The risk isn’t just related to cost and security. With legacy systems, when government policy changes, institutions often wait weeks for coders to rewrite systems. A change to reporting requirements, visa compliance, student support obligations or funding models can trigger a cascade of manual interventions. IT teams raise tickets, vendors scope the work, programmers code custom fixes – and staff scramble to adjust processes while they wait. And wait. And wait.
This lag creates real risk. Policy settings can shift overnight – as we’ve seen with Ministerial Directions affecting international student caps, TCSI changes, new funding rules or rapid pivots to online learning. Until the system update arrives, staff are left in the lurch, relying on spreadsheets, workarounds and late nights to stay compliant. It’s an inefficient and stressful cycle. All of this at a time when universities need their staff focused on creating better student and staff experiences, not maintaining old tech.
Replacing 'old tech' in the cloud with a like-for-like lift doesn’t solve the problem. It risks embedding inefficiency for another decade. What’s needed is a step-change: modern, agile platforms designed for the digital era, with AI built in to support decision-making and automate manual work.
In an AI-enabled cloud-native platforms, configuration changes that once required specialist coding and testing over weeks can now be completed by AI agents that can see where changes need to be made, make recommendations for a member of staff to review, and make those changes once they’re approved in a matter of minutes.