

While democratization is Hoit’s goal, it doesn’t mean abandoning governance entirely. The challenge lies in creating frameworks that protect the institution from risks—including data privacy violations, algorithmic bias, and academic integrity concerns—without stifling innovation. This balance is particularly delicate in the current environment, where AI capabilities are evolving faster than regulatory frameworks can keep pace.

NC State has had to develop policies that address everything from student use of AI in coursework to faculty deployment of AI in research and grading. These policies must be flexible enough to accommodate rapid technological change while providing clear enough guidance that users understand boundaries. The university has also had to grapple with questions about data ownership, model training on institutional information, and the potential for AI to perpetuate or amplify existing biases in educational settings.

The Competitive Imperative Driving AI Adoption

Hoit’s urgency around AI democratization is driven partly by competitive pressures. Universities are competing for students, faculty, research funding, and prestige in an increasingly crowded market. Institutions that can offer cutting-edge AI capabilities have a recruiting advantage, both for attracting top researchers who want access to advanced tools and for students who recognize that AI literacy will be essential for their careers.

This competitive dynamic is accelerating AI adoption across higher education, sometimes faster than institutions can thoughtfully address the implications. Schools that move too slowly risk falling behind, but those that move too quickly without adequate planning risk implementation failures that can set back progress for years. Hoit’s collaborative approach attempts to thread this needle by moving quickly while bringing stakeholders along rather than leaving them behind.

Lessons for IT Leadership Beyond Academia

While Hoit’s work is focused on higher education, his approach offers lessons for IT leaders in other sectors grappling with AI adoption. The emphasis on democratization over control, collaboration over mandate, and enablement over gatekeeping represents a modern leadership philosophy that may be increasingly relevant as AI capabilities become more powerful and more accessible.

Corporate IT leaders, in particular, may find value in Hoit’s stakeholder engagement strategies. As AI moves from specialized applications to general-purpose tools that every knowledge worker might use, the traditional model of IT as a controlling function becomes less tenable. Instead, IT organizations may need to evolve into platforms that provide infrastructure, governance, and support while empowering users to innovate within appropriate guardrails.

The Training and Change Management Challenge

One of the most significant obstacles to AI democratization is the skills gap. Making AI tools available is meaningless if users don’t know how to use them effectively or understand their limitations. NC State has had to invest heavily in training programs, documentation, and support resources to ensure that democratization doesn’t simply mean giving people access to tools they can’t use productively.

This training challenge extends beyond technical skills to include critical thinking about AI capabilities and limitations. Users need to understand when AI is appropriate to use, how to evaluate AI-generated outputs, and what biases or errors might be embedded in AI systems. This kind of AI literacy is becoming as fundamental as digital literacy was a generation ago, and universities like NC State are on the front lines of developing educational approaches that can scale across diverse user populations.

Measuring Success in a Rapidly Evolving Domain

Determining whether AI democratization efforts are succeeding presents its own challenges. Traditional IT metrics like system uptime or help desk ticket resolution times don’t capture whether AI tools are genuinely enhancing teaching, learning, and research. NC State has had to develop new frameworks for assessing impact, looking at measures like research productivity, student outcomes, and operational efficiency gains.

The university is also tracking adoption metrics to understand which user groups are engaging with AI tools and which remain resistant or unaware. These insights help inform targeted outreach and training efforts, ensuring that democratization benefits extend across the entire institution rather than concentrating among early adopters. As AI capabilities continue to evolve, these measurement frameworks will need to evolve as well, creating an ongoing challenge for IT leadership.

The Road Ahead for University AI Strategy

Hoit’s work at NC State represents an early chapter in what will be a long-term transformation of higher education through AI. The decisions being made now about access, governance, and support will shape institutional capabilities for years to come. Universities that get this transition right will be better positioned to fulfill their teaching, research, and service missions in an AI-enabled world.

The democratization approach carries risks—including the possibility of misuse, the challenge of supporting diverse use cases, and the difficulty of maintaining quality and consistency across decentralized implementations. However, Hoit’s bet is that these risks are outweighed by the benefits of widespread engagement and innovation. As other institutions watch NC State’s progress, they’ll be gathering evidence about whether this collaborative, democratized approach delivers better outcomes than more controlled alternatives.

For IT leaders across sectors, the fundamental question Hoit’s work raises is whether the traditional model of centralized technology control remains viable in an era of rapidly accessible, powerful AI tools. His answer—that collaboration and democratization are not just idealistic goals but practical necessities—may point the way forward for organizations trying to harness AI’s potential while managing its risks. The success or failure of this approach at NC State will offer valuable lessons for the broader higher education community and beyond.