I work almost exclusively with technology leaders at top research universities and they never cease to amaze me. Higher ed CIOs see into the future, making decisions that won’t outdate themselves in a year, or even 10 years.
And, although these CIOs and CTOs serve large universities, their strategies can be scaled to any size institution.
Below is a list of five specific trends I’ve observed in the university technology world. AI features prominently in this list, but it’s the strategic use of AI in various capacities that CIOs believe will have the greatest impact to keep their universities running smoothly, their research capabilities growing and their students learning to the best of their abilities.
1. Self-healing, self-supporting networks driven by AI
Top public research universities spend up to $45 million per year for their central IT budgets, according to the most recent CDS Interactive Almanac from EDUCAUSE. Based on experience in this space, anywhere from 25% to 30% of this spend is currently dedicated to administrative IT tasks, such as account management, hardware and software maintenance, data backup and recovery tasks, patch management, troubleshooting, and many more.
Self-healing networks, also called autonomous networks, are being developed today. The University of Maryland is building an AI-powered, role-based, policy-driven, self-healing network to support the school’s research-intensive environment with minimal human intervention, allowing university staff to significantly reduce IT troubleshooting and focus on innovation, not maintenance.
AI-powered analytics do a lot of heavy administrative lifting. Universities can monitor and optimize network usage, automate access and manage the growing complexity of research and collaboration demands in real-time. They also identify, diagnose, and resolve network anomalies, allowing staff to focus on other institution-enhancing projects.
2. Cloud-based infrastructure: The backbone of global research collaboration
The best CIOs understand the power of the cloud. Astute Analytica, an analyst firm, estimates cloud spending in higher education will increase an average of 22% per year through 2030.
Cloud-based infrastructure is essential for managing the massive data flows that are key to wide-reaching research projects, enabling institutions to scale up or down without the limitations of physical hardware.
More from UB: Here are 3 ways college leaders can groom emerging talent
Already, moving to a cloud-based infrastructure has made a major difference for an R2 university in the Southwest. Since moving to the cloud, the increased network speed and reliability has enabled students and faculty to engage in more advanced research, utilize high-bandwidth applications and collaborate seamlessly.
It wasn’t an easy decision to transition from a 10-year-old, rapidly aging infrastructure, but it also wasn’t serving the community well to continue without making a change.
3. Advanced security through AI-driven network access control
AI-driven access control systems will be essential for ensuring the security of increasingly valuable and sensitive data. Already, Gartner estimates more than one-third of organizations are using AI-powered threat-detection tools.
By 2030, these systems will become indispensable, managing real-time responses to security threats across thousands of devices used on college campuses and securing the critical research data that R1 and R2 universities depend on.
These systems will also be able to adapt to a growing array of devices and research environments as well as monitor network traffic for suspicious activity and rapidly contain potential breaches.
4. Urgency of upgrading legacy systems: Staying ahead by 2030
It’s probably not surprising that about half of the universities we work with support legacy infrastructures, at least in certain portions of their network. While these may be challenging to replace, with proper planning, there is a straightforward path to seamlessly upgrade these systems. CIOs know they have to act now or risk falling behind.
Beyond efficiency and security, moving away from legacy networks will save significant time and resources that these universities currently invest in supporting older architectures. Migrating away from legacy systems comes with vast operational efficiencies, so universities can focus on delivering proactive and beneficial network services, versus spending time just keeping the system updated and functional.
5. Personalized learning through AI: Crafting tailored educational experiences
As educational paradigms shift, AI-powered personalized learning is becoming a more common tool. By analyzing data on student behaviors, learning habits and performance, AI can craft tailored learning experiences that meet each student’s needs.
A study by EDUCAUSE reveals that 69% of technology leaders believe that educators will increase their use of AI analytics for teaching and learning in the next two years.
As a whole, research universities are just beginning to explore the role and shape of personalized learning in higher education. However, with a modern, cloud-based architecture as a foundation, they are setting the stage for easy implementation.
We will most likely have more data to report in 2025, as more R1 and R2 institutions adopt AI-driven personalized learning tools as a competitive advantage, helping to attract and retain top talent while promoting academic success.
It’s all possible
The landscape of higher education technology is evolving rapidly, and CIOs at leading universities are taking proactive steps to address the future. Self-healing networks, cloud-based infrastructure, AI-driven security, modernization of legacy systems, and personalized learning are the pillars of their strategies.
These innovations don’t need to break budgets. In fact, by 2030, we expect them to enhance operational efficiencies.
All colleges and universities, regardless of size, should take note. As R1 and R2 CIOs anticipate and navigate these technological shifts, they are ensuring that their institutions remain resilient, adaptable, and ready for the demands of a globalized, data-sharing environment.
