Is There ROI For AI In Online Education?

Dr. Anthony A. Pina, Chief Online Learning Officer, Illinois State University

Dr. Anthony A. Pina, Chief Online Learning Officer, Illinois State University

Although the current political climate affecting higher education is dominating headlines, interest in artificial intelligence (AI) in higher education remains at a fever pitch. In an era where many colleges and universities have closed, while others are making significant cuts due to budget deficits, does investing in AI make fiscal sense? As higher education leaders are having to make difficult decisions regarding spending and resources, can implementing AI at our institutions be considered in terms of cost benefit and return on investment (ROI)?

AI Benefits

The promise of AI lies in its ability to realize benefits through increased efficiencies, capabilities, and scalability, leading to overall reductions in cost. While the saying, “AI won’t take your job--someone using AI will” is found throughout the Internet (and is attributed to different people), AI-driven automation can take over repetitive administrative tasks—from admissions processing to compliance reporting—allowing institutions to redeploy staff toward higher-value functions. Predictive analytics can enhance marketing strategies by identifying students who are most likely to enroll and persist. AI tools can streamline the design and delivery of instruction. Faculty can leverage AI for course design, grading, feedback, and content generation. Adaptive learning systems personalize instruction to meet individual student needs, improving learning outcomes while reducing demand on instructional staff.

Virtual assistants and chatbots provide 24/7 support, guiding students through onboarding, financial aid, advising, and more. AI-driven analytics can predict at-risk students and tailor interventions to improve retention. AI can improve institutional reputation by enhancing the student experience and helping colleges manage online reviews, spotlight success stories, and respond effectively to criticism.

“AI in higher education is not just a technical shift— it is a strategic transformation”

The most obvious–and most controversial—fiscal benefit of AI is its potential to reduce personnel costs (salaries and benefits) by performing tasks previously done by human workers. While automation has long been a method to reduce operational budgets, this benefit also comes with the costs of cultural resistance and morale mentioned in the next section.

AI Costs

AI Costs Despite the many advantages, AI implementation requires a thoughtful analysis of costs, including AI Applications: Licensing costs can range from free to hundreds of thousands of dollars depending on the tool and scope. Enterprise-level applications such as AI-enhanced LMS platforms or campuswide tools may require significant investments. Infrastructure: Many institutions will need to upgrade network capabilities, storage systems, and computing hardware to accommodate AI systems. Data Security and Privacy: Compliance with data privacy laws (e.g., FERPA) and ensuring cybersecurity adds a layer of operational cost, particularly when managing sensitive student information. Training: The value of AI is only realized when users understand how to apply it effectively. Institutions must invest in comprehensive training and support systems. Cultural Resistance and Morale: AI adoption can lead to workforce anxiety over job displacement, necessitating change management strategies to maintain morale and productivity. Environmental Impact: AI systems often require substantial energy and water resources. Leaders with sustainability mandates must weigh these considerations in their planning.

AI and ROI

Leaders evaluating the return on AI investments must move beyond simple profit metrics. ROI in higher education can— and should—encompass both tangible and intangible benefits. Suggested ROI metrics include:

• Reduced labor and operational costs

• Time savings for faculty and staff

• Increased student satisfaction and retention

• Improvement in course completion and academic outcomes

• Greater efficiency in course design and student services

• Enhanced marketing reach and enrollment yield

• Extended lifespan of physical assets through predictive maintenance

To assess these metrics effectively, institutions should compare “pre-AI” and “post-AI” data, recognizing that initial implementation may result in a temporary productivity dip as users adapt. The pre- and post- data may include number of employees, costs of salary and benefits, time spent on tasks, survey and test scores, number of courses created, number of students who received services, number of recruitment leads converted into enrollments, number of enrollees from targeted markets and differences in maintenance schedules.

Maximizing ROI

To ensure AI investment leads to meaningful returns, institutional leaders should consider the following: Create a cross-functional AI steering committee including stakeholders from across campus ensures broad buy-in and holistic decisionmaking. Communicate transparently, explaining the value of AI to faculty, staff, students and trustees. Use data and real-world examples to build confidence and excitement. Providing comprehensive training to support users via diverse training options, including workshops, online modules, guides and AI-assisted support. Prioritize scalable solutions by selecting AI tools that address systemic needs and can scale across departments and disciplines. Starting small and scaling strategically by beginning with pilot programs to identify challenges, build champions and refine your approach before large-scale deployment.

AI and Leadership

AI in higher education is not just a technical shift—it is a strategic transformation. ROI in online learning includes more than dollars. It includes access, equity, innovation and institutional vitality. AI can extend the reach of a university to non-traditional students, improve support for those with disabilities and offer personalized learning-at-scale. But these outcomes are not automatic. They require vision, leadership and an unwavering focus on long-term value. For higher education institutional leadership facing the realities of constrained budgets and rising expectations, AI represents both a challenge and an opportunity. Embracing it wisely may well define the next era of higher education.