Is your admissions process ready for AI?
Most AI tools in admissions underperform for the same reason: the foundations underneath them aren’t ready. AI-Ready Admissions (AIRA) gets your data, processes and governance in shape first, so whatever you choose to adopt actually works.
The problem
The pitch decks make it look simple. Plug in the tool, automate the routine decisions, free up your team for the work that actually needs judgement.
Then it lands on top of inconsistent data, processes nobody has written down, and a policy that doesn’t mention AI at all. And it does exactly what you’d expect.
The technology is rarely the thing that lets you down. It’s everything underneath it. You can’t automate a process you haven’t agreed, and you can’t trust a decision built on data you don’t trust.
A different order of operations
AI-Ready Admissions (AIRA) programme is built on a simple idea: get ready first, then choose the technology.
We work through four foundations, in order. Each one rests on the one below it – which is why we think of it as a staircase rather than a checklist. Skip a step and the ones above it wobble.
AI readiness – and only now, with the first three in place, are you actually ready to evaluate, choose and deploy a tool with confidence.
Process – how admissions actually works today, not how the handbook says it should. Where the decisions happen, who makes them, and where the bottlenecks really are.
Data – whether the information feeding your decisions is accurate, consistent, governed and lawful to use. This is the step most institutions assume is fine and most often isn’t.
Policy – lawful basis, fairness, accountability and human oversight. The questions a regulator, an applicant or your own board will ask before they ask anything else.
How AIRA works
The programme runs in two stages, and you can stop after the first.
Stage 1 – Where you actually stand. We start with a diagnostic across all four foundations, anchored by a Data Governance Health Check. You come out of it with a clear, honest picture of your readiness and the gaps that matter most. Some institutions take that away and act on it themselves. That’s a perfectly good outcome.
Stage 2 – Getting genuinely ready. For those who want support to close the gaps, Stage 2 is the build: turning the findings into governed data, agreed processes, defensible policy and a clear path to adopting AI well.
Who AIRA is for
UK higher education providers thinking seriously about AI in admissions – whether you’re already being sold tools, already piloting one, or simply being asked by your leadership what the plan is.
AIRA is for admissions, registry and data teams who would rather get the foundations right once than firefight a deployment that was never going to work.
Who’s behind it
AI-Ready Admissions is a partnership between Sparkline Advisory and Think Bold, bringing together data governance and admissions process expertise that usually sits in separate rooms.
Between us we’ve spent decades inside UK higher education, on data governance, regulatory returns, admissions process and responsible AI. We’ve seen what works, and we’ve seen what happens when the foundations get skipped.
Rachel Reeds is a senior higher education admissions specialist with fifteen years’ experience across the UK sector. Founder of Think Bold Ltd and creator of the Admissions Diagnostic Review methodology, she helps providers build admissions operations that are regulator-defensible, operationally sustainable, and ready for what the sector is about to ask of them.
Martha Horler is a data and AI governance specialist with over 20 years’ experience working in and alongside UK higher education. Founder of Sparkline Advisory Ltd and creator of the ICE/BERG responsible AI framework, she helps institutions build the data foundations and governance structures that make AI work properly – and defensibly.
Not sure where your foundations stand?
That’s the question Stage 1 is built to answer. Book a 30-minute conversation and we’ll talk through where you are and whether the AIRA programme is a fit.
