Top 10 AI Prompts and Use Cases and in the Government Industry in New York City

Generative AI matters for New York City government because it can scale services, cut friction, and boost outcomes - from streamlining Medicaid and DMV workflows to powering 311-style chatbots - while also surfacing urgent risks around bias, privacy, and election misinformation.

The Manhattan Borough President's “A Call to Action on AI in NYC” lays out concrete recommendations for agency AI policies, workforce planning, and education (Manhattan Borough President AI NYC recommendations for agency AI policy and workforce planning), and Google Cloud documents live New York deployments in healthcare and constituent services that show tangible gains and governance trade-offs (Google Cloud case studies on generative AI in New York public sector deployments).

With symposium findings warning of deepfakes that briefly rattled markets, city agencies need audits, human-in-the-loop checks, and practical upskilling - such as Nucamp's 15-week AI Essentials for Work bootcamp (Register for Nucamp AI Essentials for Work 15-week bootcamp) - to adopt responsibly and at scale.

Attribute	Information
Description	Practical AI skills for any workplace
Length	15 Weeks
Cost (early bird)	$3,582

“Artificial intelligence in the public sector is more than wishful thinking,” says Karen Dahut, CEO of Google Public Sector.

Ludo Fourrage is the CEO of Nucamp.

Selection prioritized prompts and use cases that align with New York's evolving governance needs: choices were weighted toward high public‑impact opportunities that can be governed, audited, and staffed responsibly - reflecting findings from the FINOS AI Governance Framework workshop key takeaways (FINOS AI Governance Framework workshop key takeaways).

Cases that expose agencies to transparency, bias or accuracy risks were deprioritized unless accompanied by clear human‑in‑the‑loop checks and training recommendations, echoing the New York State Artificial Intelligence Governance audit report's call to develop coordinated statewide training and stronger ITS guidance (New York State Artificial Intelligence Governance audit report).

Practicality and policy alignment were also essential: candidate prompts needed to fit the NYC AI Action Plan implementation guidance's emphasis on ethical deployment, procurement safeguards, and workforce readiness (NYC AI Action Plan implementation guidance), so each selected use case pairs a concrete operational task with measurable controls and training paths.

Selection Principle	How it shaped prompts
Risk‑based governance	Prioritize prompts with mapped controls (18 risks → 17 controls)
Public impact & transparency	Favor cases with disclosure and human review per NY audit
Feasibility & procurement	Ensure prompts fit NYC Action Plan procurement and training goals

“Risk comes from not knowing what you're doing.”

Policy drafting and review for NYC agencies should start with practical, battle‑tested templates and clear, enforceable rules: borrowable frameworks like the GovAI Coalition's templates and resources for municipal AI policy (GovAI Coalition templates and resources for municipal AI policy), while customizable municipal templates - such as the Ordinal AI policy starter - help translate principles into everyday rules about procurement, disclosure, and audits (Ordinal AI policy template for local governments).

Concrete checklist items to adopt now: require IT approval and a central registry for approved tools, log or cite AI use in significant communications, enforce human‑in‑the‑loop fact‑checking before publishing, and prohibit input of PII into public models - practical guards that turn abstract ethics into actionable controls.

Imagine every AI output arriving with a small “draft” stamp and a staffer's initials: that one vivid habit alone can prevent a cascade of errors and public records headaches.

Resource	Purpose
GovAI Coalition templates	Policy, governance handbook, incident response, procurement aids
AI Policy Template (Ordinal)	Plain‑language municipal policy scaffold for transparency, accountability, training
AI Contract Hub / FactSheets	Vendor disclosures and example model fact sheets for procurement review

“AI outputs shall not be assumed to be truthful, credible, or accurate.”

Constituent communications need to be simple enough that New Yorkers can act the first time they read them, and generative AI can do the heavy lifting - when prompted correctly - to de‑jargonize letters, renewal notices, and 311 replies into clear, scannable guidance.

Build prompts that ask the model to hit a grade‑6–9 reading level, use active voice, shorten sentences, add subheads and bullets, and replace technical terms with everyday words, following NYC InfoHub plain language tips for government communications (NYC InfoHub plain language tips for government communications) and the statewide standard that makes plain writing a public service (New York State plain language guidance for public service communications).

Pair model outputs with a mandatory human review and training - use curricula like the CDD/YAI accessible information program - so AI becomes a productivity tool that reduces errors and call‑backs instead of adding risk.

Federal resources also underscore this approach: PlainLanguage.gov guidance and training materials (PlainLanguage.gov guidance and training materials), creating consistent, accountable customer messages across agencies.

“To keep your application moving, please send your documents by August 15. If we have not received the documents by this date, we won't be able to approve your application.”

Public engagement and listening in NYC is already a large, multilingual operation - Participatory Budgeting (PBNYC) and The People's Money have mobilized some 82 community partners, translated ballots into 12 languages, and produced high‑volume participation (110,371 ballots cast in recent cycles) - so a practical “Public Engagement & Listening” prompt should help agencies turn that raw civic input into usable priorities and plain‑language summaries for neighborhood decision‑making.

A well‑scoped prompt would cluster ideas from idea‑generation sessions, surface the recurring themes that produced many winning projects (mental health, job training, youth services), flag equity neighborhood allocations, and format briefings that staff can share with community partners and translate for non‑English ballots.

By aligning outputs with the City's PB phases - idea collection, proposal development, GOTV and voting - agencies can speed analysis while preserving public transparency and the inclusive features (in‑person and online voting, broad outreach) described in the City Council's PBNYC materials and Participedia's case study of The People's Money initiative (NYC Council official Participatory Budgeting page, Participedia case study: The People's Money Initiative - NYC).

Metric	Value
Community partners engaged	82
Ballots cast	110,371
Ballot languages	12
Noted project focuses	Mental health (13), Job training (9), Education (7)

Legal research and brief support for NYC agencies needs prompts that do more than fetch cases: they must surface binding authority in the Second Circuit or New York Court of Appeals, pull relevant consent decrees and DOJ summaries, flag where federal precedent changed (for example, the Supreme Court's 2024 overruling of Chevron deference in Loper Bright v.

Raimondo), and produce concise, source‑linked brief drafts that annotate holdings, citations, and likely persuasive weight so human reviewers can verify and file with confidence.

Good prompts ask the model to prioritize primary sources (opinions and orders from a free case law database like Justia's U.S. Case Law), to extract DOJ case summaries and enforcement outcomes for civil‑rights or administrative matters (DOJ Civil Rights Division case summaries), and to note litigation volume and status trends reflected in current trackers - so a litigator isn't blind to a wave of related filings.

The practical result: AI that turns a stack of PDFs into a one‑page memo that highlights whether a case is binding, persuasive, or under active appeal, leaving attorneys to focus on strategy and ethical review.

Metric	Count
Total cases tracked (Just Security)	371
Awaiting court ruling	140
Temporarily blocked	78
Blocked	23
Government action stopped	4
Case closed	19

For NYC agencies drowning in permits, contracts, and FOIA requests, a sharp “Contract & Permit Extraction” prompt turns messy PDFs and scanned files into structured, auditable data so staff can stop hunting for clauses and start acting on them: AI document analysis can ingest mixed formats, classify amendments, extract payment terms and renewal dates, and surface compliance red flags so renewal notices, inspections, and vendor obligations no longer slip through the cracks (see IBML AI document analysis primer for government contracts).

Leveraging the GenAI IDP Accelerator pattern from AWS lets agencies combine OCR, LLM summarization, confidence scoring, and human‑in‑the‑loop review to scale from pilot to production - so citizen applications and permit packets that once took weeks to comb can produce searchable fields and one‑page summaries in minutes.

Practical pilots in the public sector also highlight big wins in records management and security: automated indexing feeds case management systems, reduces backlog, and helps meet FOIA and audit timelines (read the DatabankIMX public‑sector guide to automated records management).

Built‑in confidence scores and HITL checkpoints keep legal and procurement teams in control while delivering faster, more transparent service delivery for New Yorkers.

Metric / Finding	Source & Value
Staff time savings potential	60% of employees estimate they could save 6+ hours/week if manual entry automated (DatabankIMX)
IDP market projection	CAGR 30.1% to $11.29B by 2030 (Hyland)
Industry accuracy / automation	Hyperscience: up to 95% data entry with >99% accuracy; ~80% out‑of‑the‑box automation (FedScoop)
Case study improvements	Deep Cognition: 80% faster turnaround, 99%+ accuracy, ~75% time savings in government cases

“Hyperscience delivers up to 95% of data entry with over 99% accuracy, far surpassing the average industry accuracy rate, which hovers around 55%.”

Administrative automation for NYC agencies isn't about replacing judgment - it's about shrinking the boring, repetitive parts of email work so staff can focus on decisions that matter: deploy prompt patterns that auto‑fill meeting requests, confirmations, reminders, and follow‑ups from vetted templates, then require a quick human review before send.

Collections like the Starter Story "10 Executive Assistant Email Templates" provide ready‑made subject lines, meeting confirmations, and scheduling messages that speed routine outreach, while the Axios HQ communications template library and best‑practice templates help maintain consistent voice, inclusivity, and track opens and clicks across mission units (Starter Story 10 Executive Assistant Email Templates for Executive Assistants, Axios HQ communications template library and best‑practice templates).

Pair templates with brief, plain‑language prompts (lead with the ask, include attachments, list next steps) and timing rules from follow‑up guidance - e.g., short follow‑ups 24–48 hours after initial contact - to cut back‑and‑forth and reduce call‑backs; the payoff is simple: routine notices and reminders become predictable, auditable, and often resolvable in a single short reply, freeing caseworkers for complex exceptions and community outreach.

“As our Social Impact work grows, we recognized smart communications would be crucial. Axios HQ is a streamlined platform to communicate with our employees around the world, and the ability to easily customize our messaging for regional audiences.”

Procurement evaluation and RFP drafting in New York City can move from slog to strategic when generative AI is used to create baseline RFP language, automate market research, and flag vendor‑risk signals - while governance and training keep accountability intact; practical training such as the AI for Public Sector Procurement course (Innovate‑US) equips teams to use AI for document review, spend analysis, and cross‑team coordination (AI for Public Sector Procurement course - Innovate‑US practical procurement AI training), and NASPO's Procurement U offers bite‑size, free modules to build procurement staff fluency before scaling tools (NASPO Procurement U free procurement AI microlearning and training).

Industry reporting shows immediate wins - AI shortens scope language and surfaces issues that once lurked in 35‑page scopes that could be replaced by tidy 3–5 page statements of work - and also signals where encryption, role‑based controls, and auditable decision trails are required (StateTech article on AI in procurement and government accountability), so pilots should pair generation with mandatory human review and clear transparency rules to preserve fairness and public trust.

Resource	Format / Key benefit
AI for Public Sector Procurement (Innovate‑US)	Self‑paced course; practical skills for document review, market research, certificate of completion
Procurement U (NASPO)	Free microlearnings and courses for procurement professionals; builds AI literacy and procurement best practices
StateTech article	Overview of AI uses and risks in procurement; examples of scope shortening, vendor analysis, and accountability requirements

“When a tool is making a decision for that entity - if you're using a tool to decide who gets a contract - you have to be able to show how that decision was made.”

Emergency preparedness prompts for New York City agencies should turn sprawling guidance into fast, usable actions: craft a plan that extracts Ready New York household steps - pick two meeting spots, map all exit routes, and assemble a Go Bag with waterproof copies of IDs and seven days' supplies - while producing clear, plain‑language evacuation vs.

shelter‑in‑place checklists that staff and residents can follow in minutes (NYC Emergency Management Get Prepared guidance for household preparedness).

They should also auto‑draft Notify NYC alerts and multi‑channel messages that align with school and EOC protocols - NYC DOE's EPR/EOC model runs 24/7 and creates stakeholder notifications within 15 minutes - so outputs feed the city's operational hub without extra friction (NYC DOE Emergency Planning & Response (EPR) and Emergency Operations Center (EOC) guidance).

For complex scenarios, prompts can reference New York State planning guides (mass‑fatality, mass‑gathering, school safety) to generate incident‑specific checklists and tabletop exercise scripts that keep drills realistic and AARs actionable (New York State Division of Homeland Security & Emergency Services planning resource guides).

Imagine a single plain‑language SMS that names a nearby shelter, lists three items from your Go Bag, and tells you where to meet - that one clear message can cut panic and speed reunification.

Resource	Use
NYCEM Get Prepared	Household plans, Go Bag & evacuation guidance
NYC DOE EPR / EOC	24/7 operational notifications, EOC coordination, school EOPs
NYS Planning Resource Guides	Mass‑fatality, mass‑gathering and planning frameworks

Data analysis and reporting turn government data into fast, actionable decisions by pairing BigQuery's operational charts with clear dashboard specs and delivery rules: prompt models to generate a dashboard template that lists the exact BigQuery metrics to surface (slot usage, job concurrency, bytes processed, query execution time percentiles), the chart types (timeline charts, error donut, top‑active queries), filters (region, reservation, project, time range), and alert thresholds (for example, a 99th‑percentile execution‑time trigger) so engineers can wire Cloud Monitoring alerts and scheduled PDF reports from Looker without guesswork - see Google's guidance on creating dashboards and alerts and on monitoring resource utilization in BigQuery (Create dashboards, charts, and alerts | BigQuery, Monitor health, resource utilization, and jobs | BigQuery).

For spatial or public‑facing briefs, include a map tile spec (choropleth, legend, state or tract join keys) like CARTO's BigQuery‑backed COVID dashboards so a single map can instantly show where service demand is spiking - one clear visual often replaces ten pages of tables.

Require the prompt to emit datasource queries (INFORMATION_SCHEMA or dataset SQL), human‑review checklists, and delivery rules (alerts, recipients, cadence) so dashboards scale from pilot to production while preserving auditability and performance observability.

Metric	Why it matters
Slot usage	Diagnoses capacity and contention across reservations
Query execution times (P95/P99)	Sets alert thresholds and surfaces slow queries
Bytes processed	Tracks cost drivers and query efficiency

Multimodal outreach for NYC agencies should turn data and plain‑language rules into sharable, accountable assets: craft prompts that output ready‑to‑post social copy with suggested hashtags, tag lines, alt text, and image specs (so posts follow the City Bar's social media best practices around hashtags, tagging, visuals, and copyright), plus parallel language variants and field materials for non‑English audiences drawn from HPD's NYCHVS playbook - think translated information guides, flash cards and even the small coloring book used in field packets - to make outreach genuinely multilingual and easy to use in person or online (NYC Bar social media best practices for government outreach, HPD NYCHVS research and multilingual field materials).

Add AI email templates that suggest subject‑line A/B tests and optimal send times so messages reach residents when they'll act, and require a human review step and a simple audit trail to keep public trust intact (AI‑driven email outreach strategies and best practices).

Picture a neighborhood flyer, social post, SMS and translated packet all generated from one prompt - coordinated, accessible, and auditable.

Asset	Example / Source
Social posts, hashtags, tagging	NYC Bar social media best practices for government outreach
Multilingual field materials	HPD NYCHVS guides and multilingual field materials
Email templates & timing	AI‑driven email outreach strategies and best practices (Martal)

Responsible adoption in New York City means pairing strong governance with real, scalable upskilling: run small, auditable pilots with human‑in‑the‑loop checks, publish vendor and model disclosures, and make training mandatory so staff can spot bias, hallucinations, and privacy risks before they hit the public record.

Free, public‑sector training - like InnovateUS's self‑paced courses and workshops on “Using Generative AI at Work” and prompt engineering - offers practical modules and recorded sessions that agencies can assign to teams to build baseline literacy and governance know‑how (InnovateUS course: Using Generative AI at Work), while targeted bootcamps such as Nucamp's 15‑week AI Essentials for Work provide hands‑on prompt writing and job‑focused skill building so supervisors and caseworkers can apply controls every day (Register for Nucamp AI Essentials for Work).

Start with sandboxed pilots, clear procurement checklists, and a training roadmap that moves teams from awareness to audited production work - one practical course, one pilot, and one accountable policy at a time will keep services fast, fair, and trustworthy for New Yorkers.

Attribute	Information
Description	Gain practical AI skills for any workplace; learn prompt writing and applied GenAI
Length	15 Weeks
Cost (early bird)	$3,582
Registration	Register for Nucamp AI Essentials for Work (15-week bootcamp)

“This fantastic course has provided me with a deep understanding of how to responsibly integrate Generative AI (GenAI) into government tasks. I've gained practical skills in GenAI, including prompt engineering and risk mitigation. Looking forward to applying these insights and continuing to improve processes in the public sector.”