Bottom line: AI-powered PD systems can generate personalized learning maps Reconsidering icebreakers in expert learning Tips, tools, and facts: Making PD significant in today’s classrooms For
more news on AI and PD, check out eSN’s Educational Leadership hub The PD issue we know too well: A flustered female bursts into the room, late and disoriented. She’s carrying a shawl and a laptop computer she does not know how to utilize. She describes herself as a literacy specialist called Linda, however within minutes she’s asking teachers to “dance for literacy,” assigning “elbow partners,” and insisting the district currently has workbooks no one’s ever seen (awalmartparkinglott, 2025). It’s disorderly. It’s overstated. And it’s painfully familiar.
This viral satire, initially published on Instagram and TikTok, resonates with educators not because it’s unreasonable but because it mirrors the worst of expert development. Numerous instructors have experienced PD sessions that are disordered, detached from practice, or delivered by outsiders who misinterpret the local context.
The implementation gap
Regardless of years of research study on what makes professional advancement efficient– consisting of a focus on content, active learning, and continual assistance (Darling-Hammond et al., 2017; Joseph, 2024)– too many sessions remain generic, compliance-driven, or detached from day-to-day teaching truths. Training training is powerful but pricey (Kraft et al., 2018), and while collective knowing communities reveal pledge, they are challenging to preserve in time.
Typically, the challenge is not the quality of the ideas but the systems needed to bring them forward. Leaders struggle to create appropriate experiences that sustain momentum, and instructors go back to classrooms without clear supports for application or follow-through. For all the time and cash invested in PD, the implementation gap remains large.
The AI chance
Artificial intelligence is not a replacement for thoughtful design or competent assistance, however it can reinforce how we plan, provide, and sustain expert knowing. From tailoring programs and distinguishing materials to scaling training and mapping long-lasting growth, AI uses concrete ways to make PD more responsive and effective (Sahota, 2024; Adams & Middleton, 2024; Tan et al., 2025).
The most promising applications do not try one-size-fits-all fixes, however instead address relentless challenges piece by piece, allowing educators to lead smarter and more tactically.
Reducing clerical load of PD preparation
Before any PD session starts, there is a peaceful mountain of undetectable work: drafting the description, objectives, and program; structure slide decks; developing handouts; creating flyers; aligning products to standards; and handling time, space, and roles. For lots of school leaders, this clerical load takes in hours, leaving little room for designing rich knowing experiences.
AI-powered platforms can generate foundational materials in minutes. A simple timely can produce a standards-aligned agenda, transform text into a slide deck, or produce a branded leaflet. Tools like Gamma and Canva streamline visual style, while bots such as the PD Workshop Coordinator or CK-12’s PD Session Designer tailor agendas to grade levels or educational goals.
By moving these repeated tasks to automation, leaders free more time for content design, strategic positioning, and individual engagement. AI does not simply save time– it restores it, allowing leaders to focus on thoughtful, human-centered expert learning.
Scaling training and continual practice
Training coaching is impactful however costly and time-intensive, limiting gain access to for many instructors. Frequently, PD is delivered without significant follow-up, and continual impact is rarely obvious.
AI can help extend the reach of training by lining up supports with district improvement plans, teacher and trainee data, or personnel self-assessments. Subscription-based tools like Edthena’s AI Coach supply asynchronous, video-based feedback, enabling instructors to upload lesson recordings and receive targeted tips over time (Edthena, 2025). Task Café (Adams & Middleton, 2024) uses generative AI to evaluate class videos and provide prompt, data-driven feedback on educational practices.
AI-driven simulations, virtual classrooms, and annotated student work samples (Annenberg Institute, 2024) offer scalable opportunities for teachers to practice class management, refine feedback methods, and calibrate rubrics. Custom AI-powered chatbots can assist in virtual PLCs, connecting teachers to co-plan and share ideas.
A current research study presented Novobo, an AI “mentee” that instructors train together utilizing gestures and voice; by teaching the AI, instructors externalized and assessed indirect abilities, reinforcing peer cooperation (Jiang et al., 2025). These innovations do not change coaches however guarantee constant development where traditional systems fail.
Supporting long-lasting expert development
Many professional development is episodic, doing not have connection, and failing to line up with instructors’ progressing goals. Sahota (2024) likens AI to a GPS for professional growth, guiding teachers to set long-lasting objectives, identify ability spaces, and access knowing opportunities lined up with aspirations.
AI-powered PD systems can generate individualized learning maps and suggest courses tailored to particular roles or licensure paths (O’Connell & Baule, 2025). Machine learning algorithms can analyze an instructor’s interests, prior coursework, and broader labor market trends to establish adaptive expert knowing plans (Annenberg Institute, 2024).
Yet setting goal is not enough; as Tan et al. (2025) note, numerous efforts stop working due to weak application. AI can close this gap by providing continuous insights, individualized suggestions, and formative information that sustain growth well beyond the initial workshop.
Making virtual PD more flexible and inclusive
Virtual PD often mirrors standard formats, requiring all individuals into the same live sessions regardless of schedule, discovering design, or language gain access to.
Generative AI tools permit leaders to convert live sessions into asynchronous modules that teachers can review anytime. Platforms like Otter.ai can transcribe conferences, generate summaries, and tag crucial takeaways, allowing missing participants to capture up and multilingual staff to access equated transcripts.
AI can adapt materials for different reading levels, offer language translations, and customize pacing to fit individual schedules, guaranteeing PD is extensive yet available.
Improving feedback and assessment
Expert development is frequently evaluated based on participation or complete satisfaction surveys, with little attention to application or trainee results. Lots of well-intentioned initiatives stop working due to inadequate follow-through and weak assistance (Carney & Pizzuto, 2024).
Guskey’s (2000) five levels of examination, from initial reaction to trainee impact, remain an effective structure. AI enhances this technique by automating evaluations, creating surveys, and evaluating responses to surface styles and gaps. In PLCs, AI can support educators with product analysis and trainee work review, providing insights that guide training changes and develop evidence-informed PD systems.
Starting: Practical moves for school leaders
School leaders can integrate AI by starting little: use PD Workshop Coordinator, Gamma, or Canva to simplify agenda style; make sessions more inclusive with Otter.ai; pilot AI coaching tools to extend feedback between sessions; and use Guskey’s structure with AI analysis to strengthen execution.
These actions shift focus from clerical work to instructional impact.
Ethical use, equity, and privacy factors to consider
While AI provides promise, dangers must be attended to. Financial and facilities disparities can widen the digital divide, leaving under-resourced schools not able to access these tools (Center on Reinventing Public Education, 2024).
Issues of information personal privacy and ethical use are crucial: who owns performance data, how it is stored, and how it is utilized for decision-making needs to be clear. Language translation and AI-generated feedback require care, as cultural nuance and professional judgment can not be reproduced by algorithms.
Over-reliance on automation dangers decreasing instructor company and relational elements of growth. Responsible AI integration demands openness, equitable access, and safeguards that safeguard educators and communities.
Conclusion: Smarter PD is within reach
Educators are worthy of expert knowing that appreciates their time, builds on their know-how, and results in lasting educational enhancement. By dealing with style and execution obstacles that have afflicted PD for years, AI provides a path to better, not simply different, expert knowing.
Leaders need not revamp systems overnight; piloting little, strategic AI applications can indicate a shift toward valuing time, relevance, and genuine execution. Smarter, more human-centered PD is within reach if we develop it purposefully and morally.
References
Adams, D., & Middleton, A. (2024, May 7). AI tool shows instructors what they perform in the class– and how to do it better. The 74. https://www.the74million.org/article/opinion-ai-tool-shows-teachers-what-they-do-in-the-classroom-and-how-to-do-it-better
Annenberg Institute. (2024 ). AI in expert knowing: Browsing chances and obstacles for teachers. Brown University. https://annenberg.brown.edu/sites/default/files/AI%20in%20Professional%20Learning.pdf
awalmartparkinglott. (2025, August 5). The PD speaker that makes 4x your salary [Video] Instagram. https://www.instagram.com/reel/DMGrbUsPbnO/
Carney, S., & Pizzuto, D. (2024 ). Carry out with effect: A framework for making your PD stick. Learning Forward Publishing.
Center on Reinventing Public Education. (2024, June 12). AI is pertaining to U.S. class, however who will benefit? https://crpe.org/ai-is-coming-to-u-s-classrooms-but-who-will-benefit/
Darling-Hammond, L., Hyler, M. E., & Gardner, M. (2017 ). Efficient teacher professional development. Learning Policy Institute. https://learningpolicyinstitute.org/sites/default/files/product-files/Effective_Teacher_Professional_Development_REPORT.pdf
Edthena. (2025 ). AI Coach for instructors. https://www.edthena.com/ai-coach-for-teachers/
Guskey, T. R. (2000 ). Evaluating expert development. Corwin Press.
Jiang, J., Huang, K., Martinez-Maldonado, R., Zeng, H., Gong, D., & An, P. (2025, May 29). Novobo: Supporting instructors’ peer knowing of instructional gestures by teaching a mentee AI-agent together [Preprint] arXiv. https://arxiv.org/abs/2505.17557
Joseph, B. (2024, October). It takes a village to create the best expert advancement. Education Week. https://www.edweek.org/leadership/opinion-it-takes-a-village-to-design-the-best-professional-development/2024/10
Kraft, M. A., Blazar, D., & Hogan, D. (2018 ). The impact of teacher training on guideline and accomplishment: A meta-analysis of the causal evidence. Review of Educational Research Study, 88( 4 ), 547– 588. https://doi.org/10.3102/0034654318759268
O’Connell, J., & Baule, S. (2025, January 17). Utilizing generative AI to transform educator growth. eSchool News. https://www.eschoolnews.com/digital-learning/2025/01/17/generative-ai-teacher-professional-development/
Sahota, N. (2024, July 25). AI energizes your profession course & charts your professional development plan. Forbes. https://www.forbes.com/sites/neilsahota/2024/07/25/ai-energizes-your-career-path–charts-your-professional-growth-plan/
Tan, X., Cheng, G., & Ling, M. H. (2025 ). Artificial intelligence in mentor and instructor professional advancement: A systematic evaluation. Computer systems and Education: Expert System, 8, 100355. https://doi.org/10.1016/j.caeai.2024.100355