Like it or not, students throughout higher education are using artificial intelligence — specifically large language models — while on your campus, connected to your network and even while using your devices. A 2024 survey from the Digital Education Council revealed that a whopping 86% of college students use AI in their studies, and more than half of respondents (54%) do so at least weekly.
And to be clear, that’s not a bad thing.
Today’s students are tomorrow’s workforce, and those workers will be expected to have at least a basic level of AI literacy when they begin their careers. Those with a more advanced understanding of how to get the most out of an LLM will have an even greater advantage over their peers.
The goal then is to educate students on using AI the same way you would teach them to use, say, lab equipment, a paintbrush or a soldering iron — except that AI, unlike a paintbrush, is still evolving. So, while teaching them remains important, making sure you’re doing so using the latest tools, and keeping up with the next evolution, is just as crucial.
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Built-In Generative AI Tools Keep Students on the Cutting Edge
The leading productivity suites in higher education — Google Workspace and Microsoft 365 —have already introduced generative AI tools directly into their applications. Google Gemini and Microsoft Copilot are embedded in the word processors, spreadsheets, slideshows and more that are included in those suites. The tools are there at no additional cost and offer a basic collection of user personalization and training opportunities for students and faculty.
The free features, however, are set back a bit from the cutting edge where recent college graduates want to be. Paid tiers of Gemini and Copilot may sound like a luxury purchase for a college or university contending with a budget crunch, but the available features in the two embedded LLMs can make the investment worthwhile. And there is also an expectation that, as with most software, new features will be rolled out to the paid tier first.
With Gemini, the paid tier already includes real-time transcription and translation services, something that’s a boon to universities trying to improve accessibility. It can even be used for in-person meetings: Just set up a call on Google Meet on a device in the room, and the meeting is preserved for future use, accessible to all.
Gemini’s paid tier also offers unlimited pings for deep research. Such queries cite many more sources than the free tier and enable deep dives into all the cited material. It’s a no-brainer for students who are pushing themselves academically.
In Copilot, for example, paid features allow students to create their own AI agents to conduct research. A student working on a project could create an AI agent, put it on a well-trafficked website, and have that agent ask questions of the site’s visitors to build up its — and the researcher’s — knowledge base.
86%
Percentage of higher education students who report using artificial intelligence in their studies
Source: Digital Education Council, Digital Education Council 2024 Global AI Student Survey, August 2024
Of course, free is free. But even for universities that stick with the preloaded LLMs, engaging with a multivendor solutions provider such as CDW ensures you get the most out of those free versions. Few university employees have the time or experience to develop deep knowledge of these ever-changing AI tools, but the experts at CDW offer end-user training on the free and paid versions of Copilot and Gemini, conducting courses with a small group that can then bring that knowledge to your campus.
If there’s one easily fixable mistake we’ve seen in AI implementation, it’s from institutions that bring these AI tools onto campus and let them run wild. Students who will be expected to know how to prompt and how to customize AI solutions need to be taught how to do that before they enter post-college life.
Beware Security Risks From Third-Party Generative AI
There are, of course, other LLMs beside Gemini and Copilot, and students are likely using those as well. But for institutions engaging with those tools on a large scale, there will be both opportunities missed and new challenges created.
One of the nice things about an AI-powered productivity suite is that the LLM can communicate across apps. So, for example, you can have Gemini create a calendar event from inside Google Sheets. Or have Copilot open a Microsoft Word document when you’re creating a PowerPoint presentation. The integration with any third-party option is far less smooth.
Students using Gemini and Copilot will also have added security protection for their data while working within those platforms. If a school has a Google Workspace license, for example, all traffic within those Google platforms, including Gemini, is secured in the same way students’ email and data storage are protected. The same goes for Microsoft.
With a third-party LLM, a student’s prompts and the LLM’s answers are outside of that secure perimeter. Most third-party tools should have their own options for data protection, but as IT security pros know, more tools from more vendors means more opportunities for data leaks and cyberattacks.
This article is part of EdTech: Focus on Higher Education’s UniversITy blog series featuring analysis and recommendations from CDW experts.
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