{"resourceId":"alda-cba-ai-police-report-writing-20260612","versions":[{"version":"external-e286bed4e7a4284c4b6c3de1dc13f1b82deb6bb836efbf929603d911d5d47bb2","resource":{"id":"alda-cba-ai-police-report-writing-20260612","title":"Cost-benefit study finds AI police-report tools can show positive NPV under per-officer pricing but negative under bundled contracts, without valuing report quality","organization":"Erik Alda (SocArXiv / OSF preprint)","sector":"Policing / AI-assisted report writing evaluation","geography":"Manchester, New Hampshire, United States (medium-department modeling)","publishedAt":"June 12, 2026","publicationDate":"2026-06-12","eventDate":null,"sourceName":"SocArXiv (OSF)","sourceLabel":"When Does AI Pay for Itself? A Cost-Benefit Analysis of AI-Assisted Police Report Writing","sourceUrl":"https://osf.io/preprints/socarxiv/4x8zw_v4","evidenceClass":"academic-research","outcomeClass":"mixed","topics":["knowledge-work","governance-procurement","operating-model"],"finding":"Alda's June 12, 2026 preprint models agency-budget cost-benefit for AI-assisted police report writing at Manchester PD. Under per-officer subscription pricing, average NPV is about $2.3M (favorable productivity reading) or $0.8M (conservative reading anchored to the department's RCT null on speed) for a medium department, with positive return likely in both; attributing a bundled vendor contract instead yields a negative return. The author warns productivity evidence draws on Draft One field results while modeled price is PoliceNarratives.AI at Manchester, report quality is not valued, and results should be read as an upper bound on the labor-savings case. Newly relevant amid ongoing U.S. Draft One pilots and quality debates.","sledRelevance":"Gives procurement teams a quantitative caution: pricing structure and how much time savings are credited to AI can flip the ROI sign even before quality risks are priced.","evidence":"Opened the SocArXiv PDF via OSF download. Preprint modeling study; not peer-reviewed here; mixes products and does not measure downstream justice outcomes.","architectureImplications":"Separates subscription SaaS costing from bundled suite contracts; implies agencies should meter AI report seats independently of body-camera bundles when testing ROI.","governanceImplications":"Interpretation: Require pre-registered success metrics including quality and prosecutor outcomes, not labor hours alone.","securityPrivacyImplications":"Paper focuses on labor economics; does not assess BWC-audio privacy or model-provider data flows.","caveats":"Preprint; quality unvalued; Draft One evidence vs PoliceNarratives.AI price; Manchester-specific.","streamIds":["public-safety"],"roles":{"sales":"Sales framing: a Manchester-based cost-benefit model says AI report writing can look ROI-positive on per-officer seats yet negative if costs are bundled—and it ignores report quality. Agencies need bounded financial analysis tied to their contract shape. This preprint does not prove time savings in a new department.","engineering":"Engineering framing: instrument actual edit time, seat counts and contract cost allocation before trusting vendor ROI slides. Prerequisites include baseline report-duration data and clarity on whether AI is sold standalone or in a suite. Proof of value is a department-specific Monte Carlo or sensitivity using local wages and prices.","delivery":"Delivery framing: run a priced pilot that logs hours, override rates and quality samples, then recompute NPV under subscription vs bundle assumptions. Ownership is finance plus patrol admin. Risk: buying on vendor time-savings claims while RCT evidence showed null speed gains."},"roleDetails":{"sales":{"customerProblem":"Departments are buying AI report writers without a clear, quality-aware ROI under their actual contract structure.","stakeholders":["Police chief","Budget/finance","Patrol command","City procurement","Vendor account team"],"discoveryQuestions":["Is pricing per seat or bundled with cameras?","What local time-savings evidence exists?","Will quality metrics enter the go/no-go?","How many officers would be licensed?"],"valueHypothesis":"Contract-aware CBA can prevent false-positive ROI from bundle accounting; it cannot guarantee field time savings.","potentialEngagement":"Two-week AI report-writing ROI model using the agency's wages and contract.","unsupportedClaims":["AI always pays for itself","Manchester results transfer unchanged","Quality is unaffected"]},"engineering":{"fit":"Medium agencies evaluating Draft One-class tools with either seat or suite pricing.","architectureIntegration":"Capture timestamps from CAD/RMS draft-to-submit, seat license counts and cost centers separating AI from BWC storage.","prerequisites":["Baseline report duration data","Wage/benefit loaded rates","Contract price schedule"],"constraints":["Preprint methods","Cross-product evidence/price mismatch","Quality omitted"],"security":"Keep BWC audio and drafts in approved CJIS/cloud boundaries when instrumenting pilots.","proofOfValue":["Replicate NPV under local prices","Sensitivity on time-savings credit","Include a quality-failure cost scenario"]},"delivery":{"work":"Design pilot metrics, allocate costs correctly and brief leadership on subscription vs bundle NPV.","dependencies":["RMS/BWC vendors","Finance","Union/policy on AI drafts"],"ownership":"Patrol administration with budget office","skillsAdoption":"Supervisors need to score AI-draft quality, not only speed.","governanceCheckpoints":["Pilot go/no-go criteria set","Mid-pilot metrics review","Procurement award memo with CBA"],"acceptanceCriteria":["Documented cost attribution method","Local sensitivity analysis delivered","Quality sample plan approved"],"risks":["Over-crediting AI for organizational learning","Ignoring prosecutor rejection costs","Bundle accounting hides true AI spend"]}},"retrievedAt":"2026-10-29T01:05:13Z","enrichedAt":"2026-10-29T01:06:25Z","enrichmentBasis":"retrieved source","accessibilityWorkforceImplications":"Assumes officers still review drafts; adoption curves affect NPV more than headline vendor time-savings claims.","procurementImplications":"Interpretation: Compare per-officer subscription versus bundled attribution in any AI report-writing buy.","operatingModelImplications":"Operational owner: budget office with patrol command evaluating AI report tools.","sourceVerification":{"openedUrl":"https://osf.io/preprints/socarxiv/4x8zw_v4","referenceExcerpt":"subscription pricing, the tool appears to pay for itself: for a medium department, the average","promptVersion":"sled-research-v4.0","model":null,"basis":"agent-reported inspection"}}}]}