PROJECT BRIEF

BACKGROUND 

Local governments increasingly deliver resident assistance through digital-first services, yet the residents who most need it are often the least equipped for online-only access. At the same time, cities are adopting resident-facing artificial intelligence (AI) tools often without clear evidence that those tools help residents. Rather than assuming a predefined need, cities require evidence on where access barriers actually sit and whether AI can reduce them at all. 

AIMS 

The City of Fort Collins asked whether residents struggle to access its digital assistance programs and how those struggles vary by language, literacy, income, and digital access. The project assessed accessibility across four stages of a resident's service journey: identifying the appropriate program, understanding requirements and eligibility, completing an application, and obtaining help when a step fails. It then evaluated, barrier by barrier, whether AI is an appropriate and worthwhile intervention, explicitly including where AI is not a recommended solution. 

METHODOLOGY 

The team conducted secondary research before fieldwork: a literature review of municipal AI deployments and their documented outcomes, comparative case studies from peer cities, a demographic profile of Fort Collins, and structured walkthroughs of the City's live service pages. The team then collected primary evidence through interviews with three frontline City staff, written responses from the City's Chief Communications and Engagement Officer, and the City's intercept-survey and website analytics data. Because planned resident focus groups did not take place, resident experience is proxied through staff and city data. Findings are labeled by evidence strength, and single-source observations are flagged for verification. 

DELIVERABLES 

Deliverables included a combined report comprising (1) a Resident Access Assessment prioritizing eight access barriers within a two-layer model separating page-level problems from integration and hand-off problems; (2) an AI Suitability Assessment issuing a verdict on whether AI is a suitable solution for each barrier; and (3) a five-stage general evaluation framework based on AI case studies best practices for judging any proposed or ongoing AI initiative. 

IMPACT AND FUTURE WORK 

The assessment equips Fort Collins to make evidence-based decisions about AI adoption: fix systems and forms first, pilot three bounded AI uses under explicit conditions, and measure every tool against the simpler non-AI alternative. Future work includes validating findings directly with residents and verifying single-source observations before acting on them.