Adrian Anderson, Artificial Intelligence Educator / IT Technical Trainer, University of South Carolina
Artificial IntelligenceEdTechHigher Education

Establishing a Proactive AI Hub on Campus

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By Adrian Anderson, Artificial Intelligence Educator / IT Technical Trainer, University of South Carolina

Artificial intelligence adoption and integration have proved to be a challenge. In my experience working previously in the Office of Student Conduct and Academic Integrity and now as an Artificial Intelligence Educator within the Division of Information Technology, I have seen first-hand how divided factions of students, faculty, and staff often have conflicting expectations and limited clarity on AI’s role in academics and administration.

Faculty are debating in teaching workshops and retreats whether their focus should be on AI detection as a deterrent or mandating AI use in some form to better prepare students for a new global job. All the while, administrative offices are plugging emails into ChatGPT and running data analysis with AI-powered tools that have hopefully been vetted for security purposes, but likely aren’t using the tools to their full potential.

Areas of friction will likely involve governance, academic integrity concerns, and bias in AI.

Faculty, students, and staff are all asking for training, clarity, and ethical guardrails; they have been unsatisfied with the answers that one group asks the other. Mutual expectations are blurry. Along the way, someone in one of these groups thinks maybe these questions are best answered by professionals across campus who make up the IT department. They put in a ticket or pick up the phone and hopefully they find the right person to assist with explaining the pros and cons of adopting certain technologies, maybe the person helps break down the tech-jargon from the new software, and this then leads to understanding and decision-making. This is the best-case scenario at many institutions in Higher Education; it is not ideal. In this post-ChatGPT landscape, IT cannot position itself as a last resort or problem-solver on the fly. We must be proactive, we must be seen as the first call and not the afterthought, and we must become educators. Here, I outline a strategy for establishing a centralized AI hub.

The AI Educator Role

At the University of South Carolina, the AI Educator team bridges the gap between users and technology. We serve as trainers, consultants, and facilitators, helping campus stakeholders understand and leverage AI tools. Our mission is to make AI resources accessible, reliable, and aligned with campus needs. We serve as the institution’s greatest steps towards an AI Hub of knowledge, training, and resources for all at the university.

To those outside of the IT sphere, the role can be described as a teacher or trainer on various AI concepts and platforms supported by the infrastructure within the Division of IT. This gives the AI Educator team a leg up by being tapped into IT’s services, internal knowledge base, and AI vendors. Within the IT sphere, this role is imagined to be an in-house IT consulting unit or group of IT Technical Trainers for users across the campus environment, serving as a stop gap between users and the technology, in this case AI, they are attempting use while conducting university business or coursework. Housed within Service Management, we are establishing a hub for AI resources that does not wait for a problem to solve.

Why a Centralized AI Hub?

A centralized AI hub streamlines access to information, training, and support. Instead of fragmented resources and unclear responsibilities, the hub offers one place for users to ask questions, build a community of practice, receive training from AI Educators and vendors, and change the perception of IT services.

Building an AI Hub

Establishing AI Hubs and fortifying ones like what is being built at USC will require relying on cross divisional partnerships and service providers.

  • Assess Needs
    • What are people saying both in and outside of the IT department regarding AI literacy, governance, ethics, and authority.
  • Establish Partnerships
    • Secure buy-in from university leadership (CIOs, Presidents, Boards) and collaborate with service providers. Partnerships with trusted vendors (e.g., Microsoft, OpenAI, Google) ensure security and reliability.
  • Build Infrastructure
    • Create both online and physical spaces for engagement. Develop a website, shared data hub, and offer in-person and virtual training. Make it easy for users to find information and connect with experts.
  • Pool Existing Resources
    • Leverage knowledge from university libraries, computing departments, and IT professionals. Consolidate resources to benefit all campus users

Expected Outcomes

Outcomes derived from taking the steps above will include a new perspective from various campus stakeholders, shifting the idea of IT only being problem solvers to being content experts and teachers. Campus users should be able to articulate where the university stands on AI offerings more easily, and IT departments will be able to adopt new technologies sooner for campus-wide integration because they will have a better established connection with the population, as use cases for AI arise from conversations had while engaging with the hub.

Anticipated Challenges

Areas of friction will likely involve governance, academic integrity concerns, and bias in AI. This is why getting the decision-makers on one accord is imperative to iron out before establishing an AI hub. A campus’s Honor Code must not contradict recommendations that a user could receive from the hub, for example. It would be most appropriate to have answers for tough questions before they are prompted to instill confidence in potential users and bolster the appearance of a truly unified campus initiative.

Early Success

While new the team at the University of South Carolina has already began filling a gap and the best measure of that success to date has been how quickly students, faculty, and staff have begun relying on this team to not only consult one on one but, lead faculty and staff development workshops because finally they don’t have to search for AI solutions on their own. Now they can just call an AI Educator.

Call to Action

Consider this model. Success will require trust and collaboration from stakeholders in a new way in Higher Education. Share these concepts within your campus or network, identify what’s needed, and chart the next steps. While adopting and integrating Artificial Intelligence can be difficult, working toward a unified vision for AI is essential for collective progress.