Key Takeaways
- Sal Khan remains optimistic that AI can transform education, but early adoption of Khanmigo showed limited student engagement.
- The initial version of the AI tutor was optional and often ignored, with many students opting to copy‑paste answers from other AI tools.
- Khan’s team learned that proactive nudges and tying AI interaction to course credit significantly boost usage.
- Close partnership with teachers—making AI part of assignments and using data to target struggling learners—has proven essential for impact.
- While AI grading of full essays is not yet deployed, Khan expects rubric‑based, bias‑checked grading within a year.
- Schools should assume AI use on take‑home work, monitor activity, and let technology handle personalized practice while teachers focus on human‑centric instruction.
- Evidence from Newark Public Schools shows that integrating Khan Academy with strong teacher support can triple math growth relative to the state average, even in low‑income districts.
Introduction: Sal Khan’s Rise and AI Vision
Sal Khan, the founder of Khan Academy, has become one of the most visible figures in U.S. education, earning praise from Bill Gates, Michelle Obama, and millions of viewers of his 2011 TED Talk. In May 2023 he declared in another TED Talk that artificial intelligence represented “probably the biggest positive transformation that education has ever seen.” He argued that AI could personalize lessons for every student, essentially giving each child a customized digital tutor, while also acknowledging the risk of cheating. This vision set the stage for Khan’s next experiment: an AI‑powered chatbot called Khanmigo.
The Birth of Khanmigo and Early Hopes
After receiving early access to ChatGPT, Khan developed Khanmigo as a Socratic tutor that would nudge learners forward rather than simply give answers. He promoted the tool in a “60 Minutes” segment with Anderson Cooper, featured it in the book AI for Good by Josh Tyrangiel, and wrote his own manifesto, Brave New Words: How AI Will Revolutionize Education (and Why That’s a Good Thing). The initial design emphasized transparency for teachers and parents, aiming to avoid the “cheating nightmare” that many feared would accompany generative AI in classrooms.
Initial Reception: A “Non‑Event” for Many Students
Despite the fanfare, the first rollout met with tepid response. In an April interview with Chalkbeat, Khan conceded, “for a lot of students,” Khanmigo “was a non‑event.” Many “just don’t use it much,” he said, noting that the tool often sat unused while students turned to other ed‑tech platforms to obtain quick answers. This acknowledgment highlighted a gap between the technology’s potential and actual classroom behavior.
Why the Extra Layer of Support Fell Short
Khan illustrated the problem with a vivid analogy: “Imagine I walk into a classroom and I say, ‘Hey kids, my name is Sal. I think I’m a pretty good tutor. I’m just going to sit in the back of the room here, and if any of you have any questions, I’m happy to help you.’ Well, you can imagine what would happen. Some of the kids maybe would leverage it, but a lot of kids might be too embarrassed. They wouldn’t know how to do it.” He added that “the easiest thing for the student to do is cut and paste the Google search’s AI summary and they’ll have the answer.” The passive, optional nature of the bot failed to overcome students’ reluctance to seek help openly.
Shifting Strategy: Proactive Prompts and Teacher‑Linked Credit
Responding to these observations, Khan’s team piloted a revised version that moves the AI from a passive helper to an active coach. “When you get a question wrong, the AI says, ‘Hey, why don’t you work with me a little bit on this question?’ And [the teacher can then say:] If you can show me that you really understand it, I’ll give you credit for it.” By embedding the AI’s suggestion into the workflow and linking successful interaction to credit, the tool now gives students a clear incentive to engage rather than ignore it.
Teacher Partnership as the Engagement Driver
Khan stresses that technology alone cannot drive usage; teacher involvement is crucial. “We have been partnering with teachers and districts so closely – because we see that when teachers make it part of the assignments, that drives engagement for most students.” In practice, the system highlights which learners are struggling with specific concepts. “Imagine a class of 30 students, all working on their different things. We highlight to teachers that these five kids are really struggling with negative exponents. And we can now tell the teacher, ‘You don’t have to slow down all the other 25 kids, but you take these five kids aside and assign a tutoring session with Khanmigo on negative exponents.’” This targeted approach turns AI into a supplemental tutor that teachers can deploy efficiently.
Addressing AI’s Judgment, Bias, and Grading Limits
Khan acknowledges concerns about AI judgment and bias but argues that the goal is not perfection. “Humans also have a lot of bias. There actually have been studies about how human beings grade students differently based on their perceptions of them… The goal is: Could you have a system that’s more consistent and less biased than the status quo?” Currently, Khan Academy does not assign AI grades to full essays, but it does provide AI‑generated feedback on papers. Khan predicts that within a year the platform will be able to deliver “pretty solid rubrics‑based grading,” which can be benchmarked and tested for bias related to factors like a family’s cultural background.
Practical Guidance for Schools: Monitoring and Purposeful Use
For districts adopting AI, Khan urges a realistic stance: “Assume kids are using AI for any take‑home assignment. Even in the classroom, like when kids are on a computer screen, you need to very carefully monitor what they’re doing – even things as basic as Google are AI now.” He warns against laissez‑faire deployment: “If you leave a laptop on kids’ desks all day, nothing good’s going to happen.” Instead, schools should define clear learning objectives—math practice, reading comprehension, writing—and let technology handle the personalized drill while teachers devote energy to the human aspects of instruction that no algorithm can replicate.
Evidence of Impact: Newark Public Schools Success Story
The effectiveness of this balanced approach is illustrated by Khan Academy’s partnership with Newark Public Schools. “We worked closely with Newark Public Schools. They’ve been deep with Khan Academy for about four years, and Khan Academy is a major part of why Newark is now seeing three times the growth in math compared to the state of New Jersey, despite being one of the state’s poorer districts.” This outcome demonstrates that when AI‑driven practice is woven into a teacher‑led framework, substantial achievement gains are possible, even in under‑resourced settings.
Conclusion: Optimism Tempered by Realism
Sal Khan remains bullish about AI’s long‑term promise in education, but his recent reflections underscore that innovation must be paired with thoughtful implementation. The journey from an optional chatbot to a teacher‑integrated, credit‑linked tutoring system shows that sustained impact hinges on aligning technology with human motivation, classroom culture, and rigorous evidence. As schools navigate the evolving AI landscape, Khan’s advice—monitor usage, focus on meaningful practice, and let teachers lead the human work of teaching—offers a pragmatic roadmap for turning potential into real‑world improvement.
https://www.csmonitor.com/USA/Education/2026/0807/ai-schools-sal-khan-academy