Recruiting, promoting and evaluating officers has long challenged police leaders. At IACP 2025, chiefs and researchers shared how artificial intelligence is helping them do it faster, fairer and with clearer feedback.
Panelists
- Michael Anderson – Founder, CivicSolutions
- Lisa Broderick – Founder, Police2Peace
- Chief Jack Cauley – Chief of Police, Castle Rock Police Department
- Chief Phil Lukens – Director of Police, Rhode Island Airport Corporation
- Chief Robert Spinks – Chief of Police, Parsons Police Department
Making the case for AI in promotions and evaluations
Lisa Broderick opened the discussion by drawing parallels between AI and other disruptive technologies that have reshaped society — from the personal computer to the internet. Just as these innovations transformed how we communicate and work, she said, AI now offers policing a chance to rethink how it identifies and develops leadership talent.
Her motivation is grounded in the mission of Police2Peace: to advance policing that is effective, empathetic and just. “What better way to do that,” she asked, “than by using the best technology to find the best people to lead our agencies?”
The limits of traditional systems
Before adopting AI, most departments relied on oral boards, written exams and a patchwork of supervisor evaluations — processes that demanded heavy administrative time but often delivered inconsistent results. Chiefs on the panel described how these systems tend to favor strong test-takers over steady performers, overlook intangible leadership traits and leave little documentation to defend promotion decisions. In smaller agencies, limited evaluator pools can also increase bias and discourage candid feedback. Together, those factors make it harder to identify the best leaders — and to explain promotion outcomes with confidence.
From static assessments to dynamic feedback
For decades, police promotions have depended heavily on standardized tests and short-form assessments that capture only a moment in time. Chief Phil Lukens pointed out that this often rewards those who “test well” over those who demonstrate steady leadership on the job. He and others on the panel argued that the shift to AI-driven 360-degree evaluations marks a turning point — from static assessment to dynamic feedback.
Castle Rock Police Department is a case in point. Chief Jack Cauley shared how his agency is using a 360-degree process that collects structured feedback from peers, supervisors and subordinates.
How agencies are applying it
Castle Rock PD first adopted the AI-assisted 360 process for promotional testing and leadership selection, gathering structured feedback from supervisors, peers and master patrol officers to better inform advancement decisions. Each participant receives a development plan summarizing key strengths and growth areas, which has made the process both more efficient and more constructive. Parsons PD followed a similar path, starting with promotional testing before expanding the platform to annual employee evaluations. Both departments report measurable time savings, greater participation and improved confidence in outcomes.
Participants answer open-ended questions about communication, leadership, decision-making, empathy, cultural advocacy and humility. An AI engine aggregates that data into a comprehensive report, identifying common themes and quantifying strengths and developmental areas. Each participant, whether promoted or not, receives a personalized development plan.
The system — the Policing Performance 360 platform developed by CivicSolutions in collaboration with Police2Peace — is designed specifically for law enforcement agencies to streamline promotions, performance reviews and leadership development.
The result, according to Cauley, has been “a more holistic and transparent process that reflects who our people really are — not just how they perform under test pressure.”
Tangible results: efficiency, participation and cost savings
The outcomes have been significant. Castle Rock PD reported saving more than 40 hours of administrative time per promotion cycle, doubling evaluator participation and achieving over $4,000 in savings per rank promotion — all while improving satisfaction with the process. Evaluators have praised the system for its clarity and efficiency, while candidates appreciate the detailed feedback they receive.
Similarly, Chief Robert Spinks said Parsons PD first used the AI-supported Policing Performance 360 platform for promotional testing and found that it produced deeper, more factual data on each candidate’s strengths, weaknesses and areas for growth. The resulting reports, he explained, gave staff a sense of ownership in the process and served as career-development guides for everyone who participated — whether they were promoted or not. Encouraged by the positive results, Parsons PD plans to expand the use of AI-generated 360 assessments to annual evaluations for command staff, sergeants and line officers.
The platform also makes participation simple: raters can speak or type their input via secure links, and AI compiles the results automatically. Chiefs can customize weighting by role or rank and filter out outlier responses to ensure balanced outcomes.
The broader benefits
Together, the chiefs said, the advantages go beyond speed and savings. The Policing Performance 360 system has improved consistency across evaluators, produced transparent documentation that stands up to scrutiny, and created a clearer connection between performance feedback and professional growth. Departments reported stronger trust in the process, higher morale among candidates and fewer disputes after promotion decisions. For smaller agencies, automation also freed up supervisors to focus on coaching instead of paperwork.
Earning trust through transparency
Because the word “AI” can raise eyebrows, each panelist emphasized the importance of transparency and communication in implementation. This application of AI, they stressed, is not about automation or surveillance — it’s about organizing human feedback.
Cauley noted that his team built trust by being open about how the data would be used and by framing the process as an enhancement, not a replacement, for human judgment. Lukens described it as “a low-risk, high-value application of AI that helps us make better, more defensible decisions.”
Broderick agreed: “When people understand that AI is helping interpret their peers’ insights rather than making decisions itself, resistance drops dramatically.”
Expanding beyond promotions
The panelists also explored how this technology can strengthen performance evaluations and ongoing leadership development. By applying the same 360-degree framework to annual reviews, agencies can track progress over time, detect trends across units and identify future leaders early.
Castle Rock is now building a secure, closed database of feedback data to guide coaching, training and succession planning. “Imagine being able to ask your own data for answers,” said Lukens. “That’s where leadership development is heading — using our information to solve our own challenges.”
Spinks added that Parsons PD plans to use the platform for performance evaluations at every level of the organization. “We’re seeing higher morale because employees feel their voices matter in the process,” he said. “It’s made leadership evaluation something people look forward to rather than dread.”
A scalable, low-risk model for any agency
Panelists agreed that one of AI’s biggest advantages is scalability. Agencies of any size can adopt the model without overhauling their HR systems. Implementation begins with small pilot groups — often command staff or promotional candidates — before expanding to rank-and-file employees.
The system’s anonymity and auditability help ensure defensible results even in unionized environments, where fairness and documentation are paramount. “It’s not about replacing judgment,” said Anderson. “It’s about equipping chiefs with better information and a process that saves time while improving trust.”
From data to development
Perhaps the most powerful shift described was cultural: moving from evaluation as judgment to evaluation as development. Each participant walks away with a report that highlights what they do well, where they can improve and practical recommendations to help them grow.
Cauley noted that this approach transforms the emotional tone of performance conversations. “Instead of ‘why didn’t I get promoted,’ the question becomes ‘what can I do to prepare for the next opportunity?’”
That shift — from evaluation as judgment to evaluation as growth — may be AI’s most valuable contribution to policing’s next generation of leaders.
Tactical takeaway
Start small: Pilot an AI-assisted 360 review with one rank or unit. Clearly define rater groups, share how results will be used, and deliver each participant a written development plan. Measure time saved, evaluator participation and satisfaction to build support for wider adoption.
Where could structured feedback make the biggest impact in your agency? Share below.
| WATCH: AI questions for police chiefs
