Faculty Are Being Asked to Do the Impossible
Imagine asking a professor to:
- Personalize learning for every student
- Provide meaningful, timely feedback
- Support a wider range of learner needs
- Keep students engaged
- Improve retention and outcomes
- Redesign courses for new technologies
- Use AI thoughtfully and responsibly
- Meet growing expectations for accessibility and flexibility
- Do all of it with the same time, budget, and support
For many faculty members, that is not a hypothetical. It is the reality of teaching in higher education today.
Faculty are doing extraordinary work in increasingly complex environments. They are teaching students with different levels of preparation, balancing in-person and online learning, adapting to new technologies, and responding to growing expectations around student success.
At the same time, institutions are asking them to take on more.
The goals themselves are important. Students should receive timely feedback. Courses should be accessible and engaging. Faculty should have opportunities to explore new approaches to teaching. Institutions should be thinking seriously about how AI will shape learning.
But every new priority requires time, attention, and support.
Too often, that part of the equation is overlooked.
The challenge is not that faculty are unwilling to change or unable to meet students’ needs. It is that even the most committed educators have finite capacity. When new responsibilities are added without removing others or providing additional support, the pressure builds quickly.
That is not a faculty problem. It is a design problem.
Faculty already spend enormous amounts of time preparing courses, teaching, grading, advising students, responding to questions, attending meetings, conducting research, and contributing to their departments and institutions.
Much of this work is invisible.
A thoughtful comment on a student paper may take only a few minutes to read, but far longer to write well. A strong course redesign can take months. Supporting a student who is struggling often requires care, judgment, and time that cannot be reduced to a simple task or workflow.
This is the work that makes teaching meaningful.
It is also the work institutions should be protecting.
As student needs become more varied and expectations for support continue to grow, the answer cannot simply be to ask faculty to stretch further.
The better question is: How can institutions create more capacity for faculty?
Creating capacity does not mean lowering expectations or reducing the role of educators. It means giving faculty the time, tools, and support to focus on the work where their expertise matters most.
That includes mentoring students, designing thoughtful learning experiences, leading discussion, providing meaningful feedback, and helping learners connect ideas in ways that go beyond the course material.
Technology can play a role, but only when it supports that work rather than adding another layer of complexity.
The most useful technologies are not necessarily the ones with the most features or the fastest rollout. They are the ones that fit into teaching in a practical way, reduce unnecessary work, and make it easier for faculty to support students at scale.
That should also shape how institutions think about AI.
The goal should not be to automate teaching or replace the judgment of educators. It should be to determine where AI can responsibly reduce repetitive work, extend student support, and create more space for meaningful human interaction.
Success, then, is not measured by how many tools are adopted or how many faculty members complete a training.
It is measured by whether educators feel better supported, whether students receive stronger learning experiences, and whether new initiatives make teaching more sustainable rather than more demanding.
Higher education has no shortage of commitment, expertise, or ambition.
The opportunity now is to build the capacity that allows all three to translate into the kind of teaching and student support institutions are working so hard to deliver.