Police Identification and Records Officers

Collect evidence at crime scene, classify and identify fingerprints, and photograph evidence for use in criminal and civil cases.

The occupation "Police Identification and Records Officers" is assigned an automation risk of 31.2%, which places it in the lower-risk category when compared to many other professions. The base risk for this role is calculated at 31.7%. This relatively moderate level of risk is largely due to the nature of many routine and repetitive tasks these professionals perform, as well as the necessity for human judgment in critical elements of their work. Automation technologies, such as digital records management and advanced logistics systems, are already capable of handling a wide range of standardized administrative activities, which accounts for the automation potential reflected in the risk percentage. The top three most automatable tasks for Police Identification and Records Officers include maintaining records of evidence and writing and reviewing reports, packaging, storing, and retrieving evidence, and submitting evidence to supervisors, crime labs, or court officials for legal proceedings. These tasks generally involve detailed documentation and standardized procedures, making them well-suited for automation through software, barcoding, and digital workflow tools. Automated systems can efficiently log, update, and track evidence records, reducing the risk of human error and increasing process efficiency. As organizations continue to adopt digital solutions, the share of routine clerical and logistic tasks completed by machines is likely to grow, heightening the automation risk for these specific work elements. However, some aspects of the job are significantly more resistant to automation. Tasks such as identifying, comparing, classifying, and filing fingerprints with complex systems like the Automated Fingerprint Identification System (AFIS) or the Henry Classification System, performing emergency work during off-hours, and processing film and prints from crime or accident scenes require a blend of critical thinking, situational adaptation, and on-the-spot decision-making. These responsibilities call for originality—a bottleneck skill rated at just 2.8% and 2.9% presence, indicating that while not the dominant skill, its necessity forms an important automation barrier. Furthermore, the responsive and unpredictable nature of fieldwork, particularly in emergency or sensitive contexts, limits the extent to which current technologies can fully replace human officers. This ongoing reliance on human expertise and adaptive problem-solving is why the overall occupation’s automation risk remains moderate.