Assets and Liabilities of Utilizing AI in the Admissions Process

By Jacob Henry

In higher education, artificial intelligence (AI) seems to be on everyone’s mind, in some way or another, these days. Although the original focus has been on students’ usage of AI and how admissions application reviewers will adapt, we are coming to a moment in our field where the tools may be utilized to assist in the streamlining of our existing systems and processes. “Artificial intelligence, according to Coppin, is the ability of machines to adapt to new situations, deal with emerging situations, solve problems, answer questions, devise plans, and perform various other functions that require some level of intelligence typically evident in human beings” (Chen, et al. 2020). Most higher education professionals would view this ability as a strength to be leveraged, particularly amid declining support and resources. But some others in the field see this as a warning sign of new problems on the horizon. There are societal and ethical concerns that need to be addressed (Pedró, et al. 2019).

In this article, I will review the assets and liabilities of utilizing AI in the admissions process, including references to prospective student inquiries, application process, and visit opportunities.

Assets

Streamline Our Process

The Common Application reports increases in first-year application rates, with 1,228,016 applications submitted during the 2023–24 admissions cycle (Nietzel 2025). The number of applications that first-year students submit is continuing to rise. Admissions departments need to do more with less now. This is where AI can come into play. Artificial intelligence uses big data technologies to efficiently handle large data volumes (Pedró, et al. 2019). With the increase in guaranteed acceptance programs, artificial intelligence can assist departments in delivering applicant decisions in a timely manner. This is just the beginning. We can begin to imagine an admissions process where the college application process can be personalized without adding extra staff (Dennis 2018).

Create Clarity Through the Clouds

We often hear about misinformation given to prospective students from varying sources. AI can provide clarification regarding prospective students’ inquiries. This form of technology can help institutions stay competitive in an increasingly competitive and digital world (Garg, et al. 2025). Prospective students often use our websites to obtain the information they need. Some institutions are currently utilizing systems like Kollegio, TargetX, or PeopleGrove to create AI counselors that are available at the click of a button. When students communicate with our institutions outside regular business hours, this implementation can help guide prospective students through the funnel.

Increase Institutional Awareness

With the United States housing many individual institutions, it is challenging for each to break through the noise. Prospective students are bombarded with information from colleges and universities on a regular basis. “Prospective students, especially those from far-off places, may not be able to utilize traditional admission methods” (Garg, et al. 2025, 1) Using AI can increase awareness by providing information that is personalized to the needs of prospective students on an individual level. AI software can provide clearer search results for prospective students and help institutions identify students who fit their campuses.

Liabilities

Concerns with Equity

We often challenge our admissions practices internally and seek ways to increase equity. Some would argue that creating standardized practices should do just that, but certain aspects of artificial intelligence could raise concerns. The concept of human-centered AI can be seen as the main culprit (Lira, et al. 2023). These newer systems are being implemented by humans with their own sets of biases. We often see reports of concern with AI generalizing individuals and making mistakes where human influence could have corrected them. Fairness and transparency concerns about AI have been raised in the context of facial recognition and recidivism prediction (Alvero, et al. 2020). We should be cautious when implementing new systems in our admissions process. Equity can sometimes be best handled by our own hands.

Depersonalization of Recruitment

Admissions officers are often asked to assess the personal qualities of applicants (Lira, et al. 2023). Admissions offices consistently emphasize the personal touch in recruiting students. This is often what we brag about when discussing our efforts in the field. Including AI in either the recruitment or application phase can seem disingenuous at times. Of course, this can address our shortage of admissions officers, when necessary, but there can be a fine line between the two. AI measuring personal qualities of applicants can be both optimistic and cautious (Lira, et al. 2023). We need to identify that line so that we do not cross it and lose the personal touch of our work.

Requiring New Knowledge

AI is an ever-changing model that will go through multiple iterations throughout its time in our work. “Artificial intelligence continues to develop, and new ways of application in education emerge” (Chen, et al. 2020; 75265). By the time we begin the implementation phase, new programs and technologies can disrupt this. With the changes, we need professional staff who can take this challenge on. This can be a concern amid shrinking resources and a changing professional landscape within the admissions office. If we are going to use this new technology in our practices, we need to begin allocating resources to support experts in the field.

Recommendations for Best Practices

Beginning this implementation process can seem challenging, but there are steps that can be taken at a department level that meet best practices. Starting off small is achievable for most admissions departments. This can be done utilizing existing AI systems through marketing and communications with prospective students. These systems can generate drafts of communication plans, freeing staff to focus on finer details. Institutions also have existing data sets that can be used at a local level. “When existing data is used to create predictive models, the behaviors and features of these models provide a powerful opportunity to better understand both the potential impact of policies on different populations, and the limitations of the models themselves” (Van Busum and Fang 2023; 17).

Most admissions professionals lack the foundational knowledge of AI needed for their work. There are, of course, educational technology companies that can provide this service. These are the true experts we can rely on to oversee high-level implementation across our application process and recruitment strategies. In addition, higher education institutions have internal experts in these fields who can support this implementation.

When we begin to include AI in our application process and potentially its review structure, experts often recommend establishing specific measures. AI has made it possible to read textual material in a statistical way (Alvero, et al. 2020). When admissions offices begin setting up their enrollment targets, they can build out keywords that current AI systems can highlight in applicants’ admissions essays. This can also help summarize the key traits of our incoming classes and inform changes to our application process.

Conclusion

AI may seem very new, but it has been impacting our lives in many ways. Working in admissions requires us to continually adapt to the latest trends and programs. Some may feel hesitant about using artificial intelligence in the admissions process, citing concerns about equity, the risk of losing professional staff, or fear of something new and ever-changing. When admissions departments connect with education technology providers and peers in our field who are already engaged in this work, it can help alleviate concerns. We must use our resources in efficient ways, including the implementation of AI in our outreach efforts. We can begin to analyze our existing data more effectively and better understand our admissions funnel. We can free up our professionals’ time by using AI to create marketing and communication plans. The institutions that embrace this new practice will be ahead of the curve in our recruitment and enrollment efforts.

References

Alvero, AJ, N. Arthurs, A. L. Antonio, B. W. Domingue, B. Gebre-Medhin, S. Giebel, and M. L. Stevens. 2020. AI and holistic review: Informing human reading in college admissions. In AIES ‘20: Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society, edited by A. Markham, J. Powles, T. Walsh, and A. L. Washington. New York: Association for Computing Machinery.

Chen, L., P. Chen, and Z. Lin. 2020. Artificial Intelligence in Education: A Review. IEEE Access. 8(2020): 75264–75278.

Dennis, M. J. 2018. Artificial intelligence and recruitment, admission, progression, and retention. Enrollment Management Report. 22(9): 2–3.

Garg, L., D. Agarwal, D. Gupta, P. Goel, and P. Jain. 2024. An Intelligent Approach to Admissions using Blockchain and Artificial Intelligence (presentation). Piscataway, NJ: IEEE.

Lira, B., M. Gardner, A. Quirk, C. Stone, A. Rao, L. Ungar, S. Hutt, L. Hickman, S. K. D’Mello, and A. L. Duckworth. 2023. Using artificial intelligence to assess personal qualities in college admissions. Science Advances. 9(41).

Nietzel, M. 2025. January Common App data show rise in college applications this year. Forbes. January 17.

Pedró, F., M. Subosa, A. Rivas, and P. Valverde. 2019. Artificial Intelligence in Education: Challenges and Opportunities for Sustainable Development (working paper). Paris, France: United Nations Educational, Scientific and Cultural Organization.

Van Busum, K., and S. Fang. 2023. Analysis of AI models for student admissions: A case study (presentation). In SAC ‘23: Proceedings of the 38th ACM/SIGAPP Symposium on Applied Computing, edited by J. Hong, M. Lanperne, J. W. Park, T. Cerny, and H. Shahriar. New York: Association for Computing Machinery.

About the Author

Jacob Henry has worked in higher education for the past ten years and currently works in college admissions at the University of Colorado Boulder. His past research areas have included the implementation of test-optional admissions policies, the centralization of underrepresented student support services, and political engagement/motivation among college students. Henry holds a bachelor’s degree from Bowling Green State University and a master’s degree from Indiana University Bloomington.