contributed by Dr. Athena Stanley
Artificial intelligence is increasingly present in conversations about education. Some teachers are experimenting with this. Others are cautious. Many are simply not sure where it belongs, or if it even belongs.
Recent Gallup study found that three out of ten teachers use AI weekly, with findings showing improvements in the quality of certain assignments. The study also estimates that AI-supported work could equate to approximately six weeks of saved time over the course of a year.
Meanwhile, a RAND survey found that more than half of students and teachers report that they are already using AI in a school context, although official guidelines and policy are struggling to keep pace.
Amid concerns about plagiarism, bias and the potential impact on students critical thinking skillsthe uncertainty is understandable. Therefore, the question may not be whether AI exists in education, but where it meaningfully fits into curriculum and assessment.
In some classrooms or contexts, integration may be limited in scope and highly intentional, emphasizing critical inquiry rather than routine or active use.
Several fields of study offer starting points for this reflection. Rather than positioning AI as a solution or threat, educators can consider how and whether it aligns with their learning goals, assessment practices, and professional values.
1. Curriculum planning and lesson design
Curriculum planning is one area where AI can intersect with a teacher’s workflow, especially during the early stages of lesson design or brainstorming. Teachers may feel overwhelmed by the task, have too many ideas vying for attention, or look for ways to refresh familiar approaches. AI can help relieve this pressure on the “blank page” by offering general reviews or serving as a brainstorming partner.
AI can also support more specific elements of lesson and unit planning, such as identifying alignment between objectives, grades, and rubrics. It can also help teachers organize ideas for difficult communications, turning lists of notes or journal-style reflections into clear, professional messages.
For example, teachers can revise a unit overview by asking the AI to outline what to keep or cut based on specific criteria, such as eliminating redundancy to fit into a shorter time frame or incorporating a new approach to learning that their school is implementing.
2. Evaluation and Feedback Workflows
Assessment design and feedback are central to teaching practice, and these processes may be areas where AI tools intersect with teacher decision-making. Teachers’ time is valuable, and teaching requires constant attention and flexibility. Routine tasks such as writing instructions, developing feedback starters, planning discussion prompts, or designing rubrics often take up more time than is available during the school day, often spread over evenings and weekends.
AI can help by handling some low-risk, low-stakes production tasks, such as converting notes into a rubric or generating a language draft for feedback. This can reduce drafting time, potentially freeing up space for instructional decision making and student interaction. The usefulness of AI-generated drafts often depends on the specificity and context that teachers provide through their prompts. By setting clear parameters and describing levels of learning, classroom culture, and intended outcomes, teachers can spend minutes refining a draft instead of hours starting from scratch.
3. Differentiation and accessibility
Differentiation remains one of the most complex and essential aspects of teaching. Meeting students where they are while providing an appropriate level of challenge takes time, flexibility and thoughtful planning. AI tools can offer support in generating a variety of examples, scaffolds or alternative explanations that teachers can adapt to meet different learning needs.
Differentiating instruction is time-consuming, and limited planning capacity can hinder even the most skilled teachers. AI can support more sustained and responsive differentiation by generating materials for teachers to review and refine in minutes.
For example, AI can create new-level texts, generate variations on practice questions, or offer multiple explanations of the same concept. It can also create supporting supplements such as lists of potentially challenging vocabulary that students can review before instruction and refer to during lessons. When used judiciously, these aids can contribute to fairer access to education.
4. Digital literacy and assessment
Beyond the learning workflow, AI can provide an opportunity to strengthen students’ digital literacy and assessment skills. Students of all ages already encounter AI in their daily lives, often through the people and digital platforms around them. Teachers who model responsible use of AI could help students develop essential digital literacy skills.
Ethical and thoughtful use of AI becomes a powerful teaching moment when teachers focus on evaluating AI-generated output, drawing on background knowledge, cross-referencing sources, spotting inaccuracies, and asking better questions. This approach helps students build confidence and develop a toolkit to use AI properly without letting it replace their own thinking.
5. Professional growth and future readiness
As AI continues to evolve, education is challenged to balance current learning goals with preparing learners to responsibly navigate emerging technologies. In some contexts, preparing students for college and careers may include helping them understand how to work thoughtfully with AI tools.
As AI becomes more pervasive, teacher knowledge can help maintain relevance in a variety of subject areas, from STEM and language arts to social studies and creative fields. Importantly, the use of AI does not replace teacher expertise; amplifies it.
Responsible use
When AI is incorporated into curriculum or assessment, clear expectations about ownership, integrity, and boundaries are essential. AI can help plan instruction or student work, but educators must continue to uphold standards of academic honesty, transparency, and confidentiality.
Students can be encouraged to reveal when AI tools supported their thinking and explain how these tools were used. Teachers can model responsible practice by avoiding entering personal or identifying information into AI systems and by openly discussing limitations such as bias and inaccuracy. Engaging students in exploring these limitations can strengthen evaluation skills and enhance the role of human judgment. AI is imperfect, and learning to question its results can be one of the most valuable lessons it offers.
Conclusion
Rather than asking whether AI should be used in classrooms, educators can begin by asking where it meaningfully fits into their curriculum, assessment practices, and professional values. Mindful integration requires clarity, boundaries, and continuous reflection. When teachers approach AI not as a shortcut or mandate, but as a consideration within their broader instructional design, they retain what matters most: professional judgment.
In this space of intentionality, AI becomes not a disruption but a solution.
Dr. Athena Stanleyborn in Marquette and proud Yupper, holds a Ph.D. in Curriculum, Instruction and Learning Science from the University at Buffalo (2018) and an M.A. in Education (2013) and a B.A. in Elementary Education (2010) from Northern Michigan University (NMU). Dr. Stanley is the founder and CEO of Athena Global Learning (AGL). A former Assistant Professor of Applied Workplace Leadership at NMU, she is in her 16th year in education and draws from 14 years of international teaching, curriculum development and leadership experience in Ecuador, Turkey and China. She holds a teaching certificate from Michigan and a certificate in school leadership and management from Harvard.
