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Copilot—Your AI Partner in Teaching
Copilot—Your AI Partner in Teaching
Imagine beginning your workday with an assistant that can help you draft a lesson, create three versions of a reading passage, generate formative assessment questions, suggest feedback, summarize a long document, and prepare a family newsletter—all within minutes.
This is the promise of the AI Teaching Copilot. Unlike an AI teacher designed to operate independently, a teaching copilot works alongside the educator. It can reduce repetitive work, generate starting points, and provide ideas or options. AI may support educators by generating ideas, adapting materials, identifying patterns, drafting routine communications, and reducing repetitive work.
However, AI-generated outputs still require human review. Educators must evaluate their accuracy, relevance, fairness, and suitability for particular learners and learning contexts (UNESCO, 2023; U.S. Department of Education, Office of Educational Technology, 2023).
See the Copilot in Action
See the Copilot in Action
Watch this demonstration of Microsoft 365 Copilot’s Teach tools.
As you watch, consider:
Which tasks could AI help you complete more efficiently—and where would your professional judgment still be essential?
Beyond Microsoft Copilot: Specialized AI Tools for Teaching
Beyond Microsoft Copilot: Specialized AI Tools for Teaching
I. The Copilot Cycle
I. The Copilot Cycle
Effective use of an AI teaching copilot begins with the educator, not the technology. The teacher identifies the learning goal, provides relevant context, and decides what kind of support is needed. AI can then generate, adapt, organize, or analyze material, but its output should be treated as a starting point rather than a finished product. The educator must verify its accuracy, revise it for the specific learners, and determine whether it is appropriate for classroom use. After students engage with the material, the teacher observes the results and adjusts instruction accordingly.
Consider: At which stage of the cycle is teacher judgment most important? Can any stage be handed over completely to AI?
II. The "Who Knows What?" Comparison
II. The "Who Knows What?" Comparison
AI systems can quickly recognize patterns, identify common errors, and generate possible explanations or feedback. However, these systems work only with the information they are given. They do not fully understand a student’s learning history, relationships, cultural background, emotional state, or the circumstances affecting their performance. Teachers bring this human and contextual knowledge to every instructional decision.
The educator’s role is therefore not simply to accept the information produced by AI, but to interpret it. A pattern may suggest that a student is struggling, but the teacher must determine why the difficulty exists and how best to respond.
Consider: What important information might be missing when an AI system makes a recommendation about a student?
From Assistance to Human Leadership
From Assistance to Human Leadership
Teaching responsibilities do not always fit neatly into either an “AI task” or a “human task.” Instead, they exist along a continuum. AI may independently produce low-risk first drafts, such as lesson ideas, practice questions, checklists, or routine announcements. More complex tasks—including differentiation, feedback, assessment design, and family communication—may benefit from AI support but require careful teacher review. Responsibilities involving student wellbeing, final grades, sensitive conversations, discipline, and decisions affecting future opportunities must remain human-led.
The level of teacher involvement should increase as the consequences, sensitivity, and need for contextual judgment increase.
Consider: Where would you place each teaching responsibility on this continuum, and what conditions might cause its position to change?
Beyond the Promise of AI:
Beyond the Promise of AI:
Protecting Education's Future
Protecting Education's Future
Artificial intelligence is transforming education by making teaching more efficient, personalized, and accessible. However, Cory Doctorow's concept of enshittification reminds us that digital platforms can change over time. They often begin by serving users well, but as they become essential, commercial priorities may gradually outweigh the interests of educators and learners. Schools and universities can become dependent on a small number of proprietary platforms, making it increasingly difficult to change systems or retain control over educational data and teaching practices. The Educator Renaissance is therefore not only about learning to use AI effectively. It is also about developing the critical capacity to choose technologies wisely, support open standards, protect academic autonomy, and ensure that AI continues to serve education rather than education serving the platform.
What We Can Do
What We Can Do
Artificial intelligence and digital platforms are creating remarkable opportunities to improve teaching, learning, and educational access. They can personalize learning, reduce routine tasks, and help educators design richer learning experiences. However, history reminds us that technologies can change as commercial priorities begin to outweigh the needs of learners and educators. When schools become dependent on a small number of platforms, issues such as reduced transparency, limited choice, data privacy concerns, and loss of educational autonomy may gradually emerge.
The Educator Renaissance is therefore about more than adopting new technologies. It is about ensuring that educators remain thoughtful leaders in shaping how these tools are used. This means thinking critically about who benefits from educational technologies, supporting openness and interoperability, protecting learner data, preserving academic freedom, and always placing education before commercial interests. AI should empower educators not replace their judgmentso that technology continues to serve learning, human development, and the public good.
Delegating Tasks to Copilot
Delegating Tasks to Copilot
Imagine that you have access to Copilot—an assistant that can support lesson planning, create differentiated materials, generate assessment questions, draft feedback, and automate routine tasks.
But Copilot does not take control of the journey. You decide what to delegate, what to review, and where human expertise must remain central.
For each responsibility below, decide whether AI should primarily assist, whether responsibility should be shared, or whether the responsibility should remain primarily educator-led. There may not be one correct answer. Consider your own teaching or learning environment, the learners you work with, and the level of professional judgment each task requires.
What did you notice?
What did you notice?
Some responsibilities may seem well suited to AI support because they are repetitive, time-consuming, or involve generating a first draft. Others require professional judgment, contextual understanding, ethical responsibility, or meaningful human relationships.
However, the boundary is not always clear. Many responsibilities may be most effective when AI and educators work together: AI can generate options, identify patterns, or reduce routine workload, while educators evaluate those outputs and make the decisions that shape learning. This human-centred approach aligns with current guidance emphasizing educator oversight, responsible use, and careful consideration of AI’s ethical and educational implications (UNESCO, 2023).
The question is not simply “What can AI do?” It is “Where does human expertise matter most?”
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