In this Q&A, Zach Pendleton, Chief Architect at Instructure, breaks down how “agentic AI” is reshaping the future of digital learning. As higher education continues to evolve in response to rapid technological shifts, a new question is emerging: Are universities ready for the next major leap in artificial intelligence?
While many institutions are still learning to manage generative AI, an even more capable class of technology is already taking shape — agentic AI. Unlike generative AI, which creates content based on prompts, agentic AI can plan, reason, and execute multi-step tasks autonomously, opening the door to a new era of intelligent, responsive learning environments.
What exactly is “agentic AI,” and how does it go beyond the generative AI that educators are still adapting to?
Pendleton: Agentic AI refers to systems capable not only of generating content but also of reasoning, planning, and executing multistep tasks. This emerging technology is set to reshape how universities build and manage digital infrastructure to scale personalised learning.
Where generative AI responds to simple prompts, agentic AI can act with intent, learn from context, and carry out complex workflows to achieve specific outcomes.
Today, teachers may use generative AI to draft an email to struggling students — but they must still identify those students and send the message. In an agentic system, an instructor can instead ask the agent to “find all students who scored below 60% on the last assignment and send them an email offering extra help.”
In real-world terms, how could agentic AI transform the daily experience of students, faculty, and administrators?
Pendleton: For students, agentic AI can create frictionless, personalized learning pathways — from generating summaries and translations to guiding study progress within the learning environment itself, without relying on external apps or scattered tools.
For faculty, it can align rubrics, detect disengagement patterns, and suggest timely interventions for at-risk learners.
For administrators, agentic systems can automate routine queries, reporting, and cross-department workflows, freeing them to focus on strategic initiatives.
In short, it introduces an ecosystem where every student, teacher, or administrator gains a personalised assistant capable of anticipating needs and driving meaningful outcomes — provided it is safely and properly integrated with existing tools.
Many still see AI as a disruptor or threat. How can universities reframe it as a partner in learning and operations instead?
Pendleton: Universities must shift from “policing AI” to partnering with it. Instead of treating AI tools as external disruptors, institutions can embed them into structured, outcomes-driven engagement that emphasises transparency and trust.
This shift includes designing courses and assessments that account for AI use — not to ban it, but to harness it responsibly. It also requires clear communication about how data is used and protected within institutional systems.
When educators and learners see AI as a collaborative framework that augments human expertise, it becomes a catalyst for deeper learning and operational excellence.
What does an “agent-ready” virtual learning environment look like, and what core technologies must universities have in place to build it?
Pendleton: Agentic AI cannot operate effectively if the underlying infrastructure is closed, fragmented, or outdated. Universities need agent-ready architecture: unified data access under institutional control, robust and transparent APIs that support emerging standards, and interfaces designed for both human and machine use.
This setup allows AI agents to access the right data safely and act across systems without compromising institutional control. Only universities that prioritize VLE modernization within their pedagogical strategy will be positioned to build cloud-based, agent-friendly systems — placing them at the forefront of higher education’s next digital transformation.
If you were advising universities in the Philippines and across Asia, what practical steps should they take now to prepare for this next wave of AI?
Pendleton: According to the 2025 State of Higher Education, 66% of students in the Philippines are open to flexible learning, with 71% valuing anytime-anywhere study options. At the same time, 83% of educators prioritise lifelong learning and support non-traditional pathways. Another 83% say academic staff are poised to adopt AI — but leadership involvement remains limited.
This highlights both opportunity and urgency. Universities must first raise the bar for transparency and trust. That means using virtual learning environments that safeguard student data, prevent it from being used to train external models, and clearly explain how information flows across institutional systems.
Next, institutions should invest in faculty development so educators can design courses, assessments, and learning experiences that integrate AI responsibly and effectively.
Finally, universities must adopt a readiness mindset grounded in ethics, transparency, and continuous evaluation of emerging AI tools. Those that lay the groundwork for agent-friendly environments today will strengthen academic integrity and position themselves at the cutting edge of higher education’s data-driven future.
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