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

Philadelphia's government landscape is at an inflection point: local pilots like SmartCityPHL are pairing GoodRoads camera imaging and human review to map cracks, potholes and lane markings across the city - with the goal of scaling inspections across all 2,500 miles of roadway - while sentiment-analysis pilots using Zencity mine 311 reports and social media to surface neighborhood concerns in real time (SmartCityPHL road and 311 pilots).

At the state level, a yearlong ChatGPT Enterprise pilot reported dramatic time savings - roughly 95 minutes per employee per day - prompting Pennsylvania to pair innovation with governance and an executive-led AI board to set safeguards (Spotlight PA on the ChatGPT pilot and policy).

Those gains come with clear caveats - cybersecurity, public-records exposure for prompts, and hallucination risks - so workforce training is crucial; practical programs like Nucamp's AI Essentials for Work bootcamp teach prompt-writing and verification skills that governments will need to adopt AI responsibly.

Bootcamp	Length	Early Bird Cost	Register
AI Essentials for Work	15 Weeks	$3,582	Register for AI Essentials for Work bootcamp

“We don't want to let A.I. happen to us.” - Gov. Josh Shapiro

Methodology: prompts and use cases were chosen to reflect what Pennsylvania's own guidance flags as essential - starting with a readiness assessment, strong governance, careful data management, mandatory disclosure of AI-generated content, and a short list of prohibited uses (no sensitive data, no sole-source final decisions) as summarized in Pennsylvania AI usage guidelines for state governments (Pennsylvania AI usage guidelines for state governments); selections also tested for legal and policy fit against the 2025 state-by-state legislative landscape so teams could spot where tool design might collide with new statutes or executive actions (NCSL 2025 state-by-state AI legislation summary).

Priority favored high-impact, low-risk applications that keep humans in the loop (customer-service assistants, policy-brief analysis, training simulations), plus prompts that are auditable, documentable, and easy to scale for city pilots - gaps such as the absence of statewide K–12 AI guidance were noted as a caution when considering education-facing use cases (Penn Capital Star coverage on K–12 AI guidance and Pennsylvania's gap), ensuring each recommended prompt includes verification steps, provenance metadata, and human-review checkpoints so benefits don't outpace safeguards.

“The single most important ingredient in the recipe for success is transparency because transparency builds trust.” – Denise Morrison

For executive-branch staff in Pennsylvania, ChatGPT Enterprise can move routine heavy lifting off calendars and into minutes: a recent Commonwealth pilot reported roughly 95 minutes saved per employee per day, freeing time that could otherwise be spent drafting a one‑page policy brief, answering resident emails, or joining neighborhood meetings; practical toolkits like OpenAI's prompt‑pack for government leaders give copy‑ready prompts for briefings, fiscal analysis, and plain‑language rewrites so teams don't start from scratch (OpenAI government prompt pack for leaders).

Enterprise features - file upload, Canvas co‑editing, Deep Research and Custom GPTs - help align outputs to approved templates and evidence, while implementation deals such as the GSA OneGov agreement make scaled access possible across agencies (GSA OneGov partnership with OpenAI); guidance from vendors and law firms also stresses that outputs are drafts requiring human review and records‑management safeguards (Debevoise guide to ChatGPT Enterprise features and safeguards), so the “so what?” is concrete: deployed responsibly, these tools can convert slogging administrative hours into measurable constituent-facing work.

“One of the best ways to make sure AI works for everyone is to put it in the hands of the people serving our country.” - Sam Altman

Philadelphia's Philly311 is already the city's “spinal cord” for non‑emergency requests - taking calls, web reports and app photos and returning status updates - and a Custom GPT can make that everyday connection faster and smarter: by powering AI‑powered 311 solutions that accept photos, exact addresses and multi‑channel inputs, a chatbot can auto‑triage issues, route them into the right department, and surface the same real‑time tracking residents expect from the Philly311 mobile app (Philly311 contact center and mobile app information and status tracking).

Low‑code, AI‑enabled platforms show how automation and analytics improve engagement and case management, while reducing repetitive workloads for staff (AI-powered 311 solutions and CaseXellence for municipal governments).

The payoff is concrete: imagine a neighbor snapping a photo from the stoop, the assistant tagging the exact address, routing the ticket, and feeding back a status - freeing human agents for complex, high‑touch cases and turning routine reports into measurable civic wins (virtual assistants for municipal customer service and government efficiency).

Data rigs and policy memos suddenly become digestible: by pairing tried-and-true prompts for dataset exploration, cleaning, and statistical checks with report-summarization templates, Office of Administration teams can turn raw CSVs and long regulatory reports into tight, evidence‑based policy briefs that busy officials can act on.

Practical prompt recipes - from quick dataset summaries and outlier detection to stepwise data‑cleaning instructions and visualization code - come straight from playbooks like AnalyticsHacker's guide to AI prompts for data analysis and PromptLayer's templates for summarizing long reports, which even show how to compress a 50‑page report into a two‑paragraph executive summary (AnalyticsHacker AI prompts for data analysis examples, PromptLayer AI prompts for summarizing long reports quickly).

The payoff is concrete: clearer recommendations, faster turnarounds, and fewer late‑night spreadsheet scrambles - imagine an analyst spotting a neighborhood‑level service disparity from a heatmap before the next council briefing.

Task	Example prompt / output
Dataset exploration	Summarize key characteristics, missing values, and outliers - initial data patterns (AnalyticsHacker)
Report summarization	Create a one‑page executive summary for a 50‑page report - concise findings & recommendations (PromptLayer)
Data cleaning & code	Methods and Python/R snippets to handle missing values or create crosstabs (AnalyticsHacker / Analythical)

Carnegie Mellon's learning ecosystem offers Pennsylvania governments a practical pathway to workforce readiness through simulated, cohort-based and on‑demand training: the Heinz College's Public Interest Technology Certificate (PITC) bundles Data Management, Digital Innovation, and AI Leadership into a six‑month, cohort‑style program built for public‑sector leaders (Carnegie Mellon PITC executive education for government leaders), while campus resources - everything from Ansys‑backed simulation spaces to eLearning modules like AI‑Enabled Enterprise Architecture - translate classroom lessons into realistic scenario work (budget tradeoffs, tech procurement, or service‑delivery role plays) that agencies can reuse for onboarding and refreshers (Carnegie Mellon eLearning course list and simulations).

For cyber and operational readiness, the Federal Virtual Training Environment (FedVTE) supplies free, on‑demand cybersecurity and certification prep for government staff, making it simple for counties and city teams to layer technical drills onto leadership simulations (FedVTE online cybersecurity training for government staff).

The result is tangible: staff practice high‑stakes decisions in a safe sandbox - think simulated incident calls or customer‑service escalations - so real emergencies meet practiced, not panicked, responses.

“Public Interest Technologists are helping to shape the government of the future, and improve how the government engages with citizens.” - Chris Goranson

5. Redaction & PII Detection - PennDOT Document Preprocessing: For state transportation agencies handling accident reports, permit files and frequent FOIA releases, a dependable preprocessing workflow is non‑negotiable: start with clear redaction policies and staff training, then pair human review with automated PII detection so sensitive items are removed permanently and auditable logs show who redacted what and why.

Practical toolchains include AI‑powered redaction platforms and cloud-native PII APIs - Redactable's government guide outlines the legal triggers for redaction plus a six‑step playbook for secure, irreversible redaction and audit trails (Redactable government redaction best practices guide).

For file‑level automation, Azure's native document PII redaction shows how to send PDFs and DOCX into a pipeline that detects, catalogs and writes redacted outputs back to blob storage (Azure document PII redaction how-to and implementation guide), while AWS's SageMaker + Comprehend pattern demonstrates scalable redaction for tabular datasets (hundreds of thousands of cells can be redacted in minutes with exportable results) (AWS SageMaker Data Wrangler PII redaction for tabular data tutorial).

The practical payoff for PennDOT: fewer embarrassing leaks, a clear public record of why fields were removed, and the ability to publish transparency without exposing names, SSNs or account numbers - a FOIA packet that used to risk exposure should now leave only clean redaction marks and an incontrovertible audit trail.

Public notices are the bedrock of local transparency in Pennsylvania, but their dense legal wording - mortgage-foreclosure and sheriff‑sale listings routinely buried in Legal Notices - makes them hard for neighbors to act on; a City of Philadelphia “Public Notice Simplifier” could pull from the centralized Public Notice Database maintained by the Pennsylvania NewsMedia Association and convert a checklist‑style notice into plain language that answers

“what happened,” “what you must do,” and “who to call.”

For example, instead of wrestling with courtroom jargon in an Inquirer listing about a sheriff's sale or foreclosure that notes

“You have 20 days to defend,”

a summary would flag the deadline, translate consequences, and surface concrete resources like the Philly Tenant Hotline and Right to Counsel eligibility steps so a renter sees

“Call (267) 443‑2500 for free legal help”

and a link to applications.

By pairing accurate extraction from Legal Notices listings with trusted referral links to Community Legal Services and municipal Right to Counsel pages, the tool would turn a dry notice into an actionable civic prompt - so a resident can move from confusion to a clear next step in minutes, not hours.

Pennsylvania's Generative AI Governing Board has turned high‑level principles into practical readiness tools - checklists that make procurement, bias reviews, and staff training into repeatable steps rather than one-off decisions - so agencies can pilot smart assistants without exposing sensitive data or skipping human review; the state's resource page lays out this strategy, from employee‑centered guidance to required training and governance, while the Executive Order 2023‑19 formalizes the board's role in recommending procurement processes, assessing bias and security, and inviting expert and labor input to keep deployments accountable (Pennsylvania Generative AI resource page, Executive Order 2023‑19).

Templates and readiness assessments distilled from the board's mandates - confirmation of data classifications, required human‑in‑the‑loop checkpoints, disclosure prompts, and training signoffs - help agencies scale pilots like the year‑long ChatGPT Enterprise trial (175 employees) while documenting provenance and audit trails so benefits (the pilot reported roughly 95 minutes saved per employee per day) don't outpace safeguards (year‑long ChatGPT Enterprise pilot).

These checklists turn governance into operational muscle: a simple readiness form can be the difference between a safe, transparent rollout and a misstep that costs public trust.

Board Responsibility	Example Checklist Item
Recommend agency use	Bias & security review completed; aligns with core values
Procurement guidance	Problem‑based RFP language; accessibility and vendor fairness assessment
Training & feedback	Mandatory user training; channels for labor and public input
Expert engagement	Technical advisory consultations logged

“You have to treat (AI) almost like it's a summer intern, right? You have to double check its work.” - Cole Gessner

Philadelphia Parks & Rec can use a dedicated “Accessibility GPT” to turn dense program listings, permit notices, and event pages into podcast‑style audio summaries and synchronized transcripts so more residents can engage on their own terms: AI‑generated audio summaries capture key points in a conversational format rather than robotic readbacks (AI‑generated audio summaries for accessibility), while automated captioning, alt‑text suggestions and contrast checks help meet WCAG guidance and municipal needs (AI tools for captions, alt text, and WCAG support).

To be compliant, every audio‑only product needs a text alternative and synced transcripts should live on the same page - as the W3C explains - so a resident who can't access audio still gets full meaning and visual context (W3C guidance on transcripts and accessibility).

Built with human oversight and clear provenance, the GPT can prefill transcripts, flag needed human edits, and log versions so Parks & Rec meets the new DOJ accessibility requirements rolling into enforcement in 2026–27 while genuinely widening access for people with disabilities and busy families alike.

“This final rule marks the Justice Department's latest effort to ensure that no person is denied access to government services, programs, or activities because of a disability.” - Attorney General Merrick Garland

Simulation and bias‑testing scenarios are the safety rehearsal that turns a promising ChatGPT pilot into a dependable public tool: Pennsylvania teams should build structured red‑team scripts that probe weaknesses - fictional framing, subtle sidestepping, translation or “ignore prior instructions” tricks, and multi‑turn persuasion - to reveal where models might be coaxed into biased or unsafe outputs, then fix them before public use; practical primers on adversarial prompting and red‑teaming explain these techniques and the psychology attackers exploit (Appen adversarial prompting guide for testing AI models, red‑teaming playbooks for LLM adversarial prompts).

Tests should mix automated benchmarks with human reviewers and scenario‑based scripts - for example, a persistent “authority” role‑play that stretches a model across a dozen back‑and‑forth prompts - to catch gradual persuasion attacks that simple filters miss; Google's adversarial testing workflow shows how to choose diverse, edge‑case inputs and build reproducible datasets for mitigation (Google adversarial testing guide for generative AI).

The payoff is concrete: fewer hallucinations, demonstrable bias‑checks, and audit trails that protect trust and limit regulatory and reputational risk when conversational AI serves residents.

When Pennsylvania's Department of Health starts using AI to draft advisories, FAQs or media statements - especially as the Regulatory Agenda shows DOH rulemaking on communicable and noncommunicable disease reporting (proposed March 2025) - safeguards must be baked into every workflow: lawyers and communicators need to treat model outputs like draft text that can't displace attorney judgment, honoring confidentiality under Rule 1.6 and the duty of competence in Rule 1.1, supervising nonlawyer tools per Rule 5.3, and ensuring truthfulness and candor in public statements under Rules 4.1 and 3.3.

Practical controls include human‑in‑the‑loop signoffs, redaction checks for PHI, and clear provenance metadata so a misplaced sentence doesn't become a discipline case; early industry experience even shows drafting assistants change the role of human editors in communications teams (drafting-assistance examples).

For health agencies balancing speed and legal risk, the rulebook matters: the Pennsylvania Rules of Professional Conduct spell out confidentiality, supervision and disclosure duties (Rules of Professional Conduct), and the DOH regulatory docket flags why accuracy and recordkeeping are nonnegotiable for public‑facing health messages (DOH rulemaking agenda).

Safeguard	Relevant Rule / Guidance
Confidentiality & PHI checks	Rule 1.6 - Confidentiality
Supervision of AI & nonlawyer tools	Rule 5.3 - Responsibilities Regarding Nonlawyer Assistance
Accuracy, candor & public statements	Rules 4.1 & 3.3 - Truthfulness and Candor

Philadelphia's next sensible move is to match ambition with guardrails: start every pilot with the readiness assessments and governance checks Pennsylvania's AI usage guidelines call for - clear data management rules, prominent disclosure of AI‑generated content, and a short list of prohibited uses - so systems help residents without exposing sensitive records (Pennsylvania AI usage guidelines for state governments).

Procurement is the practical lever: build RFP clauses that require explainability, limited trade‑secret waivers, and vendor accountability so contractors can't hide consequential logic from auditors (Procurement path to AI governance for contract clauses).

Pair those rules with hands‑on staff training - prompt‑writing, verification and human‑in‑the‑loop workflows - to keep models honest and useful; practical courses like Nucamp's AI Essentials for Work bootcamp translate policy into day‑to‑day skills that municipal teams can use to run safe pilots and scale responsibly (Nucamp AI Essentials for Work bootcamp - registration and syllabus).

Next Step	Why it Matters	Resource
Readiness assessment	Ensures staff understand risks, data needs, and human‑in‑the‑loop checkpoints	Pennsylvania AI usage guidelines for state governments
Procurement clauses	Sets transparency, explainability, and auditability expectations for vendors	Procurement Path to AI Governance - procurement and contract levers
Workforce training	Builds prompt, verification, and compliance skills for everyday users	Nucamp AI Essentials for Work bootcamp - 15 weeks, early bird $3,582 (registration)

“The single most important ingredient in the recipe for success is transparency because transparency builds trust.” – Denise Morrison