As policing approaches 2026, artificial intelligence (AI) is set to become a defining challenge for law enforcement leaders. According to a recent excerpt from “26 on 2026: A police leadership playbook,” the conversation has shifted from whether AI will influence policing to how it will be integrated, whether shaped by law enforcement or for law enforcement. AI adoption necessitates a strategy built on innovation, accountability, and a people-centered approach, rather than piecemeal implementation.
The playbook outlines four essential pillars that police leaders must consider. First, leaders must confront the skepticism surrounding AI and address it head-on. Public concerns and internal worries about the technology’s implications are valid. Authorities are urged to avoid both the “wait-and-see” mentality, which risks ceding control to external forces, and the hasty deployment of untested tools. Transparent communication and ethical engagement with officers and the community are crucial to building the necessary trust before any AI systems are rolled out.
Failure to acknowledge this leadership responsibility could result in AI adoption being directed by vendors and public pressure rather than informed by professional judgment. The playbook emphasizes that the governance of AI should not be left to technology providers or relegated to IT departments. Police chiefs must establish formal oversight structures, incorporating regular reviews and accountability mechanisms, such as human-in-the-loop assessments and continuous validation processes.
The second pillar focuses on co-designing AI systems that meet actual operational needs. This means moving beyond vendor promises and opaque designs to involve a range of stakeholders—police leaders, practitioners, technologists, and community representatives—right from the outset. Agencies that engage with vendors during live pilots can define standards and safeguards, ensuring that the technology aligns with both operational realities and community expectations.
If police departments neglect this collaborative approach, they risk adopting systems that do not fit their specific contexts or community requirements, ultimately undermining the effectiveness and legitimacy of AI tools. Governance and accountability must be central to any AI strategy. Police leaders need to take ownership and establish robust oversight mechanisms, including requirements for regular audits and bias testing to ensure that AI outputs can withstand legal scrutiny and public oversight.
The third pillar emphasizes the importance of human elements, particularly in training and leading through the transition to algorithmic policing. As technological advancements can cause anxiety among officers regarding workload and sustainability, police leaders are advised to plan for ongoing training that extends beyond initial onboarding by vendors. Conducting readiness audits can help assess how well departments are prepared for AI integration in terms of culture, policy, and training capacity.
Without a focus on training, AI could become either underutilized or misused, leading to frustration among officers and skepticism from the community. In this regard, leaders must be proactive in embedding AI into everyday workflows to navigate the challenges of the transition smoothly.
In conclusion, effective AI leadership in policing by 2026 will be assessed not by technological sophistication but by the degree of responsibility in governance, the sustainability of AI initiatives, the readiness of personnel, and the legitimacy with which the community receives these advancements. The future of AI in policing will depend on leaders willing to embrace their responsibilities, shifting from skepticism to stewardship as they shape the landscape of law enforcement technology.
This is an excerpt from “26 on 2026: A police leadership playbook.” Download the complete playbook here.
See also
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