Early Childhood Educator Judgment in the Age of Artificial Intelligence (AI)
As an educator and lifelong learner, I see education as one of society’s interconnected institutions, each depending on and strengthening the others. When I read about developments in other fields, I naturally bring them back to the question: “How might this influence early childhood education and learning?” Today, my mind is on Artificial Intelligence (AI) and teacher agency.
The skill I would encourage early childhood educators to develop for the future is professional judgment. Artificial intelligence may help us prepare materials, organize information, and explore possibilities. Deciding what a particular child needs still requires an educator who can observe carefully, interpret evidence, and respond responsibly. Our preparation for AI should strengthen that capacity.
Technology entrepreneur and investor Mark Cuban’s predictions about AI invite us to examine which skills early childhood educators and leaders should develop for the future. Reading career advice based on his predictions about programming, accounting, and routine work, I understand the appeal of a clear list of skills to pursue or avoid. People want security. They want their investment in learning to matter. Yet a list of supposedly declining skills can conceal how work actually happens.
Cuban was warning about the automation of programming as early as 2017 (Primack, 2017). His predictions invite inquiry; they do not establish that entire professions have become unnecessary. The International Labour Organization’s 2025 analysis distinguishes potential exposure to AI from actual job losses and identifies job transformation as the more likely overall outcome.
My interpretation for early childhood education is straightforward - examine which tasks technology can assist, then identify the knowledge and relationships needed to make sound decisions. That distinction changes what we teach children, how we prepare educators, and what leaders should protect.
The knowledge beneath the task
Consider a preschool teacher preparing a learning experience about bridges. An AI tool might suggest materials, vocabulary, and questions. A useful plan, however, depends on information the teacher must supply and evaluate. Which children are already experimenting with balance? Who needs an accessible way to handle materials? What construction experiences have families shared?
The teacher’s expertise determines whether a suggestion becomes meaningful learning. Without knowledge of development, the teacher may accept an activity that looks impressive but demands skills children have not yet developed. Without knowledge of individual children, the plan may overlook the child whose ideas emerge through gestures rather than spoken explanations.
Children also need opportunities to practice the thinking we want adults to use. During bridge play, a child may predict that adding another block will make the structure stronger. When it collapses, the teacher can ask, “What changed?” and “What could we try?” Invite children to compare their predictions with what happened. Leave room for an unexpected explanation. A child’s theory gives the educator something to investigate together, even when the theory is mistaken.
NAEYC’s framework for developmentally appropriate practice supports intentional decision making through attention to common patterns of development, individual children, and their contexts (National Association for the Education of Young Children, n.d.). AI makes this knowledge useful whenever educators evaluate generated suggestions.
The same reasoning challenges blanket advice to avoid repeatable work. In early childhood, we know repetition can serve a purpose. A familiar greeting, another reading of a favorite book, or a predictable transition can offer opportunities for connection and learning. Leaders should examine what a repeated task accomplishes before trying to eliminate it.
I would invest in understanding child development and learning to explain instructional decisions. These skills give educators criteria for evaluating a tool’s output. Producing a lesson plan and judging its suitability are different responsibilities.
For beginning educators, practice with observation and planning remains valuable even when software can produce a draft. Completing these tasks helps them learn what to notice and how decisions connect. Mentors can gradually introduce AI while asking novices to explain, check, and revise its suggestions with guidance from an experienced colleague.
Teacher agency makes judgment possible
Knowledge alone cannot shape practice when teachers have little opportunity to act on it. Teacher agency involves the capacity and opportunity to make informed decisions that respond to children and families. Wright and Abo-Zena’s discussion of agency in NAEYC’s summer 2026 Young Children connects educators’ professional judgment with intentional, equitable teaching. (Wright & Abo-Zena, 2026).
Imagine children becoming absorbed in building a bridge while the schedule calls for a worksheet. A teacher sees opportunities to explore measurement and cooperation. Exercising agency means being able to adapt the experience, explain how it serves learning goals, and assess what children understand.
This carries responsibility. Educators need sound knowledge, ethical commitments, and openness to feedback. Agency should operate within clear expectations for safety, inclusion, and learning. A leader can ask, “What did you notice, and how did it inform your decision?” That conversation makes professional reasoning visible.
An AI system could undermine agency if its suggestions become mandatory instructions. It could also support agency by offering alternatives teachers can evaluate. The difference depends on who retains authority and how the organization treats disagreement.
Inquiry gives curiosity a direction
Curiosity becomes professionally useful when we connect questions to evidence and action. Suppose several children leave group time. “How do I make them sit?” assumes that sitting is the problem to solve. “What is making participation difficult?” opens possibilities the first question excludes.
The teacher might examine the length of the gathering, opportunities for movement, language demands, and the purpose of the activity. Children’s behavior provides information. Families and colleagues may add perspectives the teacher has missed.
Try this inquiry process with one recurring classroom concern:
1. Describe what happened using observable details. Replace “They were disruptive” with a description of what children did.
2. Generate more than one explanation. Treat each explanation as something to investigate.
3. Gather relevant information. Look across occasions and invite children’s or families’ perspectives where appropriate.
4. Make one purposeful adjustment. Identify the learning goal and what improvement would look like.
5. Review what changed. Keep, revise, or discontinue the adjustment based on what you observe.
For example, a teacher might shorten a gathering and offer children ways to participate through movement. The review should consider whether children engage with the learning, rather than simply whether the room becomes quieter.
AI can help generate alternative explanations. Educators must examine those explanations against their observations. A convincing answer remains a possibility until evidence supports it.
Leaders must protect time to think
Leaders influence whether inquiry becomes a habit or another demand teachers struggle to meet. Asking educators to be adaptable while denying them planning time creates a practical contradiction. Professional learning requires time to examine decisions and try improvements.
Start with a paid, twenty-minute conversation each week about one classroom question. Ask a teacher to bring a brief observation and a decision they are considering. A colleague can offer another interpretation. The director can identify resources or clarify where adaptation is permitted.
Leaders also need to examine how they recognize competence. A polished display or completed form reveals only part of a teacher’s work. Ask teachers to explain an adjustment, its purpose, and what they learned. This creates an opportunity to recognize expertise that a checklist may miss.
Access matters. Include assistants, family child care educators, and educators whose knowledge is expressed through languages or experiences different from those leadership usually privileges. Offer ways to contribute through conversation, demonstration, or brief notes.
When technology saves time, decide deliberately how that time will be used. Returning some of it to planning and relationships can strengthen teaching. Filling every saved minute with additional assignments can erase the benefit. Teachers should help make that decision.
Use AI to strengthen professional learning
Begin with an adult planning task that carries limited consequences. Ask an AI tool to suggest discussion questions for a staff meeting or generate several approaches to a fictional classroom dilemma. Review the output together and identify what is useful, what is missing, and what requires checking.
A practical prompt might be - “Suggest three ways to support participation in a preschool group activity. Explain the assumptions behind each suggestion and what a teacher should observe before choosing.” This invites comparison and makes the proposed reasoning easier to examine.
Keep identifiable child and family information out of unapproved tools. Use fictional examples for practice. Check factual claims against reliable sources, examine suggestions for bias, and retain educator responsibility for assessment and communication with families.
The professional learning happens during evaluation. When teachers disagree with an AI suggestion, invite them to explain why. They may identify an unrealistic assumption, an accessibility barrier, or a mismatch with children’s interests. That discussion can reveal what the team knows and where further learning would help.
Choose a tool because it serves a defined need. Evaluate the time spent reviewing its output as well as the time it saves.
Make professional growth visible
Career advice often implies that learning the right skill will automatically produce better pay. Early childhood educators know compensation also depends on funding and employer decisions. Stronger skills deserve recognition, but educators should not carry the entire responsibility for overcoming low wages.
Build a small portfolio of professional reasoning. Include an observation, the question it raised, the adjustment you made, and evidence of what happened. Remove identifying details. These examples can support conversations about mentoring responsibilities, advancement, or compensation without adding a large documentation burden.
For leaders, connect new responsibilities to preparation and pay. If a teacher mentors colleagues or leads inquiry meetings, define the role and allocate time. Treat that contribution as professional work.
Whether you are beginning your career or reconsidering your next chapter, choose one question worth investigating this week. Discuss it with someone who can help you see another possibility. Make a thoughtful adjustment and examine the result. That practice gives curiosity a purpose and keeps educator judgment active as tools change.
References
International Labour Organization. (2025, May 20). How might generative AI impact different occupations? https://www.ilo.org/resource/article/how-might-generative-ai-impact-different-occupations International Labour Organization
National Association for the Education of Young Children. (2008). DAP: Defining developmentally appropriate practice. https://www.naeyc.org/resources/position-statements/dap/definition NAEYC
Primack, D. (2017, February 2). Mark Cuban: Automation will eat the world. Axios. https://www.axios.com/2017/12/15/mark-cuban-automation-will-eat-the-world-1513300267 axios.com
Wright, B. L., & Abo-Zena, M. M. (2026). Did you lose your teacher voice? Reclaiming educator agency, voice, and choice through a critical lens. Young Children, 81(2). https://www.naeyc.org/resources/pubs/yc/summer2026/reclaiming-educator-agency-voice-choice
About the Author
Victoria Long-Coleman, Ph.D., MBA is the Founder and Principal of Early Childhood Innovations. An early childhood educator, leadership, coach, author, speaker, she focuses on strengthening educators, developing leaders, and translating research into practical approaches that improve early childhood systems.
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