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In AI, Colleges See Cost-Effective Ways to Boost Enrollment

It’s no secret that data analytics is critical for the future sustainability of higher education. But what will it take to unleash the full potential of data analytics?

For one, it requires the adoption of artificial intelligence methodologies — such as predictive analytics and machine learning — to automate and optimize data. And out of all the higher education departments, enrollment services may be likely to adopt AI tools at a faster rate.

Predictions of a deep decline in university enrollment by 2026 were already emerging before COVID-19, with the pandemic throwing in an additional, more urgent element of uncertainty. In May, a McKinsey student enrollment survey found that “15 percent of students are very likely to defer by at least a semester, and up to 45 percent are very likely to look for a different school.”