What Is Left for IR When the Provost Can Use AI to Answer Their Own Data Questions?
Historically, IR offices served as the primary interface between institutional data and decision-makers. IR professionals extracted data from institutional systems, ensured it was accurate and well-defined, applied context drawn from policy and history, and delivered results to campus leaders. That model depended on distance: data lived in complex systems and expertise lived in IR.
That distance is shrinking rapidly.
Interactive dashboards, self-service reporting platforms, and now AI-powered tools have narrowed the gap between data and its consumers. Provosts drill into enrollment trends themselves. Deans explore retention patterns by subgroup without submitting a request. Leaders can ask a system a question in plain language and receive an immediate answer.
This shift raises an uncomfortable but necessary question for the field. If leaders can answer their own data questions, what is left for IR?
Shifting Landscape with AI
Technology shifts the landscape. Currently, we consider the changing role of IR in reference to advancements in generative AI. While AI certainly demands reconsideration of the role of IR, we have seen a similar pattern with the availability of dynamic dashboards in self-serve data platforms.
Data literacy among senior leaders has increased. Expectations have changed. Many leaders now assume that institutional data should be accessible, timely, and explorable without mediation.
AI accelerates this shift. Natural language interfaces can summarize dashboards, surface trends, and generate narratives that once required analyst time. In some environments, leaders can already ask questions like “What is happening to retention for first-generation students?” and receive a validated response drawn from curated institutional data.
The Role of IR
This does not mean IR was doing unnecessary work. It means the value of that work is being reallocated. Tasks that center on data retrieval, routine summarization, and basic interpretation are increasingly automated. Holding onto those tasks as a core identity is not a viable long-term strategy for the IR office. Failure to reestablish the value of IR is a very real risk to the relevance of the profession.
Redefining the Value of IR
As data sources proliferate across SIS, LMS, CRM, financial aid, residence life, and other systems, the need for coherence increases. AI can process large volumes of information, but it cannot decide which definitions are appropriate for a given decision, which metrics align with institutional priorities, or where historical context changes interpretation.
These responsibilities increasingly define the value of IR:
- Data validation and governance. Ensuring that AI and self-service tools operate on trusted, well-defined data.
- Curation. Determining which dashboards, metrics, and questions should be available to whom, and where limits should be in place.
- Institutional context. Applying knowledge of policy, history, and strategy that is not reflected in data systems.
- Risk identification. Highlighting where automated summaries or disaggregations may mislead or oversimplify.
- Translation to action. Connecting analysis to decisions, tradeoffs, and institutional goals.
In this model, IR does not compete with AI but rather guides use of it. As AI tools become embedded in daily workflows, institutions need guidance on responsible use. This includes clarifying appropriate questions, explaining limitations, and reinforcing ethical considerations around equity, privacy, and interpretation. IR is well positioned to lead this work, in partnership with IT, data governance bodies, and campus leadership.
Technology to Amplify Rather than Undermine the Impact of IR
Strategic use of technology can accelerate IR’s impact rather than undermine it. For example, Precision Campus can automate routine reporting, embed validated metrics directly into leadership workflows, and pair AI-driven access with strong governance. The benefits are multi-faceted. Access to data is expanded in an intentional and responsible manner. IR professionals are freed from repetitive work and able to create space for higher-value contributions. When implementation is informed by the values of the IR profession, technology does not replace IR judgment – it operationalizes it at scale.
So, What is Left for IR?
Plenty. But not the same work, and not in the same posture.
IR’s future lies less in producing answers and more in shaping the use of data. Less in querying data for static reports and more in empowering users to utilize tools that allow data to inform decision-making. Less in reacting to requests and more in guiding institutional sense-making.
When the provost can answer their own data questions, IR’s contributions shift to helping ensure that those answers are meaningful, responsible, and aligned with the institution’s goals.
