The start of a new academic year brings a familiar challenge for higher-education IT teams. College and university campuses return to full activity as students settle in, faculty resume teaching, administrative staff manage registration and orientation, and other critical operations resume. At the same time, large numbers of devices reconnect to campus networks, digital learning platforms become mission-critical, and connected technologies across classrooms, residence halls and common spaces come back to life.
For students, these systems are simply part of the college experience. They expect to connect their laptops and phones, access course materials, stream lectures, submit assignments, and use campus applications without interruption. When everything works as expected, much of IT’s work is invisible. When something goes wrong, however, IT teams quickly become the focus of frustration.
Preparing for the academic year is about more than confirming that network infrastructure is operational. IT teams need to understand how their environments will perform under increased demand, identify potential problems before they become disruptions, and account for cybersecurity alongside performance and availability.
A 2026 Inside Higher Ed survey found that 49% of campus technology leaders consider the pace of technology-driven change unsustainable without additional resources. Respondents also identified recruiting and retaining IT talent, cybersecurity threats, and unsustainable cost trajectories as leading risks facing institutions through 2030. For many colleges and universities, resilience will depend on making existing people, processes, and information work together more effectively.
Start with a baseline
One of the most important steps IT teams can take before the semester begins is establishing a clear picture of what normal network performance looks like in their environment. This includes understanding how much traffic the network typically handles, where bandwidth is concentrated, which systems are most heavily used, and how demand changes during critical academic events.
Traffic patterns from previous academic years can provide a useful baseline, showing when usage tends to increase and which areas of campus experience the greatest pressure. For example, the first week of classes may generate unusually high demand as students activate devices, download course materials, and access online services. Large lectures can produce concentrated wireless traffic, while registration periods, examinations, and major campus events can create additional spikes.
Establishing that baseline helps IT teams distinguish expected changes in network behavior from unusual activity or underlying capacity issues. It also gives them a point of comparison when troubleshooting problems later in the academic year.
Account for AI’s growing role on campus
Generative AI has quickly become part of everyday academic activity, with students and faculty using AI platforms for research, coursework, and other tasks. That growing adoption can introduce traffic patterns that may not have been part of previous network usage.
AI applications can create different demands from traditional web activity, particularly when users submit context-rich prompts or upload audio, images, and other multimodal data. Those demands could become even more variable as agentic AI applications become more common.
For campus IT teams, this adds another layer of complexity to an environment where traffic is already highly variable. Networks must support users and devices as they move between facilities while accommodating usage patterns that change throughout the academic calendar. AI-enabled applications can create demand in places or at times that existing capacity plans did not anticipate.
The same variability can make security monitoring more difficult. A sudden change in traffic could be the result of legitimate AI usage, a software update, or an academic event, but it could also indicate a security or infrastructure problem. Without sufficient visibility, distinguishing between the two can take valuable time.
IT teams need real-time insight into their environments to understand where traffic patterns are changing and why, whether those shifts are affecting performance and which parts of the network are involved. That visibility allows teams to make targeted capacity or configuration changes where they will have the greatest impact.
Treat cybersecurity as part of campus resilience
Today’s higher-education networks support open, distributed environments with a broad ecosystem of connected technologies, from classroom systems and security cameras to research equipment and student devices. Colleges and universities also manage valuable personal information, including student records and financial information.
That combination creates a complex security environment. The proliferation of connected devices, cloud applications, and remote access has expanded the number of potential entry points into campus environments. A security incident can disrupt learning and campus operations and allow attackers to steal proprietary research, manipulate admissions records, or compromise financial systems.
The start of a new academic year can introduce additional changes. New platforms, devices, integrations and access permissions can all alter what is connected to the network and how systems communicate. In addition to assessing the security of individual technologies, IT teams must also consider what they connect to, what access they provide, and how a compromise could affect the broader environment.
Alongside these technical challenges, skill gaps further compound the pressure on higher-education institutions. Sophos’ 2026 State of Ransomware in Education report found that 53% of higher education teams reported lacking the skills needed to detect and stop an attack in time, compared with 35% across all sectors surveyed.
As AI enables faster, more sophisticated cyber threats, IT teams can also harness AI and automation to help close those skill gaps. By surfacing relevant insights, reducing manual work, providing guidance, and supporting more automated resolution, AI reduces reliance on hands-on technical skills. What is becoming increasingly valuable is the ability to oversee automated actions and make informed decisions based on the context and recommendations AI agents provide.
Make troubleshooting faster
Even with careful preparation, problems will happen. The difference between a minor inconvenience and a major disruption can come down to how quickly IT teams can identify the source.
When a student reports that a service is unavailable, the IT team needs more than a general indication that the network is “up.” They need to determine whether the issue is isolated to a device, building, network segment, application, or external service. If the disruption is caused by compromised credentials, malware, or another security threat, the priority may also need to shift from restoring service to containing the threat, preserving evidence, and determining the extent of the compromise.
Fast troubleshooting depends on having the right context. IT teams can build that context by bringing together information from network monitoring, device management, application monitoring, and security tools, then correlating signals across the environment.
Viewing network topology, traffic patterns, alerts, configuration changes, and application performance together makes it easier to trace multiple symptoms back to a common source. Cloud-based IT management platforms can provide centralized visibility, alerting, and traffic analysis to support this work.
The faster teams can narrow the scope of a problem, the less time they spend investigating unaffected systems and the sooner they can focus their response where it is needed. That is particularly important for higher-education institutions where relatively small IT teams may be responsible for large distributed environments.
Reduce the gaps created by tool sprawl
More tools do not necessarily mean more visibility. As institutions add network, security, application, and device-management technologies, teams can end up with overlapping capabilities and information spread across disconnected systems.
Budget pressure can also lead institutions to eliminate tools without fully understanding the dependencies they support. Before making those changes, IT leaders should identify overlapping functions, determine where critical information is not being shared, and understand where removing a tool could create a visibility gap.
The goal should be to make the most important information available to the right people when they need it, rather than simply adding more dashboards. A connected view can help network and security teams work from the same information when investigating an issue.
Define collaboration before an incident
Network operations and security teams should also establish how they will work together before a problem occurs. When an anomaly appears, teams should already understand who is responsible for investigating it, when to escalate it, and who communicates with academic and administrative leaders.
Short tabletop exercises can help identify unclear ownership before an outage or security incident exposes it. These exercises can include representatives from infrastructure, security, identity, communications, and the academic or administrative groups that depend on critical technology services.
The objective is not to create a complicated incident-response process. But having a clear protocol in place and running through it regularly prevents teams from scrambling when an incident does occur and ensures that appropriate stakeholders have the information and authority to act quickly.
Build readiness into the academic calendar
The best campus technology experience is often the one students never have to think about. When networks perform reliably, students can focus on their coursework rather than connectivity problems. Faculty can teach without worrying about whether classroom technology will work. Administrative teams can depend on the systems they use to keep the institution operating.
Achieving that reliability requires more than a once-a-year assessment before students return to campus. Higher-education environments change continuously as new devices and applications are introduced, buildings are renovated, and network configurations evolve throughout the academic year.
By regularly updating performance baselines, maintaining an accurate view of the environment, preparing for periods of elevated demand and establishing clear collaboration between network and security teams, IT leaders can better identify changes and respond before disruptions spread.
With students, faculty and staff relying on digital services across nearly every aspect of campus life, that readiness is essential to delivering a reliable academic experience.
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Douglas Murray, CEO, Auvik
Doug Murray is the Chief Executive Officer of Auvik where he drives company strategy, culture, and growth. Murray has over 30 years of network and security industry experience, including two years as the CEO of cloud cybersecurity company Valtix (acquired by Cisco), as well as seven years as CEO of SDN pioneer Big Switch Networks (acquired by Arista Networks). He previously held leadership positions at Juniper Networks, Sun Microsystems and AT&T, and was a finalist for the EY Entrepreneur of the Year Northern California in 2017. Doug holds a BA in History from Colgate University and an MBA from Johns Hopkins University.
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