Artificial intelligence (AI) is a game-changer, but how can institutions ensure the adoption of principled approaches to integrating AI across their campus? The Institutional Research & Effectiveness Services (IRES), part of the Ellucian Success Services division, equips institutions with the tools and strategies needed to use AI responsibly. We help higher education leaders and data professionals implement data governance frameworks, design ethical analytics, and translate complex findings into evidence-based decisions that move the needle on student success.
In this article:
- Why institutional research professionals are essential to ethical AI implementation
- The expanding role of IR/IE teams in campus AI strategy
- Four core IRES service areas that support your IR team
- Five critical data domains for AI-driven student success predictions
- How Ellucian IRES consultants guide your AI adoption journey
Why Institutional Research Professionals Lead Ethical AI Adoption
For institutional research (IR) and institutional effectiveness (IE) professionals, the imperative to spearhead technological transformation on our campuses is nothing new. As noted in the 2024 Ellucian AI Industry Report, institutional researchers are typically among the earliest adopters of AI at their institution. AI has reshaped the way institutional researchers collect, analyze, and interpret data. Recent advances in generative AI have augmented our ability to communicate research findings with campus leaders, community stakeholders, and colleagues.
However, a thoughtful and strategic approach to new technology remains essential. In fact, the Association for Institutional Research (AIR) has long challenged its members to embrace a balanced approach as we modernize our array of student success initiatives. One of the key goals outlined in AIR’s Statement of Ethical Principles calls on us to reduce algorithmic inequality and latent bias in campus-based institutional effectiveness efforts, especially ones that leverage AI tools to process and analyze large datasets for predictive modeling purposes.
Likewise, the EDUCAUSE Horizon Report: Teaching and Learning highlights several of the core competencies found in the modern IR/IE professional. The 2025 report extols the value of critical data literacy and a human-centered attitude toward AI. These are strategies that IR/IE professionals frequently employ to mitigate the potentially harmful effects of AI in student success interventions.
From Data Analyst to AI Strategy Partner: The Expanded IR Role
IR/IE professionals recognize the value of accurate and trustworthy data. We know how to analyze data so it can inform effective, evidence-based decisions that promote student success. We manage both external compliance projects and internal business intelligence and analytics systems that rely on this data.
So, what else can IR/IE staff do?
The advent of AI has amplified our understanding of how IR/IE units can contribute additional value to a campus community. AI has the potential to streamline previously mundane data preparation tasks and provide novel analytics to guide policy and practice decisions. A highly functional IR/IE team should be able to accomplish both.
First, IR/IE staff are front-line data experts who can oversee large-scale technology projects to produce strategic metrics. We are frequently tasked with integrating data from disparate sources such as learning management systems, early alert systems, and other complex data domains.
Second, IR/IE professionals have developed rigorous and ethical methods for conducting research and disseminating findings with AI. As a result, we are uniquely positioned to aid campus leadership as they consider incorporating AI-based solutions in other areas. This opportunity underscores the expanded role data coaches and internal decision-support consultants, to leaders across campus.
In summary, AI offers new advantages for quickly processing and interpreting multifaceted student success data and rendering actionable insights. However, IR/IE professionals also understand that as the higher education industry marches headlong toward an AI-infused future, we must galvanize efforts to uphold the virtues described in the 2025 EDUCAUSE report: the ability to “maintain human-centered teaching and learning” (p. 16) while preserving knowledge that underscores “uniquely human qualities — such as ethical judgment, empathy, and innovative thinking” (p. 17).
Four Core Services: How IRES Supports Institutional Research Teams
IRES consultants provide comprehensive support across four service areas that form the foundation of effective institutional research programs.
Ellucian’s IRES practice provides four comprehensive service areas that address the full spectrum of institutional research and effectiveness needs:
1. Data Governance
We help you enable better decision-making, reduce operational friction, and improve data accuracy and quality. Strong data governance is the backbone of any successful AI implementation, ensuring that your institution has clean, reliable, and ethically-sourced data to power student success initiatives.
2. Data Gathering, Reporting and Analysis
Our consultants support your efforts to understand current performance, identify opportunities for improvement, and report status and results. Specific activities include the dissemination of institutional data and information through research, data gathering, and analysis. We help you transform raw data into actionable intelligence.
3. Organizational Development
Leadership assistance is critical when developing and using question definitions to inform data gathering and outcome methodologies. IRES consultants prepare presentation materials for higher-level decision-makers, such as Boards of Trustees, state-wide coordinating boards, affinity groups, and associations/consortiums. We also provide appropriate training to institutional leaders (administrators, faculty, and staff) in accessing data and using it to inform decision-making.
4. Decision Support and Institutional Effectiveness
Accreditation support provides both the facilitation of the accreditation process and the consolidation, analysis, and review of necessary data and measures. Our consultants bring an understanding of current trends, best practices, and processes that ease the burden of accreditation processes while strengthening your institution’s overall effectiveness framework.
Five Critical Data Domains for AI-Driven Student Success Predictions
A robust student success predictive model requires data from five key domains that represent a comprehensive, holistic view of each student’s lived experience.
The key to a robust student success predictive model is the inclusion of data that represents a comprehensive, holistic cross-section of each student’s lived experience.
Fixed data points (like student demographics) must be augmented by emergent and ongoing variables (like curricular and extra-curricular engagement patterns and survey responses) to explain the variability in performance metrics such as academic momentum, cumulative GPA, persistence, retention, and graduation rates.
The Five Key Data Domains:
1. Student Demographics
Fixed data points like ethnicity, race, sex, geographic origin, military status, and family factors (first-generation, single parent, low-income). While these baseline characteristics provide important context, they represent only the starting point of a comprehensive predictive model.
2. Academic Engagement
Ongoing evaluation of student performance in the classroom through Learning Analytics (LA) data from the Learning Management System. This includes student support services utilization such as tutoring, writing and/or math skills center visits, and career center engagement. These behavioral indicators reveal how students interact with academic resources.
3. Social Engagement
Ongoing attendance and participation rates in campus-based activities, including student orientation, learning communities, recreation center usage, Registered Student Organizations (RSOs) and social groups, and other High-Impact Practices. Social integration is a proven predictor of student persistence.
4. Student Self-Assessments
Self-reported life events (employment changes, medical issues, food insecurity) plus noncognitive factors (academic self-efficacy, commitment to school, test anxiety, grit). Regular pulse surveys and data from the Early Alert System (EAS) provide real-time insights into student well-being and challenges.
5. Academic Preparation
Evidence of prior student success in high school or previous college studies, regularly updated with term-based data as each cohort makes progress at the institution. This longitudinal view helps identify patterns and predict future performance.
Critical Questions for Your Campus:
As you consider implementing or expanding AI-driven student success analytics, ask yourself:
- Who is responsible for gathering and storing data used in student success analytics?
- Who designs the research methods?
- Who communicates about trends to stakeholders?
If the answers aren’t clear, your institution may not be positioned to leverage AI effectively—or ethically. This is where institutional research and effectiveness professionals become indispensable partners in your AI adoption journey.
How Ellucian’s IRES Practice Can Assist Your Institution on Its AI Adoption Journey
IRES consultants can help activate your school’s institutional research and effectiveness team to enhance their strategic value. Through collaboration with Ellucian’s IRES, institutional leaders are better equipped to apply critical data literacy skills that enable thoughtful and pragmatic engagement with AI tools on their campus.
Educators must remain mindful of their strategic and ethical responsibilities when working with technology and student data. This strikes at the core of Ellucian’s Strategic Services consulting practice. We offer a set of techniques that IR/IE professionals can use to achieve outcomes through technological innovation without sacrificing human-centered research design principles.
The Four Pillars of Our Consulting Methodology
Our consulting methodology emphasizes four critical pillars:
1. People
2. Process
3. Technology
4. Data
These pillars serve as the foundation for building a sustainable AI strategy with critical data literacy at its core. Through partnership with Ellucian’s IRES consultants, your campus’s institutional research and effectiveness practitioners can assist with formulating an adoption plan that balances innovation with institutional values, equipping colleges to implement AI in ways that enhance, rather than compromise, the academic mission.
Schedule time with a IRES consultant and begin a journey that will help enable IR/IE thought leadership to make ethical adoption of AI a reality on your campus.
