AI’s Role in Education: Innovation and Responsibility | Magic EdTech

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Rethinking the Role of AI in Education

  • Published on: October 3, 2025
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  • Updated on: October 5, 2025
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  • Reading Time: 3 mins
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Authored By:

Kiara Kolaczyk

Marketing Manager

AI has quickly evolved from something only appearing in sci-fi movies to a daily tool used almost everywhere. It’s reshaping the way we live, learn, and work. However, in education, its role requires nuance. Can AI accelerate and build up learning without eroding the trust of students, faculty, and administrators? Can it ease teacher workloads without replacing the human connections at the heart of learning, while retaining integrity and effectiveness?

These were the questions explored in a recent episode of EdTech Connect: Innovators in Conversation between Acky Kamdar, CEO of Magic EdTech, and Abheek Pandoh, CEO of Knowt. Their discussion offered a grounded perspective on how institutions can responsibly integrate AI into learning systems.

 

AI as a Teacher’s Ally, Not a Replacement

While the promise of AI often sparks fears of displacement, both Acky and Abheek emphasized that its true potential lies in support, not substitution.

“AI should never take away from the trust between teacher and student. It should reinforce it,” noted Abheek.

Today, teachers are overworked with wearing many hats from administrative tasks, to grading papers, to curriculum prep. In these scenarios, AI poses as a solution to step in and handle the repetitive work. This gives educators back time for what is at the core of their role: building relationships, coaching, mentoring, and igniting curiosity.

A teacher guiding a student on a laptop in a classroom, showcasing collaboration and personalized learning while rethinking the role of AI in education.

 

Finding a Balance: Ensuring Innovation Is Paired with Responsibility

AI has created an innovation race for different countries and companies to “reach the finish line first” and to figure out how to “use AI best.” Innovation in AI is moving fast, but education leaders cannot afford to adopt tools without thinking critically about their impact.

Acky pointed out that trust and ethics must sit at the center of AI adoption.

“If students feel manipulated by technology or if data is mishandled, we’ve lost the very foundation of education,” he cautioned.

That means districts and higher education institutions should vet AI solutions not only for their performance, but for their transparency, their accessibility, and alignment with long-term student outcomes. Additionally, the decision makers should decide in advance how they plan to measure effective usage and student outcomes with these AI platforms.

 

Title II and Accessibility… It’s Non-Negotiable

One of the most powerful applications of AI is its ability and potential in making education more inclusive and accessible for all.  Many existing and new software provide real-time translation to adaptive learning for students with disabilities or automatic alt-text generation. AI is now opening doors that traditional tools often leave closed, creating an even playing field for every student.

Abheek shared an example:

“For a student who struggles with text-heavy material, AI can provide audio explanations or interactive visuals instantly. That’s not just convenience. It’s equity.”

At Magic EdTech, accessibility isn’t an add-on. It’s a core principle guiding product design and consulting, which is why Magic EdTech has a dedicated team of over 100 certified accessibility experts helping to transform existing and new content to be Title II compliant.

 

Leading with Curiosity, Not Fear

Both Acky and Abheek underscored that the schools, institutions, and companies thriving in the AI era will be the ones approaching it with curiosity and openness, rather than hesitation or hype. “AI is like electricity. It’s becoming part of the infrastructure,” Acky explained. “The question isn’t whether we use it, but how responsibly and creatively we apply it in education.”

This means experimenting with pilots, engaging faculty in co-design, and ensuring that AI tools genuinely reduce, not increase, complexity for learners and teachers. However, this also means that edtech companies must design these education solutions to be easily integrated into districts’ existing ecosystems and easy to learn and use by those who need to use them. Many times, these “new solutions” mean just more problems and slow adoption. This is where user empathy is more critical than ever.

 

The Road Ahead

AI will not be the solution for every challenge in education. However, it can be a positive transformative force when guided by ethics, accessibility, and trust that are all agreed upon by the creator, the user, and the enforcer. As the conversation between Acky and Abheek highlighted, the most important role AI can play is helping educators reclaim their humanity in teaching.

Be sure to check out the full conversation on our YouTube channel, now available!

 

Written By:

Kiara Kolaczyk

Marketing Manager

Kiara is an accomplished marketing strategist and two-time Fulbright grant recipient, with 5+ years of experience as a marketing consultant for international software startups. She has driven success in Series A funding, AI platform development, and marketing team leadership, while assisting Moldovan businesses in their expansion within Moldova and the EU.

FAQs

Begin with pilots that remove routine load (grading prep, drafting rubrics, summarizing discussions) while keeping teachers in control. Co‑design with faculty, set clear usage rules up front, and expand only when outcomes and classroom fit are evident.

Be explicit about what data is collected, why, and for how long; use explainable AI; keep a human in the loop for consequential calls; and publish an AI‑use policy students and faculty can find and understand.

At the start. Bake in WCAG/Title II requirements during design (captions, alt text, keyboard navigation, translation) so AI features expand access rather than add new barriers.

Start with 1–2 courses, train faculty, set clear data rules, and track concrete outcomes—teacher time saved, dropout/pass rates, and student feedback—then iterate before scaling.

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