Article

The art of possible: Intentional AI and data analytics in higher education

May 03, 2024·Authored by Dave DuVarney, Jordan Anderson

With expenditures for artificial intelligence (AI) by schools globally expected to grow from $2.13 billion in 2022 to $25.77 billion in 2030, AI in higher education is becoming increasingly more prevalent across all departments with the push towards a data-driven future. With institutions collecting, curating and leveraging data at scale to streamline processes, enhance decision-making and operate effectively, the imperative of being data-driven is expected to become not only foundational, but also a competitive advantage for higher education institutions.

Embracing data-driven approaches, including the integration of AI, will be paramount for making decisions at scale across institutions’ extensive datasets as they continue to compete for relevance and strive to maintain an optimal student population composition. In the age of AI, it’s critical for board members to have the knowledge to ask the right questions and make informed decisions on AI opportunities.

How AI and data analytics are reshaping higher education

From enrollment fluctuations to heightened competition and evolving student needs, colleges and universities are grappling with a variety of challenges that demand innovative solutions, such as:

Enrollment declines: Institutions are facing difficulties in maintaining consistent and sustainable enrollment numbers. Colleges and universities must adapt their recruitment and retention strategies to attract and retain students effectively.
Workforce gaps: Employers and taxpayers are seeking better alignment between credentials and degrees provided by higher education and the skills required to support quality of life within a region (e.g., healthcare, high growth industries).
Increased competition: With the expansion of online education and the globalization of higher education, institutions face heightened competition from both traditional and non-traditional competitors. This increased competition requires institutions to differentiate themselves by offering unique programs, specialized services and innovative learning experiences.
Expanding student needs: Today’s students are diverse across multiple factors and therefore have diverse needs ranging from hours of availability to attend classes and academic support needs to career readiness resources and mental health services. Institutions must cater to these varying and increasing needs by providing comprehensive support systems and personalized services.

Leveraging AI and data analytics presents a transformative opportunity for colleges and universities to address these challenges to improve decision-making, optimize operational resources, enhance student outcomes and maintain their competitive edge.

Additionally, AI is being utilized by faculty, students and staff across institutions to streamline administrative processes, enhance teaching and learning experiences and access educational resources more efficiently – freeing up time and resources for other value-added opportunities. These AI uses include:

Personalized learning: Tailoring educational experiences to individual student needs and learning styles, including adoptive learning platforms that adjust content and pace based on student performance.
Automated grading and assessment: Assisting in grading assignments and exams, particularly for objective questions, saves time for educators and allows for more consistent and unbiased evaluation.
Virtual tutors and assistants: Chatbots or virtual assistants can provide students with additional support and resources, answering questions and offering guidance on a wide range of topics.
Predictive analytics: By analyzing student data, AI can predict student performance and identify those at risk of failing or dropping out, allowing for early intervention and support.
Enhanced research: Processing and analyzing large data sets more efficiently than humans can aid in complex research projects across various fields.
Curriculum development: Helping design curricula by analyzing job market trends and predicting future skills requirements ensures that educational programs remain relevant and effective.
Language learning: AI-driven language learning tools can provide personalized feedback and immersive experiences, helping students to learn new languages more effectively.
Content creation and curation: Assisting in creating and organizing educational content ensures it is up-to-date, relevant and tailored to student needs.
Fraud detection and academic integrity: Helping detect plagiarism and other forms of academic dishonesty ensures the integrity of academic work.
Administrative automation: Streamlining administrative tasks like scheduling, enrollment and student inquiries makes the process more efficient for both students and staff.
Admission management: AI applications help to auto-generate communication and workflow prompts and predict highest potential students (i.e., enrollment probability and positive student outcomes) for recruitment focus.

Overall, the integration of AI and data analytics is fostering a more adaptive, efficient and student-centered higher education ecosystem, poised to meet the evolving needs of students and staff in the digital age.

The Board’s role to realize the power of AI and data analytics

For AI and advanced analytics to be successfully executed at a higher education institution, board members need to stay on top of several key areas:

The Board’s role to realize the power of AI and data analytics

Support investment: Board members need to advocate for sufficient financial resources to be allocated towards AI and advanced analytics initiatives. This includes investments in technology infrastructure and data management systems to ensure successful implementation and ongoing support for these initiatives.
Ensure strategy: The Board should ensure that the institution's AI and advanced analytics strategy aligns with its overall mission, vision and strategic goals. They should oversee the development of a comprehensive strategy that outlines the objectives, priorities and road map for integrating AI into various aspects of the institution's operations and academic programs.
Require basics: Board members must ensure that the institution has established foundational elements necessary for successful AI implementation. This includes robust data governance policies, data quality assurance processes and cybersecurity measures to safeguard sensitive information and mitigate risks associated with AI deployment.
Be inquisitive: Board members should maintain a curious and proactive approach to understanding AI technologies and their potential impact on the institution. They should ask critical questions about the benefits, risks, ethical considerations and implications for students, faculty and staff, seeking regular updates from institutional leadership on AI initiatives.
Celebrate innovation: Boards should recognize and celebrate innovative AI and advanced analytics initiatives that demonstrate tangible value and contribute to achieving the institution's strategic objectives. By fostering a culture of innovation, board members can inspire continued investment and commitment to AI-driven digital transformation.
Fulfil fiduciary role: Board members have a fiduciary responsibility to advance the institution forward by overseeing AI and advanced analytics initiatives and ensuring they are conducted ethically, responsibly and in compliance with relevant laws and regulations.

What should be in place before implementing AI or advanced analytics?

Implementing AI or advanced analytics requires detailed planning, strategic alignment with institutional goals and a strong understanding of the current technological landscape. Leaders need to consider both the technological aspects of these initiatives as well as how they will be deployed, adopted and used throughout the institution. AI initiatives should not be championed by information technology leaders only. Assessing for AI readiness can help to identify and mitigate gaps and risks that need to be addressed prior to launching or accelerating initiatives to ensure AI is deployed in a safe and responsible manner.

Before implementing AI or advanced analytics, higher education institutions need to first assess their current state foundation, including evaluating existing data infrastructure, governance practices and technological capabilities to identify strengths, weaknesses, opportunities and risks related to AI and advanced analytics implementation. It's essential to engage a broad base of institutional constituents, determined by the intended AI adoption impact (e.g., involve students if the student experience is impacted) in the planning and implementation process to foster buy-in and collaboration – a vital component for ensuring that these initiatives are successful, sustainable and aligned with the needs and priorities of the institution and its stakeholders.

Additionally, establishing a core dataset and common data platforms is crucial for data consistency and interoperability across various departments and systems. Developing a dedicated program, such as a data excellence center, with a designated data steward and a clear charter outlining its mission, objectives and responsibilities is critical. By centralizing data management and providing a unified foundation for data-driven initiatives, institutions can unlock the full potential of their data to drive positive outcomes and transformative change across the organization.

Lastly, determining the optimal organizational placement for the AI and analytics initiatives within the institution's structure is necessary to facilitate effective coordination, communication and integration with other departments and initiatives.

Baker Tilly can help

As AI and data analytics continues to reshape the higher education industry, it’s crucial for institutions to proactively embrace its potential. Board members play a pivotal role in ensuring their institutions are equipped to navigate the complexities of AI implementation by staying informed, asking pertinent questions and making strategic decisions.

Baker Tilly’s digital team offers a variety of AI services, from a readiness assessment through implementation, to help your institution navigate the complex landscape of AI so you can safely and proactively leverage its transformative power.

Interested in learning more? Contact one of our professionals today.