We are currently standing at a pivotal crossroads in the field of education, as I shared in both Disruptive Thinking and Digital Leadership. On one side, we have the timeless, fundamental principles that make a school function successfully, including leadership, relationships, and sound pedagogy. On the other side, we are witnessing the explosive and rapidly evolving world of artificial intelligence (AI). The question is no longer whether AI will change education because that shift has already occurred. The real question for us as administrators is how we harness this power without losing the human element that defines our profession. We must look at how we use AI to become better pedagogical leaders.
To understand this shift, we need to ground ourselves in the core purpose of our roles. Pedagogical leadership is not about being a manager of a physical building or a processor of paperwork. It is about being a leader of learning. My Framework for Pedagogical Leadership centers on five key domains: developing relationships, providing research and resources, making time for feedback, learning with staff, and analyzing evidence. For years, the biggest barrier to excellence in these areas has been a lack of time. AI changes that math by allowing us to automate the mundane so we can be more present for the profound.
Reclaiming the Human Element
The first pillar of the framework is developing relationships based on trust and mutual respect. Some critics fear that AI is the opposite of human connection, but I argue that it is actually the key to reclaiming the time needed for those connections. When you use AI tools to draft newsletters or summarize meeting notes, you are buying back the minutes required to sit in a classroom and truly support a teacher. Research indicates that when leaders are perceived as supportive and present, teacher self-efficacy and job satisfaction increase significantly. According to Goddard et al. (2015), instructional leadership that fosters a collaborative environment and trust significantly predicts higher levels of collective teacher efficacy. As I noted in my book, digital leadership is about establishing direction, influencing others, and initiating sustainable change through the use of resources and relationships (Sheninger, 2019).
Curating Research and Evidence
The second and fifth pillars involve providing research and resources while analyzing evidence to improve implementation. In the past, being a resource provider meant spending hours scouring journals for strategies. With AI, a pedagogical leader becomes a high-speed curator. You can now use large language models to find research-backed strategies for specific student populations in seconds. One of my favorite tools is Consensus AI. However, the leader must still provide relevance by vetting this output through their professional lens.
AI moves us from being data-rich to being evidence-informed. We can now use technology to look for patterns across massive datasets that would take a human weeks to spot. This allows us to respond to student needs in real time. Research by Liñán and Pérez (2022) highlights how educational data mining and AI can identify students at risk and provide personalized pathways to improve learning outcomes. By using AI to analyze evidence, we ensure that our strategies are actually moving the needle for every learner.
Transforming Feedback and Professional Learning
The third and fourth pillars focus on providing feedback and learning with your team. Feedback must be timely, practical, and specific to be effective. AI-assisted leadership revolutionizes this feedback loop by allowing leaders to organize walkthrough observations into structured formats almost instantaneously. This ensures that the conversation happens while the lesson is still fresh in the teacher's mind. Hattie and Timperley (2007) emphasize that the main purpose of feedback is to reduce discrepancies between current understandings and a goal, and its effectiveness is highly dependent on how it is received and used. AI ensures that facilitation of this feedback is not delayed by administrative friction.
Finally, we must remain the learner-in-chief. Learning with your staff means exploring these new tools together rather than pretending to have all the answers. When we hold Professional Learning Communities (PLC’s), we can use AI to generate prompts that spark deeper pedagogical debates. A study by Chen et al. (2020) suggests that the integration of AI in professional development can help personalize the learning experience for teachers and provide more targeted support for their specific instructional challenges.
AI will not replace leaders, but leaders who use AI will eventually replace leaders who do not. The leaders using AI will have more time for relationships, better access to research, and the ability to provide superior feedback. My framework has not changed because of AI; instead, the technology has made each pillar more attainable. We now have the tools to finally do the work we signed up for which is the work of transforming lives through learning.
For more information on how Aspire Change EDU supports districts, schools, administrators, and educators with AI, click HERE.
Chen, L., Chen, P., & Lin, Z. (2020). Artificial Intelligence in Education: A Review. IEEE Access, 8, 75264-75278.
Goddard, R., Goddard, Y., Kim, E. S., & Miller, R. (2015). A theoretical and empirical analysis of the connections between instructional leadership, teacher collaboration, and collective efficacy scaffolding. Journal of Educational Administration, 53(5), 644-664.
Hattie, J., & Timperley, H. (2007). The Power of Feedback. Review of Educational Research, 77(1), 81-112.
Liñán, L. C., & Pérez, Á. A. J. (2022). Educational Data Mining and Learning Analytics: differences, similarities, and time evolution. International Journal of Educational Technology in Higher Education, 19(1), 1-21.
Sheninger, E. C. (2019). Digital Leadership: Changing Paradigms for Changing Times. Corwin Press.
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