Michael Zidar_

I help organizations turn AI strategy into adoption.

Director of Corporate AI Solutions at Axon, with a background spanning public safety technology, software development, crime analysis, and applied research.

Michael Zidar leads corporate AI initiatives at Axon Enterprise, helping teams adopt generative AI and applied AI through enablement, upskilling, governance, internal tooling, and practical implementation support. His background spans policing technology, crime analysis, data platforms, software development, academia, and research on police adoption of information technology.

Director, Corporate AI Solutions at Axon Enterprise, leading company-wide AI enablement — upskilling teams, accelerating adoption, and building the practices that make AI real across the organization.

01

Enterprise AI adoption

Turning strategy into repeatable practices through workforce enablement, upskilling, and implementation support.

02

Governance that enables

Building responsible guardrails that help teams move with clarity instead of adding ceremonial paperwork.

03

Practical AI tooling

Connecting models, developer workflows, and internal tools to real organizational problems.

04

Public safety technology

Applying operational experience, research, and data systems expertise to technology adoption in public safety.

Director, Corporate AI Solutions

2026 – Present

Sr. Manager, Corporate AI Solutions

2024 – 2026

Adjunct Assistant Professor

2025 – Present

Assistant Professor

2024

Sr. Manager, Public Safety Innovation Technology

2022 – 2024

Adjunct Faculty

2022

Crime Analyst and Technical Lead

2018 – 2022

Adjunct Faculty

2018 – 2019

Crime Analyst

2015 – 2022

Ph.D., Information Technology

Dissertation: Policing in the AI Era: A Mixed-Methods Analysis of Police Adoption of Information Technology

M.S., Criminal Justice

Specialization in Data-Driven Public Safety and Technology Adoption

B.S., Criminal Justice

Cum Laude, Minor in Political Science

Zidar Analytics LLC

AI and technology consulting — helping organizations build AI strategies, develop internal tooling, and stand up enablement programs. Clients include the University of Colorado at Boulder, the National Police Institute, and other data-driven organizations.

Available for select advisory, research, speaking, and implementation engagements.

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Zidar, M. (2023). Policing in the AI Era: A Mixed-Methods Analysis of Police Adoption of Information Technology. Doctoral dissertation, University of Cincinnati.

Feldmeyer, B., Cullen, F. T., Sun, D., Kulig, T. C., Chouhy, C., & Zidar, M. (2022). The community determinants of death: comparing the macro-level predictors of overdose, homicide, and suicide deaths, 2000 to 2015. Socius, 8.

Said, H., Zidar, M., Varlioglu, S., & Itodo, C. (2021). A Framework for the Discipline of Information Technology. Proceedings of the 22nd Annual Conference on Information Technology Education.

Ozer, M., Zidar, M., Deryol, R., Varlioglu, S., Eldivan, I. S., & Akbas, H. (2020). Creating A Real-Time Geocoding System: Implications of Open Source for Public Safety. 2020 International Conference on Computational Science and Computational Intelligence (CSCI).

Zidar, M. S., Herold, T. D., & Eck, J. E. (2019). Superusers of Small-Town Police Resources. The Police Chief, 86(10).

White, D. R., Hepworth, D. P., & Zidar, M. S. (2018). Texting and Driving: Is It Just Moral Panic?. Deviant Behavior, 39(11).

Zidar, M. S., Shafer, J. G., & Eck, J. E. (2017). Reframing an Obvious Police Problem: Discovery, Analysis, and Response to a Manufactured Problem in a Small City. Policing: A Journal of Policy and Practice.

White, D. R, Kyle, M. J., Galli, P., & Zidar, M. S. (2017). Youth Attitudes Regarding Police Effectiveness and Trust in One Midsize City. The Police Chief, 84(10).