A significant shift is on the horizon for artificial intelligence in higher education. According to a new forecast, the era of AI as a helpful but dependent assistant is ending. The next phase, expected by 2026, will see AI evolve into an independent, goal-oriented project manager that executes complex plans without constant human instruction.
From Helpful Assistant to Autonomous Agent
The prediction comes from Ray Schroeder, Senior Fellow at UPCEA, the US-based online and professional education association. In the report "Predictions 2026: Insights for Online & Professional Education," Schroeder outlines the arrival of a second wave of AI, termed "Agentic AI." This version is framed not as smarter assistance but as independent execution.
This Agentic AI will function as a 24/7 project manager for universities. It can comprehend a high-level objective, devise a multi-step plan to achieve it, execute that plan across various software systems, and learn from errors autonomously. This promises to lighten the workload for faculty, staff, and students continuously, operating at computer speed and reliably reporting back. The result will be significant time and cost savings, enabling work previously deemed too expensive or time-consuming.
The Core Shift: From Answering Questions to Owning Outcomes
This forecast is not about better chatbots or more fluent tutors. It describes a fundamental change in agency. Current campus AI primarily answers questions. Agentic AI changes the relationship by taking responsibility for outcomes. Instead of asking it to draft an email, you would task it with reducing dropout rates, shortening admissions cycles, or improving student support. The AI itself would then determine and execute the necessary steps.
This distinction is crucial because universities often struggle with execution, not ideas. Fragmented systems, understaffed offices, and cumbersome processes drain resources. Agentic AI, therefore, is positioned as an operational innovation rather than a purely teaching one.
How Agentic AI Works and Its Campus Impact
At its core, Agentic AI operates on a loop: define a goal, break it into steps, choose tools and data, execute actions, check progress, and adjust. In a university setting—where delays often stem from broken process chains, not lack of knowledge—this ability to hold an entire process together is powerful.
It will likely enter through administrative backdoors: admissions offices, student support teams, and academic units bogged down by follow-ups, queries, and compliance checks. Early uses may focus on speeding decisions, reducing hand-off errors, and smoothing routine interactions.
For students, this could mean faster responses and smoother paperwork. For faculty, it could free time from administrative sludge for teaching and research. For administrators, it promises scalability. However, it also raises stakes around accountability, bias, privacy, and the speed at which errors can propagate.
Governance: The Real Challenge Ahead
The move to Agentic AI forces universities to confront governance, not just novelty. The critical question shifts from whether the tool works to who is accountable when it doesn't. Institutions must decide how much authority to delegate, establish clear boundaries, and maintain rigorous oversight.
Universities that manage this well will treat Agentic AI like research ethics or financial controls—with caution and explicit accountability. Those that rush risk adopting systems with shallow automation while inheriting the full risks of delegated action.
The bottom line: Agentic AI represents a shift in how work, responsibility, and authority are distributed within universities. By 2026, the divide will not be about who uses AI, but about who governs it well. The ultimate test will be institutional maturity—the ability to delegate action without abdicating responsibility.
