Why higher education technology isn't reducing faculty burnout or student disengagement—and the AI infrastructure provosts need instead.
TUEL Team
Industry Insights
Higher education technology investment is accelerating. According to Microsoft's 2025 AI in Education Report, 86% of education organizations now use generative AI—the highest adoption rate of any industry [1]. The global AI education market has reached $7.57 billion and is projected to exceed $112 billion by 2034 [2].
Yet despite this investment, two crises continue to intensify: faculty are burning out, and students are disengaging. The problem isn't a shortage of tools. It's a fundamental misalignment between what institutions are buying and what teaching and learning require.
Today's professors face an impossible equation. Class sizes have grown while support staff have shrunk. A single instructor might manage 200+ students across multiple sections, each requiring personalized feedback, office hours, and academic support.
The math simply does not work. When faculty members are stretched across grading, administrative tasks, committee work, and research obligations, meaningful student interaction becomes the casualty. The result is dedicated educators leaving the profession at record rates while those who remain struggle with unsustainable workloads.
How common tools add friction for faculty:
On the other side of the classroom, students are struggling to stay connected. Completion outcomes remain uneven, especially in open-access and commuter settings, and too many students leave before earning a credential.
The reasons are multifaceted but share a common thread: students feel like numbers, not individuals. When a struggling student falls behind in a 300-person lecture hall, there is no safety net. By the time an instructor notices the warning signs, if they notice at all, it is often too late.
Today's students expect personalized experiences. They have grown up with algorithms that anticipate their preferences on streaming platforms and social media. Yet their educational experience often feels like it was designed for a previous generation: rigid, one-size-fits-all, and disconnected from their individual needs and goals.
The higher education technology industry has focused heavily on two areas: administrative efficiency and content delivery. Universities can now process enrollment paperwork faster and distribute lecture videos at scale.
But neither of these capabilities addresses the core challenge: how do you create meaningful educational relationships when faculty are overwhelmed and students are anonymous?
Why many AI tools fall short:
Research from Cornell University found that EdTech developers and educators have fundamentally different concerns: developers focus on technical challenges like preventing AI hallucinations and privacy violations, while educators worry about broader impacts—inhibiting critical thinking, hampering social development, and increasing workload [3]. The result is technology that serves IT departments and procurement committees but fails the people actually doing the teaching and learning [4].
Faculty are accountable for instructional quality, academic integrity, and meaningful student support. Provosts are accountable for retention, equity, accreditation, risk management, and financial sustainability. Any AI investment has to serve these responsibilities first.
Non-negotiables for responsible AI adoption:
This reframes procurement from feature checklists to institutional outcomes: integrity, engagement, and faculty capacity.
Point solutions add narrow capability but multiply workflows. Infrastructure aligns AI with governance, curriculum, and outcomes across the institution. The difference is whether AI sits as a one-off tool or as a managed layer that faculty and provosts can trust.
What infrastructure-level AI enables:
Public benchmarks from the ShareChat dataset (built from publicly shared conversation URLs across five platforms and spanning April 2023 to October 2025) report average turns per conversation of 5.28 for ChatGPT, 4.92 for Gemini, and 4.49 for Claude [5].
Estimated engagement by platform (total turns and approximate user messages):
Assumption: A "turn" represents a single message. Estimated user messages are roughly half of total turns. Engagement is interpreted as average total messages per session.
Note: ShareChat reflects publicly shared conversations and platform samples vary in size, so these figures are directional rather than definitive. The TUEL snapshot is anonymized and based on a small set of published assistants.
TUEL AI is designed as an institutional AI layer, not a chatbot. Tutoring is one interface, but the product is infrastructure that governs how AI interacts with course content, faculty policy, and student data.
That framing aligns with faculty and provost priorities: verifiable, course-grounded responses; auditability and policy controls; and actionable insights that help instructors focus on high-impact mentorship rather than repetitive troubleshooting.
When AI is implemented as infrastructure, not a point tool, it can improve student support without eroding academic integrity or adding operational drag.
Higher education stands at a crossroads. The institutions that thrive will be those that recognize technology as a means to an end, not an end in itself. The goal is not digital transformation for its own sake. It is creating environments where both faculty and students can flourish.
As 93% of higher education leaders plan to expand their AI investments over the next two years [6], the critical question becomes: expand toward what?
The answer should be clear. Invest in technology that addresses the root causes of faculty burnout and student disengagement. Choose solutions built by teams who understand the classroom. Prioritize AI that enhances human connection rather than diminishing it.
The crisis in higher education is real, but it is not unsolvable. With the right approach to technology, one that centers educators and learners rather than administrators and vendors, institutions can deliver on the promise of transformative education.
If you are evaluating AI infrastructure for student success, we can share implementation frameworks and governance artifacts. Request a demo.
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