Will AI Make Students Better Learners — or Just Faster Workers?

Led by their student host, educators explore ethics, creativity, critical thinking, and the future of learning in an AI-powered world.

Artificial intelligence is no longer a future issue in education. It is already shaping how students study, how teachers prepare lessons, how universities think about access and admissions, and how employers evaluate readiness for the workforce.  

In this episode, host Harshita Multani, a Center for Accounting Transformation intern and Indiana high school business student, leads a thoughtful discussion on AI in education with Markus Ahrens, Ph.D., CPA, CGMA, FMAA, of the American Accounting Association, and David Wood of Brigham Young University. 

What makes this conversation stand out is not just the topic. It is the perspective. 

The future does not belong to students who simply know the answers. It belongs to students who know how to ask better questions, test ideas, build something useful, and explain their thinking. 

Too often, adults talk about students when discussing AI, learning, and the future of work. This episode flips that dynamic. Harshita brings the student point of view to the center of the discussion, asking the questions many students, parents, educators, and employers are already wrestling with: When does AI help students learn? When does it replace thinking? What skills will matter more in an AI-enabled world? And how can schools make sure AI supports learning without widening the gap between students? 

Those questions lead to a conversation that is refreshingly practical, honest, and forward-looking. 

From the start, both guests make clear that AI is already affecting nearly every aspect of education. On the faculty side, it is influencing curriculum development, classroom delivery, and assessment. On the student side, it is changing how learners prepare for class, conduct research, brainstorm ideas, and complete assignments. As Wood puts it, the better question may not be where AI is impactful, but where it is not. 

That framing alone makes the episode compelling. This is not a theoretical debate about whether AI belongs in schools. That question has already been answered by reality. Students are using it. Educators are adapting to it. Employers increasingly expect graduates to know how to work with it. The real question now is how to use it well. 

That is where the conversation gets especially valuable. 

Wood offers one of the episode’s most memorable ideas when he says the real ethical issue is whether students are using AI “to become something more” or simply using it to get out of work and become less. It is a distinction that cuts through much of the noise surrounding AI in schools. Copying and pasting an AI-generated essay may save time, but it does not build judgment, communication skills, or original thought. Using AI to brainstorm, test ideas, challenge assumptions, and improve a draft, on the other hand, can make both the work and the learner stronger. 

Ahrens builds on that point by emphasizing the importance of clear classroom guidelines and intentional practice. Not every course will have the same rules, and students cannot assume AI use is acceptable in every context. He also shares a practical example from his own teaching: requiring students to submit the prompts they used, discuss them in groups, and learn from strong examples. That approach does more than monitor usage. It teaches students how to use AI thoughtfully instead of treating it like a shortcut or a search engine. 

Throughout the episode, Multani grounds the conversation in real student experience. She reflects on how quickly AI went from being barely discussed to becoming a major part of high school life. She shares what she is seeing from teachers, from universities, and from her own peers. She also brings original insight from her own research, including a school survey that found more resistance to classroom AI use than she expected, often because students worried it could weaken creativity. 

That observation leads to another standout theme in the episode: AI as an amplifier. 

Wood describes AI as a tool that amplifies what is already there. If someone is lazy, it can amplify laziness. If someone is creative, curious and hardworking, it can amplify those qualities too. That idea resonates throughout the discussion. AI does not remove the need for human skill; it raises the importance of the right human skills. Critical thinking. Communication. Creativity. Judgment. Adaptability. Initiative. 

In other words, the future does not belong to students who simply know the answers. It belongs to students who know how to ask better questions, test ideas, build something useful, and explain their thinking. 

Ahrens notes that graduates are increasingly expected to use AI in the workplace and may be asked to take on more advanced tasks earlier in their careers. That means technical fluency alone will not be enough. Communication skills, critical thinking, and the ability to evaluate AI output will matter more than ever. 

The episode also pushes listeners to rethink what student preparation should look like. One of the most interesting ideas discussed is the need for students to build portfolios of work showing how they have used AI to create, solve problems, and deliver results. That shift — from grades alone to demonstrated capability — could have major implications for hiring and education alike. 

And perhaps that is what makes this episode so powerful. It is not just about AI. It is about agency. 

 Listen to the full episode.

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