Across the globe, classrooms are being reshaped—not just by technology, but by the absence of the experienced educators who once filled them. Retirements are accelerating. Burnout is pushing others out early. And in the void, AI is moving in—delivering lessons, answering questions, and even grading assignments. What was once a deeply human exchange is increasingly guided by algorithms.
As this shift unfolds, we’re left to ask: Can machines truly carry the torch of those who once inspired generations? Or will something essential be lost when the teachers are gone?
The global teaching profession is in crisis. From the U.S. to the UK, India to South Africa, schools face widespread shortages of experienced teachers. A 2023 report from UNESCO estimates that over 69 million teachers are needed worldwide by 2030 to meet global education goals. In the U.S. alone, more than 300,000 public school teachers left the profession between 2020 and 2022, many due to burnout, low pay, and shifting expectations in post-pandemic education.
At the same time, edtech platforms powered by AI are booming. Companies like Khan Academy, Duolingo, Squirrel AI, and Google Classroom now offer personalized learning pathways, AI tutors, and intelligent feedback tools. AI is no longer just a supplement to education—it’s quickly becoming part of the infrastructure.
So as veteran educators exit and AI systems rise, we must ask: Can AI teach? And perhaps more importantly—can it care?
The Rise of the Machine Mentor
AI in education promises to solve many real and pressing problems:
- Personalized learning: AI can adapt to each student’s pace and style.
- 24/7 availability: Students can access tutoring and support any time.
- Efficiency: Grading, feedback, and curriculum design are increasingly automated.
- Scalability: AI can help address teacher shortages in rural or underserved areas.
For example, Khan Academy’s new GPT-powered “Khanmigo” assistant helps students with math, science, and humanities questions, using conversational AI to simulate tutoring sessions. Squirrel AI in China claims to deliver outcomes comparable to one-on-one human instruction, thanks to its adaptive learning engine.
Educators are also using AI behind the scenes—to identify at-risk students, recommend differentiated lesson plans, or streamline administrative tasks.
This is all incredibly promising. But it also raises critical concerns.
What Happens When Teachers Leave the Room?
Teachers don’t just deliver content—they notice when a student’s eyes glaze over in confusion. They pick up on subtle social cues: a quiet child struggling with anxiety, a teen masking personal turmoil behind a smirk, a class dynamic shifting because of bullying.
AI, for all its sophistication, lacks that emotional radar. It cannot read body language, recognize trauma, or respond to the complexities of growing minds with genuine empathy.
As seasoned teachers retire, they take with them not just pedagogical skill but relational intelligence—the ability to inspire, de-escalate, encourage, and comfort. If AI becomes a stand-in, students may get more answers but fewer role models.
This matters deeply, especially in the formative years. Numerous studies have shown that students who have supportive adult relationships at school are more likely to succeed academically and emotionally. Education is not just about knowledge transfer—it’s about human connection.
The Risk of Data-Driven Dependency
AI systems also bring with them a reliance on data—lots of it. Students are increasingly being tracked through test scores, click rates, behavioral metrics, and engagement scores. While this can help personalize learning, it also reduces education to what can be measured.
What about the immeasurable moments? The breakthrough discussion? The unexpected curiosity? The classroom debate that opens new perspectives? These are not easily captured in an algorithm’s logic.
Moreover, when AI systems recommend learning paths, there’s a risk of reinforcing bias. A student flagged as a “slow learner” early on might be boxed into remedial content, never given the challenge that could spark their growth. Teachers often defy those labels. Will AI?
Reframing AI’s Role: Assistant, Not Replacement
There is a more hopeful and balanced way forward. Rather than replacing educators, AI should be positioned to supportthem:
- AI as a co-teacher: Handling grading and content delivery so teachers can focus on relationship-building.
- AI as a spotlight: Flagging trends or concerns for human teachers to interpret and act on.
- AI as a bridge: Offering tutoring and support where teacher shortages are most acute.
In this model, AI doesn’t replace the teacher—it gives them more time to do the parts of teaching that matter most.
Sal Khan himself emphasizes this approach. “AI can free up teachers to focus on the human connection,” he says. “The best teachers don’t just teach—they mentor, motivate, and model.”
Training the Teachers of Tomorrow
To make this future work, education systems must evolve. That means:
- Training teachers in AI literacy so they can use these tools effectively and ethically.
- Embedding emotional intelligence and ethics in AI design and curriculum decisions.
- Retaining senior educators in mentorship roles—even post-retirement—to guide younger teachers and shape AI implementation with wisdom.
There is enormous potential to design classrooms where the best of technology and humanity work together. But that requires intention, investment, and humility.
Can AI Care?
AI can quiz you. It can track your progress, suggest your next lesson, even write your homework. But it doesn’t smile when you finally “get it.” It doesn’t believe in you before you believe in yourself. It doesn’t change your life with a single kind word.
That’s what teachers do.
As we enter a new era of AI-powered learning, let’s not forget the irreplaceable value of lived experience, emotional insight, and compassionate leadership. When teachers retire, let’s ensure their legacy doesn’t fade. Let’s build systems that honor the human heart of education—even in a digital age.
Next up in the series: Hands Off the Scalpel? – How AI is reshaping medical training as older surgeons exit.
