The Power of Practice: How AI is shaping the next era of academic leadership development
Higher education is entering a new phase of leadership development. Artificial intelligence (AI) is not simply another tool to incorporate into existing programs. It is changing the underlying model of how academic leaders learn and develop over time.
For decades, leadership development has been built around structured programs. Workshops, seminars, and cohort experiences have played an important role in helping faculty and administrators to learn and reflect on their practice. These approaches remain valuable. However, they have always faced a fundamental constraint. Leadership is not mastered through knowing. It is developed through doing.
AI introduces a different possibility. It enables us to reimagine leadership development across our institutions by creating virtual safe spaces to practice conversations that matter.
Why traditional academic leadership development struggles to prepare leaders for real decisions
Academic leaders operate in environments defined by complexity, ambiguity, and competing priorities. A department chair navigating faculty conflict, a dean making a resource allocation decision, or a student affairs leader addressing a crisis is not relying on abstract knowledge. They are making real time judgments in moments that are often high stakes and emotionally charged.
Traditional leadership development prepares individuals for these moments indirectly. Leaders learn models, discuss case studies, and reflect on scenarios. Yet the moment itself remains unpracticed until it occurs in reality.
This gap matters. It is in the moment of action where leadership capability is revealed and shaped. It is also where risk is highest.
Three ways AI enables practice-based leadership development in higher education
AI makes it possible to practice those moments confidentially and gain valuable feedback before having to perform them in public spaces.
Through realistic, role specific simulations, leaders can now practice the conversations, decisions, and alignment challenges that define their work. These are not generic scenarios. They can reflect the institutional context, the power dynamics, and the emotional nuance of academic environments.
This shift has three key implications:
First, leadership development becomes continuous rather than episodic. Instead of attending a program once or twice a year, leaders can engage in short, focused practice sessions when they need them. This aligns development with the rhythm of real work.
Second, development becomes personalized. Leaders can practice scenarios that are directly relevant to their role, their challenges, and their growth areas. The experience adapts based on their choices, allowing for exploration of different approaches and outcomes.
Third, feedback becomes immediate and grounded in action. Rather than receiving general guidance, leaders see how their specific language, tone, and decisions shape results.
Together, these three things move leadership development closer to how expertise is actually built.
From knowledge to capability: How AI accelerates the accumulation of that experience
This evolution extends existing approaches. Frameworks, reflection, and coaching remain essential. They provide the language and structure that help leaders make sense of their experience. However, without practice, these elements often remain conceptual.
AI-enabled practice creates the bridge between insight and capability. It allows leaders to test and refine how they show up in critical moments.
This is particularly important in today’s environment where academic leaders are increasingly asked to make decisions with incomplete information, navigate tensions, and build alignment across diverse stakeholders. Solving these challenges requires a combination of knowledge and judgment developed through experience.
Scaling leadership development across the institution: How AI changes the economics of access
One of the most persistent challenges in higher education has been scale. High quality leadership development has often been limited to small cohorts due to the resource intensity of facilitation and coaching.
Institutions can extend development opportunities to a broader set of leaders, including emerging and informal leaders who play critical roles but are often underserved. Practice can be embedded into existing programs, integrated into leadership academies, or offered as a standalone resource available on demand.
This creates the potential for a more distributed model of leadership development. Instead of concentrating capability in a small group, institutions can build leadership capacity across levels and functions.
Over time, this has implications not only for individual effectiveness but also for institutional culture. When more leaders are equipped to navigate difficult conversations, make thoughtful decisions, and build alignment, the quality of collaboration and trust can improve across the system.
Connecting leadership development to real work
The most important change is conceptual, not technological.
Leadership development is no longer something that happens primarily in a classroom or a workshop. It becomes something that is practiced regularly, in short cycles, closely connected to real work.
This shift mirrors how other complex skills are developed. In fields such as medicine or athletics, practice is central. Simulation is a core component of how professionals build capability.
Higher education now has the opportunity to adopt a similar model for academic leadership.
An opportunity for institutions to rethink leadership development
This moment presents a choice. Institutions can continue to rely primarily on traditional approaches, incorporating AI at the margins. Or they can rethink the model more fundamentally, integrating practice as a core element of how leaders are developed.
The latter approach requires building on what has worked before.
By combining research based frameworks, coaching, and AI enabled practice, institutions can create a more complete system of leadership development. One that supports leaders not only in understanding what effective leadership looks like, but in enacting it consistently in the moments that matter.
How the Academic Leadership Group is advancing leadership development
At the Academic Leadership Group, we see this shift as central to the future of leadership in higher education. AI is enhancing human development.
From insight to action: Our work has always focused on helping institutions translate insight into action. We partner with leaders to navigate complexity, align around strategy, and build the organizational capacity needed to move forward.
Extension through AI: AI-enabled practice extends this work in powerful ways. It allows us to bring our research, frameworks, and experience into dynamic environments to environments where leaders can engage directly with the challenges they face.
New systems for new realities: Through the design of new systems, we are helping institutions create spaces where leaders can practice difficult conversations, test decisions, and build confidence in a way that is both rigorous and grounded in the realities of academic life.
Anytime learning to keep up with the pace of change in higher education
The pace of change in higher education is increasing as leaders are operating with less certainty and greater complexity than ever before. In this environment, development cannot remain static.
AI offers a way to move from a model of preparation based on anticipation to one based on active creation. Leaders do not need to wait until they encounter a challenge to begin learning. They can engage it in advance, refine their approach, and enter the moment with greater clarity and confidence.
The shift from teaching to practicing is more than a methodological change. It is a redefinition of how leadership capability is built. It represents one of the most significant opportunities for higher education right now and in the years ahead.
If you’d like to know more, we’d love to talk to you. Please get in touch and we can set up a call.