Generative AI will change public access less by dazzling interfaces and more by making information findable, legible, and inclusive across languages and abilities. Over the next five years, municipal residents will expect searchable recordings with accurate captions and translations, meeting pages that answer questions in plain language, and records that are verifiable and portable across systems. City and county clerks will orchestrate this shift—not by becoming AI experts but by operationalizing ethical controls, procurement terms, and publication practices that safeguard the public record.

This paper proposes a resident-centered approach where AI augments, not obscures, the meeting lifecycle. We treat accessibility as a service level (caption latency, accuracy, interpreter uptime), embed explainability into publication (disclosure banners, corrections notes), and require portability for every artifact (open captions, transcripts, prompts, and logs). We demonstrate how retrieval-augmented generation (RAG) can turn archives into living civic knowledge—while preserving chain-of-custody and honoring retention schedules.

Our analysis organizes change into four domains: (1) Accessibility and language access at scale; (2) Retrieval and summarization for public understanding; (3) Trust and governance through transparency and identity controls; and (4) Budgets, procurement, and staffing models that make improvements durable. Each domain includes checklists, tables, and sample clauses that clerks can adopt with small teams and limited resources.

We close with a 24-month roadmap and a three-scenario outlook (baseline, constrained, ambitious). The common thread is humility: AI is valuable when its outputs are observable, reversible, and tied to public artifacts that residents can inspect. With these disciplines, generative AI becomes an engine for inclusion, not confusion.