Today, AI is no longer a concept to be explored in higher education. It’s the ability to implement. The technology has matured. Please look forward to it. Educational institutions currently face tight budgets, increased public scrutiny of costs and outcomes, FAFSA delays and far-reaching demographic impacts.
As stated in Liaison’s new report: Leveraging AI, leveraging the power of predictive and prescriptive analytics to drive smarter aid, admissions, and student successAI is a matter of survival, a cornerstone of strategy, and a catalyst for improving student outcomes. It enhances and informs human decision-making, helping institutions implement targeted strategies that support their missions. Provide visibility, clarity, and confidence in high-risk, resource-constrained situations.
AI on campus: gaining momentum
The survey data reflects the growing role of AI in higher education. 2025:
- 65% of enrolled leaders reported actively using emerging technologies like AI, compared to just 40% in 2024.
- 61% say their campus is open to AI implementation, a 25% increase from last year.
- More institutions are investing in readiness, with 19% more planning to upskill their staff for AI-driven operations.
New technologies, such as Liaison Othot’s predictive and prescriptive analytics platform, help financial institutions model the impact of different financial aid scenarios. This allows us to identify and intervene with students at risk and quantify the effectiveness of strategic decisions, while keeping equity and human judgment at the forefront of decision-making.
However, preparedness remains uneven. More than half of respondents (56%) do not believe their institution is a leader in AI adoption, and only 21% feel they are ahead of their peers. For many campuses, the opportunities are clear, but the path forward still feels complicated. Making meaningful progress requires clear goals, integrated systems, and reliable data.
Turn predictive and prescriptive analytics into measurable outcomes
Educational institutions across the country are applying predictive and prescriptive analytics to meet their most pressing enrollment and financial aid goals. For example, Indiana University of Pennsylvania (IUP) faced declining student participation and disjointed outreach efforts. Despite having a wealth of student data, staff struggled to act on insights to improve student success.
Things changed when IUP started working with Othot. Together they do the following:
- Implemented success scores and financial aid sensitivity modeling across key student groups.
- Embed retention scores into your school’s CRM for real-time decision-making.
- We leveraged Osotto’s financial aid sensitivity analysis to refine our scholarship and retention grant strategies for smarter, more equitable aid distribution.
The results were noteworthy:
More than 140% increase on international flights Deposits within one year (271-664).
- $4 million increase in net tuition revenue From the international student market.
- Significant increase in out-of-state enrollment; 40% more than expected.
Ethical framework for AI on campus
The promise of AI in higher education is immense. However, as predictive and prescriptive models become critical to admissions, financial aid, recruitment, and student success, institutions must approach their use with intentionality, transparency, and care.
AI should be a tool for expanding equity, not reinforcing bias. Therefore, responsible use requires an ethical, accountable, and student-centered mindset.
The Analytics Platform does not determine who receives financial aid or who is admitted. These provide institutions with insights that support, rather than replace, human judgment. The final decision should always be made by an enrollment and aid professional who fully understands the student’s situation and the institution’s mission.
Prescriptive recommendations from Othot are designed to help your team:
- Focus your limited resources where they have the most impact.
- Model how aid strategies affect enrollment and revenue.
- Identify hidden patterns that may be overlooked.
- Promote consistency in decision-making while accounting for nuance.
As institutions expand their use of predictive and prescriptive analytics, the question is no longer whether AI belongs in the enrollment and assistance process, but rather how to continue to evolve the use of AI in a way that is strategic, sustainable, and focused on student success. Read below to learn how AI can help improve admissions outcomes on campus. Leveraging AI, leveraging the power of predictive and prescriptive analytics to drive smarter aid, admissions, and student success.
