The AI Landscape in Higher Ed
The rapidly changing landscape of artificial intelligence is putting pressure on universities to invest in more powerful and versatile IT infrastructure.
“We’re seeing AI now not just in the computer science department, but across the university,” Martin says. “Beyond the chemistry and physics departments, AI supports linguistics with natural language processing. Art History departments are leveraging computer vision. It's being used in almost every single department now.”
Meanwhile, efforts to promote AI literacy in K–12 schools are on the rise. The next generation of students — the children of millennials — will be using AI technologies in almost every aspect of their lives. This generation will likely judge prospective colleges, in part, by their ability to provide powerful AI-enabled learning experiences. Higher education leaders will need to consider this when attracting and retaining this cohort, also known as “Generation AI.”
Whether students have knowledge of AI or not will soon impact how well they fare in the job market, as AI careers become lucrative even in industries outside of tech. “This is about workforce readiness,” Martin says. “Students need to get jobs when they graduate, and universities need to equip them with the right tools and the right experiences to meet that demand.”
This means higher education must start strategically planning for the infrastructure they need to support effective AI tools in curriculum and research.
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The Benefits of a Platform Approach to Designing AI Infrastructure
More often than not, piecemeal solutions tucked away in labs that cobble together heterogeneous IT components to create an AI ecosystem yield subpar results. It’s also an incredibly labor-intensive mission for higher education IT departments that are already understaffed.
To deliver AI infrastructure at scale, “they need a specialized solution,” Martin says. “When you look at natural language processing, for example, that’s not a linear increase in demand on the IT infrastructure, it’s an exponential increase. It involves a huge amount of data, and it can take weeks just to train one model.”