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

Columbus government leaders are under practical pressure to adopt AI where it improves outcomes - speeding permit approvals, automating routine inquiries, and scaling public health messaging - while safeguarding equity, privacy, and explainability; the Government Innovation Showcase Ohio held May 13, 2025 at the Hilton Columbus Downtown made this explicit with tracks on Data, AI, and IT Modernization and a call to:

guide ethical AI implementation

for transparency and citizen feedback Government Innovation Showcase Ohio Columbus 2025 event details.

State CIOs also flag data quality, governance, and workforce reskilling as the three priorities that determine whether AI delivers cost savings or new risks - see the analysis by CGI on top trends for state and local government CGI: State CIO top trends for state and local government.

For municipal teams ready to build applied skills, a focused pathway like Nucamp's 15‑week AI Essentials for Work teaches prompt writing and practical AI tools that help staff act on these priorities - view the full syllabus for the AI Essentials for Work bootcamp Nucamp AI Essentials for Work syllabus (15‑week bootcamp).

Selection prioritized practical, Columbus-relevant AI work that shows measurable operational value, clear governance pathways, and feasibility for municipal pilots: projects citing documented cost or time savings, strong model management, and real-world deployment ranked highest.

Sources that shaped the shortlist include enterprise case evidence (Nationwide H2O.ai case study showing multi-million savings and large-scale model deployment) and sector frameworks for public-service impact, and state-level adoption insights about workforce readiness and user adoption barriers.

Each candidate was evaluated against four filters - local relevance to Ohio/Columbus operations, documented outcomes or reproducible workflows, alignment with trustworthy-AI practices for government, and ease of piloting with existing IT stacks - so recommendations map directly to Columbus priorities like permitting automation, caseworker decision support, and secure model governance; see the Nationwide H2O.ai case study and the Deloitte Government AI dossier for public services for the evidence and sector criteria that guided scoring.

Selection Criterion	Evidence Source
Documented operational value (cost/time)	H2O.ai Nationwide case study demonstrating cost and time savings
Public-sector applicability and governance	Deloitte Government AI dossier on AI governance for public services
Workforce adoption & pilotability	OhioX / Deloitte insights on adoption and change management

“H2O.ai provides us the power and flexibility we need to solve business problems with machine learning. We are able to do more with less and do it faster. Our results are proof of the power of AI in action. Working with H2O.ai platforms allows us to quickly provide stable, statistically unbiased models that we can trust in our production environment.” - Shannon Terry, Vice President, Predictive Analytics at Nationwide

H2O.ai turns model development into a practical “model factory” for Columbus by packaging Driverless AI's AutoML, feature engineering and interpretability into deployment‑ready artifacts that municipal teams can push to production: exportable Java/C++/Python scoring pipelines, Triton or H2O MLOps endpoints for real‑time scoring, and reusable features via a feature store that speed repeatable workflows for fraud detection, permitting triage, and benefits eligibility checks; reason codes and Shapley explanations surface per‑transaction signals so investigators prioritize the riskiest cases, while Nitro/Wave apps let business users interact with dashboards without new front‑end code.

For hands‑on entry points see the H2O Driverless AI AutoML quickstart and tutorials (H2O Driverless AI AutoML quickstart and tutorials) and the Driverless AI model deployment documentation for productionizing models with Triton and H2O MLOps (Driverless AI model deployment with Triton and H2O MLOps documentation), both of which make it feasible for Columbus IT to run governed pilots on cloud or on‑prem infrastructure.

“The ability to explain and trust the outcome of an AI-driven business decision is now a crucial aspect of the data science journey.”

OpenAI's enterprise offerings - especially ChatGPT Gov and ChatGPT Enterprise - give Ohio agencies a practical path to 24/7 multilingual citizen engagement and internal automation while keeping sensitive data inside controlled clouds: ChatGPT Gov can run in Azure Government and exposes GPT-4o capabilities, custom GPTs, and centralized admin controls (SSO, user/group management) so IT teams can enforce access and audit trails; see the ChatGPT Gov overview for government deployments ChatGPT Gov overview for government deployments.

When paired with an “AI concierge” approach local to Ohio - multichannel chat, SMS, voice, and kiosk - municipalities can cut routine staff time and surface accurate, actionable answers; pilots have shown major time savings (Commonwealth of Pennsylvania reduced routine task time by roughly 105 minutes per employee per day).

Balance is essential: practical guidance on hallucinations, privacy, and human review should guide rollout and governance AI for government public sector guidance, and Ohio programs exploring multichannel AI concierges offer deployment patterns that keep services accessible while protecting resident data AI concierges for local government services in Ohio.

“The introduction of ChatGPT Gov represents a pivotal moment for government agencies looking to modernize operations while maintaining strict security and compliance standards. AI-driven solutions like these can enhance efficiency, streamline administrative processes, and improve public service delivery. At Launch, we specialize in helping agencies integrate AI seamlessly, ensuring they maximize the benefits of these advanced technologies while adhering to regulatory requirements.” - Davood Ghods, MD, Government, Strategy & Solutions

Nationwide's “Actionable AI” guide shows a practical pattern Columbus agencies can reuse: turn dense technical records into short, actionable explanations using LLMs so frontline staff and residents get clear next steps instead of raw logs.

Two concrete Nationwide proofs-of-concept illustrate this - a P&C Claims Log Summary that lets an associate “trigger a GenAI model to review the claim history and provide a summary of the claims and any actions that have been taken to date,” and Nationwide Pet HealthZone, which uses generative AI to create personalized pet‑health information from claims data; both demonstrate how model-driven summarization and personalization make complex data usable in conversation and web help centers.

For municipal teams in Ohio, that same approach can simplify permitting rules, benefits eligibility language, or case notes into plain‑language guidance and FAQ snippets that speed resolution and reduce follow‑ups; see the Nationwide Actionable AI guide for insurer examples and Nucamp AI Essentials for Work registration for practical Columbus AI resources and local pilot guidance.

Use case	Nationwide example
Technical record summarization	Nationwide P&C Claims Log Summary proof of concept
Personalized risk guidance	Nationwide Pet HealthZone (generative AI personalization)

“Gen AI will change the way we work, helping to automate routine tasks and free employees up to do their best work. Embracing this tool now will set IAs and their businesses up for success.” - Jim Fowler, Nationwide Chief Technology Officer

H2O.ai's enterprise playbook - visible in its case studies that include a PayPal fraud‑fighting deployment - shows how GenAI can pair production ML with developer‑facing code assistance to accelerate legacy migration: combine h2oGPT and LLM Studio to retrieve and summarize large policy and log corpora (RAG), then generate vetted code stubs, unit tests, and API wrappers so engineers who maintain Columbus's permitting and benefits systems spend hours validating outputs instead of days rewriting stored procedures by hand; practical outcomes include faster turnaround on security reviews and clearer traceability from natural‑language rule to executable scoring logic.

For municipalities in Ohio this pattern matters because it reduces the upfront labor barrier for modernizing legacy stacks while keeping model context and explainability intact - see H2O.ai's collection of customer examples and the PayPal entry on their case studies page, and the H2O World discussion on code generation and RAG workflows for technical teams.

Native integrations like H2O's GenAI bundles for Snowflake also let jurisdictions keep data and models inside governed cloud accounts during migration pilots.

H2O capability	Columbus use
H2O.ai case studies (PayPal fraud example)	Model‑backed code assists to speed legacy rule conversion and testing
H2O World: code generation and RAG workflows video / H2O Snowflake GenAI bundles press release	Fine‑tune LLMs on local docs and run migrations inside governed data clouds

"This is a big step in making AI accessible to everyone." - Sri Ambati, CEO and Founder, H2O.ai

Deloitte's practical playbook for Columbus leaders reframes generative AI from a novelty into a governance priority: treat GenAI as a new category of enterprise risk that shortens timelines for harm and demands board‑level attention, clear ownership, and updated fraud controls - Deloitte warns that GenAI‑enabled fraud could surge unless detection and approvals are redesigned, and recommends five concrete board actions from building AI literacy to creating dedicated oversight subcommittees.

For municipal IT and legal teams in Ohio, that means standing up a Trustworthy AI approach (policy, model risk management, and role‑based training) before scaling pilots so permitting, benefits, and casework automations stay auditable and privacy‑safe; see Deloitte's framework for assessing four emerging GenAI risk categories and the board checklist for governance and risk management.

Deloitte framework for managing generative AI risks and Deloitte five board actions for generative AI governance and risk management offer stepwise controls Columbus can map to existing compliance, procurement, and fraud‑detection workflows so pilots deliver measurable value without opening new legal or reputational exposures.

Board action	Why it matters
Build AI literacy	Enables informed oversight and risk questions
Promote C‑suite AI fluency	Aligns executive decisions with risk appetite
Recruit AI experience to boards	Provides operational oversight for deployment
Stand up dedicated governance	Keeps policy and audits current as tech evolves
Embed model risk management	Mitigates hallucinations, bias, and fraud vectors

“Generative AI amplifies the risks associated with AI, and it shortens the timeline for enacting essential steps and strategies that can enable AI risk mitigation.”

Law librarians and municipal legal teams in Columbus can use the Caselaw Access Project to turn a once‑buried archive into practical, public-facing tools - searchable opinion indexes, FOIA-ready summaries, and training datasets for custom GPTs that draft plain‑language guidance for residents - because CAP put decades of bound reporters online and exposed metadata via a browsable API at api.case.law; for developers the API is friendly and scriptable, but note the dataset's scanning window (print reporters through 2018) and practical rate limits that affect automation design (Harvard Law School Caselaw Access Project API launch and bulk data service, Using the Caselaw Access Project API and its limits - PythonForLaw guide).

Practical payoff for Columbus: embed authoritative citations into permitting and code‑enforcement FAQs, let law librarians run bulk extracts for public portals, and chain CAP with more current scraping sources to keep local legal help current - doing so leverages a dataset whose scale makes targeted legal access projects feasible for city budgets and university partners.

CAP snapshot	Value
Volumes scanned	39,796
Pages digitized	≈38.6 million
Individual cases	≈6.5 million
Coverage	~334 years of published U.S. case law (print reporters)

“Libraries were founded as an engine for the democratization of knowledge, and the digitization of Harvard Law School's collection of U.S. case law is a tremendous step forward in making legal information open and easily accessible to the public.” - Jonathan Zittrain

Summarizer Pro bundles Custom GPTs with meeting‑prompt worksheets and transcript integrations so Columbus teams can turn long calls into governance‑ready outputs: use prompt templates and one‑click summaries to extract attendees, decisions, and named action items - Tactiq's guide and examples show how prompts and auto‑highlights generate top‑5 highlights, tasks, and follow‑ups - and apply the same templates to produce concise public‑records or FOIA‑friendly executive summaries; tools like Claap add built‑in summary builders and templates that streamline moving those outputs into minutes, CRM updates, or case folders.

Practical impact: an 8,000‑word meeting transcript that once took hours to parse can be compressed to a 73‑word, three‑sentence executive summary in seconds, reclaiming staff time from meetings (people average ~31 hours/month in meetings per Atlassian studies cited in meeting‑prompt guides).

For municipal deployments, host Custom GPTs on vetted clouds and verify FedRAMP status to align summaries and redaction workflows with government security and procurement requirements (Tactiq guide to ChatGPT meeting prompts and templates, Claap best prompts and meeting‑notes templates, FedRAMP Marketplace for authorized cloud services).

"Flippin' fantastic. Best meeting companion I've ever used. Nothing else comes even close." - Steve Coppola

Socratic Quizbot adapts the Socratic method into a lightweight, scalable training tool municipal HR and legal teams in Columbus can use to raise engagement and assess understanding without heavy grading workloads: short, ten‑minute conversational assessments - run at the start of sessions or as micro‑tools tied to assigned readings - ask guided follow‑ups, capture transcripts to an LMS, and return real‑time feedback so staff practice applying policies instead of just memorizing rules; the approach has shown improved preparation consistency, lower performance anxiety, and faster instructor turnaround by replacing long essays with a simple 0–5 rubric and automated transcripts.

Practical implementation paths range from no‑code Custom GPTs in ChatGPT Teams for quick pilots to local, open‑source installs for stricter data control, and adaptive questioning plus persistent transcripts create an auditable learning trail useful for compliance training and FOIA‑ready documentation.

For a primer on classroom Socratic facilitation see the ELI guide to Socratic Method training (ELI, Inc.) and for an implementation writeup and open resources, review the Socratic Quizbot implementation and research (DonaldPrayLibrary).

Feature	Practical benefit for Columbus teams
Ten‑minute conversational assessments	Scales individual attention and reduces grading delay
Adaptive Socratic questioning	Assesses depth, not just recall
No‑code and code deployment paths	Quick pilot via Custom GPTs or privacy‑focused local install

Vibe‑coding showcases a practical, low‑risk way for Columbus departments to upskill staff: Rebecca Fordon's “Boolean minigame” - built in about 30 minutes using the Canvas feature in Google Gemini 2.5 - turns dry query syntax into a short, interactive exercise with real‑time feedback that helps learners internalize Boolean logic used in legal research, permitting searches, and records discovery; the proof‑of‑concept is playable at Play the Google Gemini Boolean Minigame (Rebecca Fordon) and is documented with prompts and teaching notes on the AI Law Librarians site (AI Law Librarians: Vibe‑Coding Boolean Minigame lesson and prompts), while campus guides point to vibe‑coding as a repeatable pattern for micro‑tools (UCSD Library: Vibe‑Coding examples and prompt guidance).

So what: a 30‑minute prototype can become a reusable micro‑tool for onboarding new hires or refreshing seasonal staff, delivering immediate practice and measurable confidence gains without heavy IT investment.

Attribute	Detail
Prototype time	~30 minutes
Platform	Google Gemini Canvas (Gemini 2.5)
Primary skill	Boolean search / query building
Demo	Google Gemini Boolean Minigame demo link

Law Capital (Jenny Wondracek) packages practical, legally-aware back‑office templates that let Columbus agencies automate routine HR and legal workflows - onboarding, document generation, timekeeping, and FOIA‑ready outputs - so clerks and HR staff reclaim hours for public service instead of paperwork; for example, Zenphi's Employee Onboarding template automates welcome emails, Google Workspace provisioning, digital signing, and IT triggers so a new hire is productive on day one (Zenphi HR workflow automation templates for employee onboarding), while law‑office playbooks and DMS recommendations show how document management, automated billing, and virtual reception cut non‑billable admin and boost responsiveness (law firm admin automation tools and DMS recommendations); pair those flows with targeted ChatGPT HR prompts to generate inclusive job descriptions, outreach, and internal comms from a vetted prompt library (100+ ChatGPT HR prompts for inclusive hiring and internal communications), and suddenly the 57% of HR time that Deloitte/AIHR flags as administrative becomes reducible to a handful of governed automation flows - so Columbus can speed permitting and benefit decisions without expanding headcount.

Template	Municipal benefit
Employee Onboarding	Auto‑provision accounts, send welcome packet, schedule IT/meetings (faster day‑one productivity)
Leave Request	Automated approvals, manager lookup, and leave logging (reduces email back‑and‑forth)
Document Generation	Generate FOIA‑friendly PDFs, contracts, and offer letters with digital signing and archive

Columbus should start with governed, measurable pilots that align with Ohio's statewide AI policy - set clear data governance, procurement checkpoints, and human‑in‑the‑loop reviews - then link those pilots to concrete staff training so tools move from experiment to everyday service: use the state's multi‑agency oversight model (see the Ohio AI policy announcement in Columbus Ohio AI policy announcement in Columbus) and borrow Idaho's phased playbook for pilots-to-scale Idaho AI phased pilot guidance and rollout examples.

Pair a small set of high‑value pilots - multichannel citizen concierge for permitting, and model‑backed summarizers for FOIA/meeting records - with a 15‑week staff pathway to build prompt and model literacy; practical training like Nucamp's AI Essentials for Work turns governance into operational capacity and shortens the time from pilot to repeatable savings Nucamp AI Essentials for Work syllabus (15‑week course).

The payoff is straightforward: auditable pilots that reclaim staff hours while keeping resident data protected and explainable.

Attribute	AI Essentials for Work
Length	15 Weeks
Focus	Prompt writing, applied AI tools, workplace use cases
Cost (early bird)	$3,582
Registration	Register for Nucamp AI Essentials for Work (registration)

“While we're measuring and mitigating risks, we're making sure that we're not getting in the way of it being launched. We want to - we really want to unleash this to the workforce.”