Leading Intelligently on AI
Leading Intelligently on AI
Your first email of the day:
“Chief, the watch commander saw one of our graveyard officers talking to you on a video call, except it wasn’t you. The officer was having a conversation with an avatar for an “AI Agent” that helps problem-solve using department policies and procedures uploaded to an on-line platform. Apparently, the team set up personal accounts on a website and has been using the ‘Hey, Chief’ AI agent chatbot during their shift. We don’t have a policy on this. How would you like to proceed?”
This fictional scenario may sound futuristic, but it’s increasingly plausible and currently possible.
Some departments are taking a cautious “wait and see” approach to artificial intelligence, while others are experimenting with so-called “walled garden” AI platforms that maintain CJIS compliance while generating content, analyzing evidentiary audio and text, or summarizing officer-worn camera footage into usable narratives. Adoption decisions are often shaped by guidance from police-centric resources like the IACP and Lexipol. These sources rightly emphasize the importance of addressing data quality, privacy, bias, and legal considerations when deploying AI in operational contexts.
However, AI is evolving too rapidly for well-intended guidance to keep pace, and the use of AI transcends police-related operations. For example, the emergence of agentic AI. While generative AI creates content based on input, agentic AI acts independently toward user-defined goals, sometimes with minimal human-in-the-loop interaction or oversight. Agentic AI could be used for real-time decision support, workflow automation, task prioritization, and autonomous staffing optimization. It can also serve as a personal assistant in both professional and personal settings, supporting everything from scheduling to wellness and performance monitoring.
Many AI tools aren’t limited to enterprise solutions. They are accessible to individual online users through AI as a Service (AIaaS), often free or inexpensively, and can be rapidly integrated into personal workflows, much like smartphones and the internet did a generation ago. The democratization of AI creates both opportunity and risk. If police executives don’t lead on this topic, others will quietly and informally.
This is not a question of whether people will use AI, but rather how, when, and under what guardrails.
Although AI use cases in policing typically focus on operational or enforcement-related tasks, police leaders should also recognize its potential to transform organizational management, from internal workflows to administrative decision-making. To think strategically, police leaders must consider how AI is transforming leadership, organizational culture, and workforce strategy across sectors. OpenAI highlights how early adopters focus their efforts on workplace challenges of repetitive low-value tasks, skill bottlenecks, and navigating ambiguity.
In corporate environments, AI is driving data-informed decision-making and reshaping how leaders lead. The public sector will not be immune. AI will change the skills required of employees, shift how tasks are delegated, and redefine expectations around roles, contributions, and value at all levels of the agency and across city departments. Managing the opportunities and challenges of AI adoption will require thoughtful implementation, and could have profound implications with trust between agency leadership and the rank-and-file.
A Strategy to Lead Intelligently on AI
To lead intelligently on AI, consider adopting a phased integration strategy. OpenAI suggests kickstarting this process by understanding where AI adds value, teaching employees fundamental case uses, and prioritizing what to scale.
The following framework, adapted from Mitchell Gurevich, PhD’s course Harnessing AI to Transform Organizations, offers a strategy for a phased approach to AI adoption and capability-building to ensure responsible, effective, and scalable integration of AI technologies in the workforce.
- AI Literacy for All Employees — Build a foundational understanding of AI principles across the organization, from line-level staff to executive leadership.
- Safe and Appropriate Use in Daily Workflows — Train personnel to use AI tools responsibly and securely with human oversight. Ensure use aligns with department and city values, and identify the problems AI is intended to solve and how AI supports organizational goals.
- Innovation in Controlled Environments — Encourage experimentation in sandboxed settings. Create safe spaces for testing AI capabilities before widespread deployment. Be strategic about how and when to adopt AI applications.
- Capacity for Governance and Compliance — Develop technical and policy expertise in-house or through partnerships to maintain human oversight, ensure accuracy and accountability, and align with responsible AI frameworks to prevent harm and build trust.
- Citywide Collaboration — Don’t keep your agency’s AI efforts isolated. Communicate with the city manager and collaborate to develop a coordinated approach to technology governance, data ethics, and deliberate implementation across city departments.
AI is more than just a tool to write speeches, generate or summarize emails, or create images for presentations. It is impacting how executives lead, how decisions are made, and how organizations adapt to change.
As Microsoft CEO Satya Nadella said at the 2024 World Economic Forum:
“The biggest lesson learned is we have to take the unintended consequences of any new technology along with all the benefits, and think about them simultaneously—as opposed to waiting for the unintended consequences to show up and then address them.”
Police executives should consider this tech executive’s counsel and adopt a proactive AI mindset. A mission-oriented AI strategy, rooted in ethical foresight and operational relevance, will position you to lead intelligently on AI with confidence, likely with the help of AI itself.
This article was written by the author and edited by generative AI using the prompt, “Review and edit for a reading audience of police executives,” in ChatGPT 4o.
References:
Gurick, Mitchell. Harnessing AI to Transform Organizations. BUS 75, Stanford Continuing Studies, AI Workforce Education & Learning Strategy, 12–13 July 2025.
OpenAI. Identifying and Scaling AI Use Cases. OpenAI, n.d. https://cdn.openai.com/business-guides-and-resources/identifying-and-scaling-ai-use-cases.pdf
About the Author:
Max Bosel was Mountain View, California’s Police Chief from August, 2014 until his service retirement in December, 2020. He returned as Interim Chief in 2023. He also served as Interim City Manager.
A former board member of the California Police Chiefs Association, Max now serves CPCA on the Finance Committee, Peer Support Team, and as the Executive Leadership Certificate Program facilitator.
Max was selected as a Fellow at Stanford University’s Distinguished Careers Institute, where he completed graduate-level coursework and continues to participate in intergenerational mentoring.