The Educator’s Role in an AI-Powered Learning Future

Artificial intelligence is no longer a future concept in education, it's actively shaping how we design, deliver, and experience learning today. From personalised feedback to AI-driven tutoring, the possibilities are expanding rapidly. But with those opportunities come challenges: data ethics, learner trust, and the need for thoughtful integration into human-centred design.

In a recent session at the Digital Learning Institute, two leading voices, Larry Hurtubise and Melinda McClimans of The Ohio State University shared practical insights and case studies on how AI is being applied meaningfully in educational settings.

Here are four key takeaways on how AI is transforming the landscape of teaching and learning:

AI is enhancing the learner experience by enabling real-time adaptation of content and pacing. From intelligent tutoring systems to automated feedback tools, educators are now better equipped to meet students where they are.

Larry Hurtubise, a curriculum and instruction expert, discussed how generative AI can tailor feedback to individual learners reducing generic responses and increasing relevance. These tools aren’t just more efficient; they help build confidence by offering support precisely when learners need it.

Melinda McClimans shared compelling examples of AI-powered tutoring systems that simulate mentoring, support language learning, and provide structured feedback in liberal arts education. While still emerging, these applications show promise for improving learner retention and autonomy.

At Ohio State, Larry and Melinda are using AI tools not as replacements for educators, but as enhancers allowing instructors to focus more on critical thinking, reflection, and interpersonal learning, while AI handles more routine scaffolding.

No discussion of AI in education is complete without addressing its limitations. Both speakers raised concerns around algorithmic bias, data privacy, and the tendency to over-rely on AI-generated outputs without pedagogical oversight.

Educators must ask:

• Is this tool promoting equity or reinforcing bias?

• How transparent is the system about how feedback is generated?

• Are we designing with the learner in mind, or defaulting to what the tech enables?

These questions underline the importance of educator agency in AI integration. It’s not about using AI because we can, but because it meaningfully improves the learning experience.

Looking ahead, AI will continue to play a supporting role in instructional design but it won’t replace the educator. Instead, educators will become curators of experiences and mentors in thinking, using AI to scaffold, differentiate, and personalize learning at scale.

Larry’s research on professional identity formation in clinician educators, paired with Melinda’s work in interdisciplinary program design, makes one thing clear: the future of education depends on cross-functional collaboration between tech, pedagogy, and institutional strategy.

AI in education is not a plug-and-play solution it requires intentional design, critical evaluation, and a learner-first mindset. As these technologies evolve, it’s up to digital learning professionals to guide their application with empathy, creativity, and accountability.

Want to know more? You can watch the full session here.