2026 ASEE Annual Conference & Exposition

Human-Centered Leadership in an AI-Driven World: Practitioner Reflections on Engineering Leadership Education

Presented at Evolution of Engineering Leadership Education: Assessment, Industry Alignment, and AI

Over the past 20 years, engineering leadership (EL) programs have been developed to foster the human-focused skills students need to have a greater impact in their careers. A 2022 Special Issue of the New Directions in Student Leadership (NDSL) summarized the development of EL programs and research. That same year, ChatGPT was released, leading to an explosion in the use of generative and agentic Artificial Intelligence (AI) which has the potential to reshape how engineers work. This begs the question: Does the instruction of EL need to change in light of the AI revolution? And if so, how?

This paper examines these questions through the collected reflections of 13 attendees from the ASEE LEAD Division Off-Site meeting held at Northeastern University in October 2025. All participants at the event were invited to submit a free-form reflection on a set of research questions based on the panels, presentations, and discussions in the workshop. The reflections were then gathered, systematically coded and distilled by the authors into key themes using the definition of EL proposed by Kendall et al. in the 2022 NDSL special issue as a reference point.

Respondents generally felt that Engineering Leadership instruction, training, and modeling will be more important than ever in the age of AI. Human-centered skills such as self-awareness, teamwork, and communication will continue to be foundational; while the environment of engineering practice may change, the key to engineering leadership continues to be fostering alignment among team-members, management and public stakeholders. However, increased emphasis is required on critical thinking, ethical decision-making, and change management. Engineering leaders will require a high degree of AI literacy to support the appropriate deployment of AI tools. Verification and validation and, at times, resistance to contraindicated uses of AI will be key to engineers upholding their professional responsibility. EL educators need to experiment with pedagogy to help students explore the impact of AI on team dynamics, with nuanced discussion on trust and we need to help engineering leaders to develop self-authorship, the ability to navigate challenges based on a strong sense of their own values and beliefs. The role of the ASEE LEAD division in supporting EL educators in this transition may be through continued engagement with industry, research on changing engineering practice, sharing pedagogical innovations that incorporate AI into EL instruction, and workshops on AI literacy.

This paper provides context and motivation for the reflection questions, outlines the findings from the reflections, discusses the implications for engineering leadership education, and offers recommendations for preparing our educators, students, future workforce and prospective leaders.

Authors
  1. Dr. Emily Moore University of Toronto [biography]
  2. Stacie Edington University of Michigan [biography]
  3. Dr. Kenneth W Lamb P.E. California State Polytechnic University, Pomona [biography]
  4. Amin Azad University of Toronto [biography]
  5. Monica Pheifer Massachusetts Institute of Technology
  6. Michael P. Manning Northeastern University
Note

The full paper will be available to logged in and registered conference attendees once the conference starts on June 21, 2026, and to all visitors after the conference ends on June 24, 2026

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