The Pulse of Higher Ed

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from UPCEA’s Research and Consulting Experts

AI Readiness and Its Relationship to Enrollment Management in Continuing Education

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By Vickie Cook

Enrollment management plays a pivotal role in the success of any online and professional continuing education units through impact on revenue generation, learner engagement, and program sustainability. AI-driven business process automation (BPA) offers transformative solutions to streamline enrollment workflows, enhance recruitment strategies, and improve the overall student experience through allowing staff to focus on human interactions while BPA supports repetitive back-office tasks. Business process automation allows units to determine where their efforts can best be used for their clients and students and which processes are better aligned to being managed through machine learning and automation.  For online and professional continuing education units, achieving AI readiness is essential to integrating BPA tools effectively.  This integration allows staff to be more effectively in dealing with clients, students and customers building relationships. 

Streamlining Enrollment Processes 

Automation can significantly reduce manual workloads associated with enrollment management back-office tasks. Processing applications, verifying documents, and managing waitlists can be handled most efficiently by AI systems. For example, optical character recognition (OCR) tools powered by AI can digitize and validate transcripts, while machine learning algorithms can prioritize applications based on predefined criteria. This not only reduces administrative errors but also accelerates response times, enabling institutions to meet learners’ expectations for faster decisions. 

Enhancing Recruitment through Marketing 

AI readiness enables online and professional continuing units to adopt data-driven recruitment strategies. By analyzing historical enrollment data, AI can identify patterns and predict which programs are likely to attract the most interest.  Additionally, predictive analytics can be utilized to determine likelihood of completion. AI-powered tools like customer relationship management (CRM) systems can personalize marketing campaigns, deliver targeted messages to prospective students based on their interests, location, or professional background. For instance, CRM systems can use AI to segment audiences and optimize outreach efforts, leading to higher conversion rates. In today’s competitive environment, it is important to consider the impact of hyper-personalization with students searching for their continuing education partners to help them meet their goals. 

Improving Retention Through Predictive Analytics 

Retention is a critical factor in the success of online and professional continuing education programs. AI-driven predictive analytics can identify at-risk students by analyzing factors such as attendance, grades, and engagement within learning management systems. Online and professional continuing education programs units can then implement timely interventions, such as offering tutoring, adjusting course loads, offering career building engagements, or providing financial counseling. While more research in this area is needed related to the impact of machine learning and AI on retention efforts, it is apparent from those that have been published the AI may demonstrate more effective student feedback to support overall student retention efforts.  It is critical that all communications with students and the determination of data analysis should be reviewed carefully for bias and discrimination that may inadvertently lower student persistence. 

Concluding Thoughts 

AI-driven strategies may be a game changer for enrollment management practices in continuing education. By streamlining processes, enhancing recruitment efforts, and improving retention, AI empowers online and professional continuing education programs units to address the challenges of a competitive higher education landscape. By leveraging AI effectively, online and professional continuing education programs units can ensure their enrollment management strategies are both innovative and impactful, fostering sustainable growth and learner success.  

To learn more about the impact of being AI ready on enrollment management: 

  1. IACTE (2024). Artificial Intelligence in adult learning: IACTE’s guide to the future of learning. https://www.iacet.org/miscellaneous/iacet-information-brief-generative-ai-in-ce-t/  
  1. Robert, J. (2024).   The Future of AI in Higher Education Administration. EDUCAUSE. https://www.educause.edu/ecar/research-publications/2024/2024-educause-ai-landscape-study/the-future-of-ai-in-higher-education  
  1. Bashkara, V. (2024). How AI admissions recruiters will transform enrollment.  https://www.forbes.com/sites/vinaybhaskara/2024/05/21/how-ai-admissions-recruiters-will-transform-enrollment/ 

 

Vickie Cook is the Vice Chancellor for Enrollment and Retention Management and a Research Professor of Education at the University of Illinois Springfield, as well as a Strategic Advisor for UPCEA Research and Consulting.  To learn more about UPCEA Research and Consulting, please contact [email protected].  

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