Key Takeaways
- Artificial intelligence (AI) will be a defining leadership test for police executives in 2026
- Police leaders must adopt a deliberate, values-driven strategy for AI adoption, focusing on innovation, accountability, and people-centered leadership
- Four integrated pillars for AI leadership in policing are: acknowledging skepticism and leading through it, co-designing AI with vendors and stakeholders, governing AI with accountability and oversight, and investing in people and training
- Effective AI leadership will be measured by responsible governance, sustainability, preparation of people, and legitimate reception by the community
Introduction to AI in Policing
As policing enters 2026, artificial intelligence will no longer be an emerging issue, but a defining leadership test. According to the author, "AI demands a deliberate, values-driven strategy built upon innovation, accountability and people-centered leadership rather than ad hoc adoption." The question for police executives is no longer whether AI will shape the profession, but whether it will be shaped by law enforcement or for law enforcement. This requires a thoughtful and intentional approach to AI adoption, rather than simply following the lead of vendors or other external factors.
The Summons to Leadership
The first pillar of AI leadership in policing is acknowledging skepticism and leading through it. As the author notes, "Public concern and internal anxiety around AI are real and justified." Leaders must resist both extremes: the "wait-and-see" approach that cedes influence to others, or conversely, the rush to deploy untested tools. Instead, they should focus on transparent communication, ethical framing, and early engagement with officers and communities to build trust before AI technology is deployed. If police leaders fail to answer the summons to leadership, AI adoption will be shaped by vendors, courts, and public pressure, rather than by professional judgment and democratic policing values.
Co-Designing AI
The second pillar is co-designing AI with vendors and stakeholders. As the author explains, "AI systems are most effective and defensible when police leaders, practitioners, technologists, legal advisors, and community stakeholders help shape them from the outset." Agencies that participate with vendors early, through live pilots and proof of concepts (POCs), can help define standards, safeguards, and use cases. Without co-design, agencies risk inheriting opaque systems designed by others, that misalign with operational realities and community expectations, undermining both effectiveness and legitimacy. By working together with stakeholders, police leaders can ensure that AI systems are designed with the needs and values of the community in mind.
Governing the Machine
The third pillar is governing AI with accountability and oversight. As the author notes, "AI governance cannot be delegated to vendors or buried in IT units." Chiefs must lead formal and internal oversight structures, insist on human-in-the-loop review, kill switches, and require continuous validation through red-teaming, analytic audit cycles and bias testing. This will help ensure that AI tools are used responsibly and with integrity, and that their outputs can withstand legal scrutiny, operational realities, and public oversight. Without strong governance, AI tools can drift beyond policy and oversight, exposing agencies to legal risk, ethical failure, and irreversible loss of public trust.
The Human Element
The fourth pillar is investing in people and training. As the author explains, "Every technological shift creates anxiety about time, workload and sustainability." Leaders must plan for training beyond initial vendor onboarding, embed AI into routine workflows, and conduct AI readiness audits that assess adoption culture, policy, training capacity, and long-term funding. When training and readiness are neglected, AI becomes either unused or misused, amplifying officer frustration, operational inefficiency, and community skepticism. By prioritizing people and training, police leaders can ensure that their officers are equipped to use AI effectively and responsibly.
Conclusion
In conclusion, effective AI leadership in policing will not be measured by how advanced an agency’s technology is, but by how responsibly it is governed, whether it can be sustained, how well its people are prepared, and how legitimately it is received by the community it serves. As the author notes, "The future of AI in policing belongs to leaders willing to answer the summons, moving from skepticism to stewardship, and taking responsibility for shaping what comes next." By adopting a deliberate, values-driven strategy and focusing on the four integrated pillars of AI leadership, police executives can ensure that AI is used to enhance public safety and trust, rather than undermine it.
https://www.police1.com/leadership-institute/artificial-intelligence-and-police-leadership-in-2026-from-skepticism-to-stewardship