Top 10 AI Prompts and Use Cases and in the Government Industry in Seattle

AI matters for Seattle government because it promises faster, more responsive services while raising concrete risks that city leaders are already trying to manage: Seattle's Responsible Artificial Intelligence Program lays out principles on privacy, transparency, human‑in‑the‑loop review, and security to guide safe adoption (Seattle Responsible Artificial Intelligence Program details), yet local reporting shows staff across Washington have used ChatGPT to draft emails, mayoral letters and policy briefs - including at least one mayoral letter written partly by a chatbot - sparking questions about accuracy, disclosure and public trust (Cascade PBS/KNKX report on ChatGPT use by Washington officials).

With a statewide AI Task Force shaping guidance, practical training (for example, Nucamp's AI Essentials for Work bootcamp) can help municipal teams learn prompt craft, detect hallucinations, and keep civic data secure so promises of efficiency don't undermine accountability.

“AI is becoming everywhere all the time.” - Bellingham Mayor Kim Lund

To surface the top prompts and real-world use cases for Seattle-area municipal teams, the reporting behind this series began with thousands of ChatGPT conversation logs obtained via public records requests to cities like Everett and Bellingham and reviewed in reporting by Cascade PBS and KNKX; those records show frequent, repeat prompts - from rewriting constituent emails and drafting mayoral letters (one support letter matched ChatGPT output in roughly half its sentences) to filling out grant applications, generating social posts, building contract-evaluation matrices, debugging code and summarizing meeting notes - which were then grouped by frequency, potential public impact and risk (accuracy, privacy and disclosure).

Findings were cross-checked against published local guidance (Washington's interim AI guidance for state employees), city policy drafts and interviews with mayors and IT directors, and redactions in the logs (GIS code, active investigations) flagged where confidentiality or security concerns limit safe adoption; the result is a prioritized list centered on high‑use, high‑impact prompts that city staff already rely on and the controls they need.

Cascade PBS reporting on Washington cities using ChatGPT and KNKX public-records analysis on city officials using ChatGPT grounded the selection.

“There's an abundant need for caution and understanding the implications of these tools.” - Bellingham Mayor Kim Lund

City-run chatbots can turn long phone queues and dense web pages into instant, searchable help desks - and vendors built for government make that practical: Rezolve.ai markets an AI service desk that integrates with Microsoft Teams, offers self‑service chatbots and no‑code automation, and says its platform can automate up to 65% of routine issue resolutions while its Agentic SideKick can auto‑resolve roughly 30–70% of L1 tickets, freeing staff for complex work (Rezolve.ai AI service desk for government agencies).

For Seattle, which already has a Generative AI policy requiring human review and vendor controls, a team‑facing bot can be paired with citizen‑facing channels to deflect FAQs, surface benefits and permitting steps, and provide 24/7 crisis information - practices that mirror recommended emergency uses of conversational AI in government (City of Seattle generative AI policy for city employees; AI chatbots for 24/7 citizen crisis support in government).

The “so what” is simple: a well‑scoped bot can answer or route the first wave of requests night and day, turning an overwhelmed phone line into an always‑on, accountable triage layer that preserves human review for high‑risk cases.

“Rezolve.ai allows our staff to get help 24x7, 365 days a year from any device. This can free up support staff for more in-depth support.”

Drafting mayoral correspondence and letters of support is one of the clearest, high‑value places for Seattle‑area officials to use generative AI: large language models can turn a blank page into a polished first draft in minutes, speeding routine outreach while preserving staff time for judgment calls - a core recommendation in the ICMA primer on ChatGPT for local government (ICMA ChatGPT guide for local government officials).

For grant work, AI can accelerate funder research, outline project narratives, and produce consistent proposal sections, but nonprofit guides caution that outputs must be verified, tailored, and human‑curated to avoid generic or inaccurate submissions; specialized tools like grant assistants can improve reliability (ChatGPT grant writing guide for nonprofits).

Risk analyses also warn that unchecked AI use can introduce bias, privacy leaks, or even propagate errors that skew funding decisions, so policies should require anonymizing sensitive data, layered review, and clear disclosure when AI contributed to a submission (Orr Group analysis of AI in grant applications and risks).

The practical takeaway: use AI as a drafting engine that multiplies capacity - but keep legal review, local context and a final human voice firmly in the approval loop so trust and credibility aren't sacrificed for speed.

Automating routine admin work - from drafting emails and formatting spreadsheets to logging service requests and populating reports - is already a practical win for Washington cities that want to reclaim staff time: a large government trial found Microsoft Copilot and similar tools could save civil servants nearly two weeks of work per person per year by cutting daily email and drafting time (roughly a 70% drop in that 30‑minute daily grind) (Microsoft Copilot trial time savings for civil service).

Everett's IT leaders have moved staff toward Microsoft Copilot for security and compatibility, requiring exemptions to use other chat tools, while Copilot Studio offers government‑specific plans with US data residency, FedRAMP High controls, and tenant isolation to limit exposure of sensitive content (Copilot Studio US Government guidance and FedRAMP High controls).

Copilot Studio agents can connect to Power Automate flows to complete end‑to‑end tasks (create SharePoint records, trigger approvals, send notifications), turning repetitive clicks into governed automations that free humans for judgment work - but KNKX reporting also shows why cautious rollout matters: staff still need layered review because AI outputs sometimes invent facts or miss context (KNKX report on Washington city officials using AI for government documents), so policy, logging and human verification must travel with any efficiency gains.

“Wordsmithing isn't everybody's strength.” - Everett Mayor Cassie Franklin

Summarizing meetings, legislation and public comments is now a practical way for Washington cities to keep records clear, accessible and actionable: AI notetakers can transcribe conversations, identify speakers, pull out decisions and auto‑generate action items so a two‑hour council meeting becomes a concise, time‑stamped decision map staff and residents can scan in minutes.

Tools such as Fireflies, which offers searchable transcripts, speaker recognition and comprehensive AI summaries, and Otter, which provides live transcription, auto summaries and action‑item capture, plug into Zoom, Teams and YouTube workflows to create shareable recaps and searchable archives for councils, boards and the public.

See Fireflies AI meeting transcription and summaries at Fireflies AI meeting transcription and summaries and Otter AI meeting transcription and summaries at Otter AI meeting transcription and summaries.

For newsrooms and municipal clerks, webinars show these systems can process long YouTube recordings into structured, time‑stamped summaries with speaker IDs and custom topic focus - making public meetings more discoverable, accountable and easier to follow for busy residents.

“The whole point of this app and this process is to help publishers cover those meetings that maybe you used to cover but don't cover anymore as much, or you can't get to every meeting.”

Legal‑document simplification is a practical way for Washington cities - including guidance being developed for Everett - to make rules, permits and notices genuinely usable for residents: rigorous experiments show interactive chat assistance and LLM‑generated plain‑language summaries significantly improve comprehension and perform comparably to human expert rewrites, especially when the simplified text is published alongside the original legal wording (SSRN study on LLM legal simplification).

Practical tools and web apps that translate legalese into plain English can provide instant, browser‑based summaries and key‑term glossaries for leases, permits and benefit notices (Legalese Decoder - AI-powered plain English conversion tool), while Rules as Code experiments demonstrate that LLMs can help generate machine‑readable policy and plain‑language summaries when paired with retrieval, templates and human oversight (AI‑Powered Rules as Code experiments for public benefits policy).

The operational takeaway for municipal teams: treat AI outputs as capacity‑multipliers - not legal signoffs - by mandating layered review, using curated prompt libraries, and publishing side‑by‑side summaries so residents can scan obligations and deadlines quickly without losing the full legal text.

AI-driven forecasting and resource-allocation tools are moving budgeting from static line items to dynamic, priority-led decision making - an especially practical shift for Washington cities juggling tight revenues and pandemic-era staffing gaps.

Priority-based models, combined with machine learning, can scan complex spending and outcome data to surface tradeoffs and reallocation opportunities (NLC's primer on AI-enabled priority-based budgeting shows localities finding large, tangible savings - Pittsburgh identified $41 million for reinvestment - by shifting to priority-driven approaches: NLC primer on AI-enabled priority-based budgeting and municipal savings).

Complementing that, AI's predictive analytics and scenario planning let finance teams run “what‑if” forecasts in real time, tighten revenue estimates, and detect anomalies before they become crises - capabilities the IMF highlights as central to smarter public finance and greater fiscal transparency (IMF analysis on unleashing AI in public finance and fiscal transparency).

The so‑what: instead of scrambling to cut across-the-board, municipal leaders can reassign dollars to climate resilience, public safety or equity programs with evidence-backed confidence and clearer audit trails for residents.

Tax collection and fraud detection are prime places for Washington governments to apply the same machine‑learning methods that helped the U.S. Treasury prevent and recover more than $4 billion in fiscal year 2024 - efforts that included $500 million from expanded risk‑screening, $2.5 billion by prioritizing high‑risk transactions, and $1 billion recovered by expediting check‑fraud detection with ML (U.S. Treasury FY2024 enhanced fraud detection press release).

State and local revenue offices, unemployment programs and utility billing teams can use real‑time anomaly detection and behavioral baselines to flag suspicious refunds or unusual payment patterns without slowing service, for example pausing a payment that looks normal by amount but comes from an unfamiliar device or location (Catalis report: AI reshaping fraud detection in government payment systems).

International and tax‑authority case studies show big gains in detection and efficiency but also cautionary lessons about data quality, explainability and privacy - reminding municipal leaders that governance, shared data resources, and layered human review are what turn AI insights into recovered dollars and preserved public trust (VATCalc analysis: tax authorities adopt AI for fraud detection and operational efficiencies).

The so‑what: smarter models can stop losses in real time, reduce noisy false positives, and free analysts to focus on the complex investigations that actually matter.

“Treasury takes seriously our responsibility to serve as effective stewards of taxpayer money. Helping ensure that agencies pay the right person, in the right amount, at the right time is central to our efforts.” - Deputy Secretary Wally Adeyemo

Washington airports and city responders can use AI-driven public‑safety analytics to turn messy, real‑time data into fast, coordinated action: AI video analytics that flag loitering, tailgating or abnormal crowd flows can automatically cue a control room and link video to access logs and flight info, while integrated gunshot‑detection sensors can pinpoint a shooter and feed live feeds to first responders - techniques already documented across U.S. airports and tested in pilot sites (ACRP report on AI in airports security and operations).

Beyond the terminal, federal work shows how ML and computer vision accelerate threat screening, disaster assessments and border security workflows that Washington agencies can borrow for statewide emergency coordination (DHS guidance on using AI to secure the homeland for border and disaster response).

The real payoff is practical: when a sensor detects an anomaly, systems can route verified, time‑stamped evidence to dispatchers and incident commanders - cutting confusion, reducing response times and preserving human judgment for complex decisions; but implementation must pair these gains with strict privacy controls, clear procurement review and community engagement to avoid surveillance overreach, bias, or legal friction (Deloitte analysis of surveillance and predictive policing risks and governance).

Imagine a camera that instantly zooms and follows a person who stops mid‑escalator and sends that clip, with location and access logs, to officers - small seconds that can change outcomes in an emergency.

“Cameras scan people or vehicles in a crowd for motions that appear abnormal, such as walking in the wrong direction on an escalator or stopping a car at an unusual place. Alarms can also trigger the cameras to automatically track the object of interest and dynamically adjust the field of view, providing visual information to the control room.”

Procurement and contract evaluation is where AI can turn slow, paper‑heavy RFP cycles into repeatable, auditable decisions for Washington governments - but only when paired with clear guardrails.

94% of procurement teams now leverage generative AI, and platforms that combine spend analytics, supplier intelligence and contract NLP can automatically classify spend, surface hidden savings, score suppliers, and flag risky clauses for human review, shrinking days of manual redlines to minutes.

Enterprise playbooks recommend embedding accountability, explainability and data controls into each step - assigning owners to AI outputs, keeping audit logs, and limiting sensitive inputs to FedRAMP or single‑tenant options - so model recommendations are reviewable and defensible.

Prompting and embedded AI agents accelerate sourcing (auto‑drafting RFP matrices, scoring responses, and generating compliance checks), but teams should prefer integrated, enterprise‑grade workflows over ad‑hoc public chat tools to preserve traceability and privacy; contextual prompts plus real procurement data yield more actionable supplier scorecards.

The takeaway for Seattle and other Washington agencies: aim for small pilots that deliver measurable time savings, bake governance into procurement buyers' checklists, and require human sign‑off on any contract award driven by AI. Art of Procurement - AI governance framework for procurement | GEP - Simplifying procurement evaluation with AI | Tropic - AI prompts and examples for procurement

Multilingual outreach and personalized engagement are practical, high‑impact tools for Washington governments and tribal partners - especially when tight budgets and rising demand make on‑the‑fly access essential; platforms that combine live AI translation, captions and interpreter services let staff flip a switch and make council meetings, emergency briefings or pop‑up community forums instantly accessible, for example by publishing a QR code in chambers so attendees can pull live captions in their language (a tactic highlighted in Wordly's city rollouts).

Real‑time options range from browser‑based captioning and custom glossaries to remote simultaneous interpretation for high‑stakes sessions, meaning agencies can scale coverage without the logistics of on‑site booths (see Interprefy's RSI and captioning) while still preserving compliance and privacy requirements.

But federal guidance and practitioner reports stress guardrails: machine translation should be paired with human review, tested in local contexts, and audited for accuracy and equity (see digital.gov's guidance and DOJ reporting on AI‑assisted translation).

The bottom line for Seattle and nearby tribal outreach like the Lummi Nation: use AI to lower the barrier to participation, pair it with competent human review, and treat translations as a service design problem so more residents actually understand what the city is saying.

“Your data is your data. We never use it to train our AI model or retain it in our system.” - Kirk Hendrickson, COO, Wordly

For Seattle government beginners, the practical path forward is clear: anchor every pilot in existing city and state guardrails, train staff, and make oversight routine rather than optional.

Start by following the City of Seattle's Responsible Artificial Intelligence Program and the State's interim AI guidelines to require procurement through approved channels, human‑in‑the‑loop review, and documented recordkeeping; treat AI outputs like traceable artifacts by labeling the model, prompt and reviewer so authorship and accountability are transparent (City of Seattle Responsible AI Program, Washington State Interim AI Guidelines for Generative AI).

Pair small, focused pilots (chatbots for FAQs, Copilot for workflows, meeting summarizers) with workforce training and prompt‑craft practice so staff learn to spot hallucinations and privacy risks; practical courses such as Nucamp's AI Essentials for Work bootcamp (15-week course) can build those prompt‑writing and oversight skills.

Finally, bake equity and community engagement into deployment decisions, monitor outcomes, and iterate - small, governed experiments plus clear documentation will preserve public trust while unlocking AI's efficiency gains.

“There's an abundant need for caution and understanding the implications of these tools.” - Bellingham Mayor Kim Lund