By Mark McConahay, Senior Consultant, AACRAO Consulting
At this year’s Ellucian Live 2026 Conference, one theme consistently emerged across conversations: the growing role of agentic AI in student information systems. While AI has been part of higher education technology conversations for several years, the tone has shifted, the prospects exciting, and the time for careful evaluation is now. This was not about isolated features, experimental pilots, or responding to individual queries. Rather, it was about AI taking action on your behalf and completing multi-step tasks (workflows) autonomously without invocation from a staff member. That distinction matters and signals where the SIS and vendor landscape is heading. The potential is phenomenal, but it raises important questions for institutions about how these tools will function in practice.
What ‘agentic AI’ means in this context
In this setting, “agentic AI” refers to AI tools that sit on top of core systems and actively assist users in navigating tasks, surfacing information, and executing workflows. Rather than requiring users to move through multiple screens or systems, these tools aim to interpret intent and guide, or even complete, actions on their behalf. Unlike general AI (like a chatbot), the model used is deterministic (a system that follows pre-defined, reliable rules, where the same input always produces the same output).
At the conference, much of the emphasis was on how these AI capabilities operate within a vendor’s own ecosystem. The promise is a more seamless, intuitive, and more efficient experience.
Why this matters for AACRAO members
For registrars, enrollment professionals, and other campus leaders, this shift is not abstract. AI-enabled layers tied to student systems will increasingly show up in product updates, demos, and procurement conversations. The key question is not simply whether AI is being added but how well these tools function across institutional processes and systems.
Institutions depend on complex, interconnected workflows—transfer evaluation, degree audit, credentialing, reporting—often spanning multiple platforms. Careful consideration needs to be applied to these inter-platform processes to ensure validity, reliability and effectiveness, and to identify any new friction points. In addition, practitioners need to be aware of issues such as consent for automated disclosure, data privacy (FERPA), generation and monitoring of audit files, procedural drift (where small errors can compound over time), and others.
These considerations have direct implications for system implementation, staff training, and long-term flexibility.
The interoperability question
This leads to a concern that is both practical and consequential for the learners AACRAO members serve. As noted above, most institutions do not operate within a single vendor environment. Even campuses anchored by a primary SIS rely on a constellation of tools: CRM platforms, degree audit systems, credentialing solutions, and data warehouses, each holding a piece of a student’s academic story. When agentic AI operates effectively within one product suite but, potentially, not across others, the results can be invisible to staff and potentially harmful to students. An automated workflow that doesn’t have access to a complete, current record can produce decisions that are technically executed but factually wrong—and because they happen without human review, errors may not surface until significant damage is done.
Interoperability, then, is not simply a technical preference; it is a student protection issue. Without shared data structures, agreed-upon standards, and open integration approaches, AI tools risk creating the appearance of efficiency but might quietly compound the fragmentation underneath.
For AACRAO members, this is why conversations about SIS interoperability, data standards, and open architectures must be elevated, not treated as infrastructure debates, but as foundational to ethical AI governance. AI does not replace the need for interoperability. It makes the cost of neglecting it much higher.
What AACRAO is working on
AACRAO’s current work in this space, guided by the Technical Advisory Council, is intentionally focused on helping institutions think beyond a single-system perspective. Several efforts are underway, including:
Development of normative data structures to support more consistent data exchange
Exploration of AI and operational interoperability, including how AI tools interact across systems
Mapping core use cases, such as transfer articulation and credential exchange, to emerging AI applications
Together, this work is aimed at creating a foundation that allows institutions to evaluate and adopt new technologies with a clearer understanding of how they will function within a broader ecosystem.
Practical takeaways
As agentic AI becomes more visible in vendor offerings, institutions may benefit from focusing on a few key questions:
Where is AI being layered into existing systems and workflows?
Does it function only within a single vendor environment, or across multiple systems?
What data structures and integrations are required to make it effective?
How will it impact existing processes, not just individual tasks?
These considerations are increasingly relevant in procurement and implementation discussions. Understanding not just what a tool does, but where and how it operates, will be essential to making informed decisions.
Looking ahead
Agentic AI is gaining traction quickly, and it has the potential to improve and reshape how users interact with student systems. But its effectiveness at the institutional scale will depend heavily on interoperability—on whether these tools can operate across the full range of systems that support the student lifecycle.
AACRAO’s ongoing work is intended to help members navigate this shift with a focus on long-term flexibility, coherence, and student-centered outcomes.
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