The Force Multiplier: AI-Assisted Pedagogical Leadership

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.

The Pivot: From Technical Fixes to Systemic Excellence

Every January, the education world is hit with a familiar tsunami. We return from the break, hopefully rested, only to be met by the relentless "New Year, New Initiatives" cycle. It’s like clockwork: a burst of energy to overhaul grading, pivot to new tech, or rewrite behavior plans. But as I’ve shared in Digital Leadership and Disruptive Thinking, we must confront a hard truth: Novelty is not transformation.

If you are chasing the "new" simply because the calendar flipped, you aren’t leading; you’re reacting. In 2026, reactive leadership is a recipe for burnout. To move beyond the buzzwords, we must evolve our leadership DNA.

Situational Awareness: Matching the Velocity of Change

In a previous post, I discussed the Adaptability Quotient (AQ), but in 2026, AQ is no longer about being "flexible". It is about situational awareness. Variables of school leadership now change monthly, if not weekly. Traditional management often misidentifies cultural shifts as technical glitches. In our 2026 landscape, we must transcend the "fix-it" mentality and adopt a Diagnostic Framework for Agile Leadership. Instead of treating student disengagement or staff burnout as bugs to be patched with a new schedule or a digital tool, we must recognize them as signals for deeper, systemic evolution. This requires a radical redistribution of agency.

As DeMatthews, Kotok, and Knight (2021) argue, effective leadership in crisis or high-velocity environments requires a move toward inclusive, distributive models that empower staff to navigate complex, non-linear problems. By decentralizing authority, we allow those closest to the instructional core to respond to shifting variables in real time.

True pedagogical leadership isn't about being the smartest person at the podium; it’s about creating an ecosystem where everyone is empowered to iterate. By decentralizing authority, we allow those closest to the instructional core to respond to shifting variables in real time. This transforms our schools from static, top-heavy institutions into agile, learning-focused organizations capable of pivoting at the speed of change.

The Rise of AI-Assisted Pedagogical Leadership

We have moved past the "ban it" brigade and the "wild west" of AI. The new frontier is AI-assisted pedagogical leadership. It isn't enough for a leader to be "tech-savvy"; you must be pedagogically fluent. This means distinguishing between learning FROM AI (passive consumption) and learning WITH AI (a feedback-driven partnership).

A current study by Zhang and Cheng (2025) found a significant "familiarity gap" where school leaders often feel more comfortable with AI than the teachers they supervise. This gap creates a friction point in implementation. To lead effectively, we must model fluency by using AI to analyze complex datasets, such as attendance or engagement patterns, to uncover insights that human observation alone might miss. This isn't about replacing human judgment; it is about using AI to amplify high-quality first instruction (HQFI).

The Empathy Paradox in Digitally Augmented Environments

As our schools become more high-tech, our leadership must become more high-touch. I call this the empathy paradox. We are more connected than ever, yet loneliness among staff and students is at an all-time high. Digital emotional intelligence is now a core measurable competency.

Current scholarship in neurocognitive leadership suggests that digitally mediated environments often filter out the rich emotional cues (tone, affect, and presence) essential for affective empathy (Fragouli, 2025). Without intentional "digital empathy," leaders risk creating cultures of shallow, surveillance-based mimicry rather than genuine care. Leading in 2026 requires "reading the digital room" to recognize that a terse Sunday night email creates a cortisol spike in staff that no "wellness" initiative can undo. We must prioritize "no-tech walkthroughs," where the device is left in the office and the focus is entirely on human-to-human validation.

Mission-Aligned Narrative Efficacy

Data without a story is just noise. In Digital Leadership, I introduced the "Storyteller-in-Chief" concept, but today we must focus on narrative efficacy. Stakeholders are increasingly skeptical of institutional claims; they demand evidence grounded in mission-aligned personal stories. Braaten and Farnsworth (2025) highlight that the most effective leaders use "narrative-driven data" to align stakeholder perceptions with actual classroom transformation, ensuring that innovation is seen as a human outcome rather than a clinical metric.

Personal storytelling is a strategic bridge. It’s the difference between reporting a 5% growth in literacy scores and telling the story of a student like "Michael," who found his voice through a specific phonics intervention. Evidence-based storytelling humanizes our roles and reaffirms the values that define our schools. In a world of skepticism, your narrative is your compass.

The Agency Shift: From Compliance to Contribution

Ultimately, the goal of disruptive thinking is to move school culture from compliance to contribution. Compliance keeps the machine running, but it doesn't spark innovation. When we shift toward contribution, we move from "doing school" to "empowering learners." Research by Karakus, Toprak, and Chen (2025) demonstrates that when leaders move from top-down mandates toward fostering teacher agency, organizational commitment and instructional quality rise significantly.

Transformation isn't an event; it's a process of layer-by-layer growth. This year, don't just look for something new, look for something better.

Braaten, M., & Farnsworth, S. (2025). School leaders and AI-driven education: A comparative study of readiness, perceptions, and implementation strategies. Emerald Insight: Journal of Educational Administration, 63(1), 45-62.

DeMatthews, D., Kotok, S., & Knight, D. S. (2021). Adaptive Leadership During a Crisis: A Case Study of a Principal’s Response to COVID-19. Journal of Cases in Educational Leadership, 24(1), 16–29.

Fragouli, E. (2025). Digital empathy and AI: Can machines support employee well-being in the workplace? Journal of Media & Management, 7(7), 1-12.

Karakus, M., Toprak, M., & Chen, J. (2025). From compliance to commitment: A quantitative study of educational leadership's influence on teacher motivation and agency. ResearchGate: International Journal of Educational Leadership, 18(2), 114-131.

Zhang, L., & Cheng, Y. (2025). The rise of AI-assisted instructional leadership: An empirical survey of global school leadership trends. Frontiers in Education, 10, Article 1643023.