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

North Dakota's early, statewide push to train government employees in generative AI - about 67 state workers completed a Microsoft TechSpark / gener8tor cohort - has produced concrete pilots such as the Dakota chatbot and three “shovel‑ready” ideas (a citizen-facing unified portal, natural‑language statute search, and legislative tracking), demonstrating how AI can free staff time and simplify access to services for Fargo residents; with Chief Data Officer Kim Weis and NDIT building policy and governance, these programs move AI from experimentation to practical productivity gains for local government - read the InForum report on the training, Fargo Inc.'s account of the gener8tor cohort, and explore worker-focused training like the AI Essentials for Work bootcamp for practical prompt- and tool-based skills.

Bootcamp	Length	Early-bird Cost	Syllabus
AI Essentials for Work	15 Weeks	$3,582	AI Essentials for Work bootcamp syllabus and details

“What's the support that our agencies will need around [AI] because they're asking a lot of questions, really excited about the potential of AI,” Weis said.

Selection of the top prompts and use cases began with a structured review of North Dakota's gener8tor–Microsoft TechSpark cohort outcomes and subsequent pilots: review sessions cataloged 10–11 capstone ideas from 12 cross‑agency teams, then filtered for citizen impact, technical feasibility, and governance readiness - yielding three “shovel‑ready” projects (a unified citizen portal, natural‑language statute search, and legislative tracker) that matched pilot feedback from the Dakota chatbot and the state's governance council; criteria weighted practical metrics (time‑saved estimates, integration with Microsoft 365 Copilot capabilities, and staff upskilling), ethical guardrails from weekly Lunch‑and‑Learns, and local scalability via TechSpark partnerships, producing prompts focused on natural‑language search, transcription + semantic search for legislative videos, and automated form completion that can be piloted with existing state resources and Microsoft TechSpark support.

Metric	Value
Cohort participants	67
Hours invested	938
LinkedIn courses completed	335
Teams formed	12
Capstone ideas	10–11
Shovel‑ready pilots	3

“We talked about the evolution of AI, the trends that they are seeing or anticipating in government, and responsible use of AI.” - Molly Herrington

The citizen-facing consolidated portal - a natural‑language unified search for State of North Dakota services - concentrates disparate resources (benefits, permits, statutes, and agency contact info) behind one conversational query so Fargo residents can find answers without juggling multiple websites or waiting in phone queues, freeing staff to handle complex cases; this approach mirrors how states have deployed chatbots and citizen portals to handle health, benefits, taxes, and inquiries and aligns with NIST‑informed governance and procurement expectations described by the National Conference of State Legislatures in their report Artificial Intelligence in Government: The Federal and State Landscape.

Successful pilots must follow North Dakota's operational safeguards - data classification, approved vendor use, and account management - as laid out by the North Dakota Information Technology department in Artificial Intelligence Guidelines | North Dakota Information Technology, and pair prompt design with documented risk controls and mitigation guidance such as practical steps for bias, security, and vendor lock‑in in guidance for mitigating AI risks in government deployments, so the portal becomes a governed, measurable channel that reduces routine casework and shortens resident search time into a single, auditable interaction.

Metric	Value
States using chatbots for citizen services	35+
State technology directors reporting chatbot use	50%

A North Dakota–focused natural‑language statute search functions as a legal reference assistant that indexes state law, administrative rules, and agency advisories so Fargo staff, local attorneys, and providers can ask plain‑English questions and get cited answers with links to source text; for example, the tool would surface ND HHS provider updates - like the MMIS security enhancements posted 7‑31‑2025 and the July 1, 2025 fee‑schedule conversion factor of $36.8442 - or highlight service‑authorization changes and new preferred drugs (Steqeyma) without manual review ND HHS Medicaid provider updates (MMIS & fee-schedule notices).

Built with an auditable retrieval layer and citation-first prompts, the assistant shortens staff research time and helps providers spot policy shifts that trigger enrollment or prior‑authorization actions; pair the search with an implementation checklist and contacts for pilot governance to keep results current and defensible Fargo AI implementation checklist and pilot governance guide.

“PREVENTION IS BETTER THAN CURE” - Desiderius Erasmus

A legislative data portal that combines accurate transcription of committee hearings with semantic search turns hours of unstructured audio, video, and bill text into an auditable, citation‑first research tool for the North Dakota Legislature and Fargo staff - enabling fast retrieval of spoken votes, amendment intent, and precedent without manual sifting.

Build the pipeline using proven research tools for transcription and full‑text indexing (see Ohio State University A‑Z Databases transcription and search engines Ohio State University A‑Z Databases: transcription & search engines), pair the index with tuned semantic models for entity recognition and relevance ranking (examples of semantic‑search model work on DagsHub DagsHub semantic search model parameters and configuration), and follow a pilot checklist and governance playbook so transcripts, access controls, and vendor choices meet North Dakota's audit and privacy expectations (Fargo AI implementation checklist and governance playbook).

The result: a searchable legislative data hub that makes intent and record‑keeping instantly discoverable and defensible for staff, reporters, and the public.

NDIT's Cybersecurity Operations Center pairs machine‑learning detection with playbook automation so Fargo and statewide IT teams can move from firefighting to prioritized response: after adopting a platform approach (Cortex XDR, XSOAR, XSIAM, Xpanse and Unit 42 services) the state saw open alerts plummet from ~16,000 to roughly 50 and now automates about 60% of incidents, shrinking weeks of hunting into minutes and freeing analyst time equivalent to 8–10 full‑time staff - concrete gains that support whole‑of‑government readiness and faster recovery for critical services.

These operational results sit alongside NDIT's statewide telemetry - continuous monitoring of 250,000+ devices, ingestion of 5 TB/day, and 572,945,827 threats prevented in 2023–24 - underscoring why ML‑driven SOC automation is not a luxury but a force multiplier for Fargo's public sector (Palo Alto Networks case study on NDIT SOC modernization, NDIT Major Accomplishments 2023–2024).

Pilot prompts should prioritize high‑confidence, auditable actions (isolate endpoint, escalate to IR, enrich IOC) and include human‑in‑the‑loop checkpoints to align automation with state AI/ML policy and incident‑response playbooks.

Metric	Value
Threats prevented (FY2023–24)	572,945,827
Endpoints monitored	250,000+
Open alerts before → after	16,000 → ~50 (99.6% decrease)
Incidents automated	60%
Incidents resolved (2023–24)	53,159

“The Cortex portfolio has really helped our SOC mature. With so many threats coming in, having that toolset has really been a big benefit for us.” - Michael Gregg, CISO, NDIT

West Fargo's two‑year purchase of Placer.ai gives city leaders an evidence‑driven lens into who visits events and businesses by using anonymized, aggregated cellphone data and tools like geofencing for trade‑area analysis - helping answer the practical question

did tax incentives pay off?

(the Junkyard Brewing incentives totalled about $690,000, including a $249,470 five‑year PILOT), and the contract itself was $20,000 in year one and $22,000 in year two paid from economic development sales tax; Placer.ai's platform, already used by more than 1,500 cities and 11 agencies in North Dakota (including Fargo's Downtown Community Partnership and the Fargo Park District), can compare local storefronts to regional anchors, reveal missing industry clusters, support site selection, and even strengthen grant bids (Grand Forks used similar stats to win a $100,000 grant).

For implementation guidance and risk controls that keep citizen privacy and vendor governance front‑of‑mind, see the InForum coverage of the West Fargo decision and Nucamp's practical guidance on mitigating AI risks in government deployments (AI Essentials for Work syllabus).

Metric	Value
Contract length	2 years
Cost (Year 1 → Year 2)	$20,000 → $22,000
ND agencies using Placer.ai	11 (incl. Fargo DCP, Fargo Park District)
Junkyard Brewing taxpayer incentives	≈ $690,000 (PILOT $249,470 + ≈ $440,000 incentives)
Approval vote	4–1

GovTribe's AI prompts streamline North Dakota contracting by turning tedious discovery and competitive research into fast, repeatable actions - examples include “Find open federal contract opportunities for [specific service or product],” automated searches scoped to Fargo or statewide suppliers, and teaming‑partner suggestions that surface compatible primes and likely bidders; built‑in capabilities like intelligent summaries, saved searches, and buyer/persona lookups reduce time spent parsing SAM.gov notices and RFPs, so small GovCon teams can triage pursuits and focus capture efforts where they matter most - answering complex business questions in minutes rather than hours.

For practical playbooks and prompt examples, see GovTribe's 10 AI prompts for contractors and the Federal Contract Opportunities user guide that explains AI Insights and opportunity pages for real‑time alerts and personas.

Sample Prompt	Use Case	GovTribe Feature
Find open federal contract opportunities for [service]	Opportunity discovery scoped to ND/Fargo	GovTribe AI prompts for government contractors
Identify key decision-makers for contracts in [agency]	Targeted outreach and relationship building	GovTribe Federal Contract Opportunities user guide (Personas & AI Insights)
Analyze opportunity and suggest teaming partners	Rapid partner shortlisting for capture	Teaming Partners / Likely Bidders

“We've developed complex prompts based on our team's extensive knowledge of government contracting, enabling customers to answer critical business questions in minutes instead of hours.”

Document automation and digitization for benefits and social services - modeled on UND/EERC's applied, evaluation‑driven approach - packages OCR, conversational intake, rule‑based eligibility checks, and an auditable retrieval layer so Fargo caseworkers spend less time on paperwork and more on complex approvals; pairing those workflows with evidence‑tier monitoring (so program changes feed back into measurable outcomes) follows the same discipline used in intervention research catalogs such as the Institute of Education Sciences' intervention reports and practice guides Institute of Education Sciences intervention reports and practice guides.

Implementation should align with practical governance and risk controls described in local playbooks - use the Fargo AI implementation checklist and pilot governance guide to set audit trails, vendor controls, and human‑in‑the‑loop checkpoints so automated document flows remain transparent and defensible Fargo AI implementation checklist and pilot governance guide for government AI use in Fargo; the concrete payoff: a single, auditable intake record that surfaces program eligibility exceptions to staff instead of burying them in stacks of PDFs, preserving case history and evidence for auditing and continuous improvement.

Program (example)	Focus	Evidence Tier
Good Behavior Game	Social, emotional, behavioral interventions	Tier 1
Pre‑K Mathematics	Early math curriculum	Tier 1
ITSS (Intelligent Tutoring for Structure Strategy)	Adolescent literacy, web‑based tutoring	Tier 2

Public-facing chat assistants for Fargo - designed with a career‑essentials, task‑oriented UX in mind - answer routine citizen questions (appointments, permit status, benefits eligibility) 24/7, shorten hold times, and free staff to handle complex cases; implement them by starting small with FAQ pilots, building a curated knowledge base, and wiring the bot into back‑end systems with human‑in‑the‑loop escalation and role‑based access to preserve auditability and privacy, following practical operational advice from StateTech on contact-center modernization (StateTech 7 best practices for public sector contact centers) and government‑grade deployment guidance that emphasizes private deployment, encryption, and compliance (Government chatbot deployment and security guide); the immediate payoff for North Dakota agencies is measurable - reduced routine caseloads and faster citizen outcomes - while governance controls and continuous analytics ensure answers remain accurate, defensible, and aligned with NDIT policy.

Deploying predictive analytics for emergency services in Fargo starts with small, governed pilots that tie demand‑forecasting models to dispatch and staffing workflows while preserving auditability and privacy; pair scenario‑based prompts (predict call volumes by hour, flag probable multi‑unit incidents, suggest staging locations) with the state's practical risk controls - see guidance on mitigating AI risks: bias, security, and vendor lock‑in - and embed human‑in‑the‑loop checkpoints so controllers verify recommendations before redeploying crews.

Include workforce transition plans that reskill dispatch clerks and compliance roles as workflows change (adapting at‑risk government jobs in Fargo), and use the Fargo implementation checklist and pilot contacts to start: the playbook lists practical next steps and an operational contact (aiquestions@nd.gov) to align pilots with statewide governance and procurement expectations - so the payoff is measurable: faster, data‑driven staging decisions that keep human judgment front and center.

Data‑center siting in North Dakota now sits at the intersection of zoning, utility planning, and legislative action, so Fargo leaders should use targeted AI prompts that flag local permit conflicts, simulate grid impacts, and estimate ratepayer effects before approvals: for example, ask a model to “compare projected transmission congestion and monthly bill impacts if a 100–200 MW data center locates in [county], using MDU/Co‑op interconnection patterns and recent Atlas/Applied Digital case studies,” because data centers' loads can rival “small cities such as the Bismarck‑Mandan area” and, in one instance, added roughly $7.40/month to MDU customer bills - concrete signals that early siting analysis matters (see the North Dakota Monitor coverage of accelerating AI demand and InForum's legislative reporting).

Build prompts for a zoning checklist (noise, decommissioning, water, workforce housing), a stakeholder‑engagement planner (local government, PSC, co‑ops), and a permit‑consistency detector tied to state funding rules so municipalities avoid losing infrastructure grants under bills like Senate Bill 2208 or repeat grid surprises discussed at PSC forums.

Policy Item	Focus	Status/Concern
House Bill 1579	State siting for large power users (data centers)	Converted to study; industry pushed back
Senate Bill 2208	Withhold state infrastructure funds for conflicting local rules	Recommended not to pass (committee vote)
PSC conferences	Grid impacts, siting dialogue	PSC has limited siting authority; convenes stakeholders

“We end up being the ones who mop up the mess when things happen without any regulation.” - Randy Christmann, PSC Chair

Next steps for Fargo leaders and local developers: convert shovel‑ready ideas into small, governed pilots that pair the Dakota chatbot lessons with North Dakota's operational guardrails - start by submitting an Initiative Intake Request through NDIT's Self‑Service Portal and routing questions to aiquestions@nd.gov so projects follow the state's North Dakota Artificial Intelligence Guidelines (data classification, enterprise accounts, human‑in‑the‑loop checkpoints); prioritize three near‑term pilots (a citizen unified search, a natural‑language statute assistant, and a legislative transcription + semantic search) with measurable outcomes (time‑saved, routine caseload reduction, and audit trails) and clear GRC review to avoid vendor lock‑in or data exposure.

Pair pilots with workforce skilling - replicate the TechSpark cohort momentum that trained ~67 state staff and produced shovel‑ready ideas - by enrolling operational teams in short, practical courses like Nucamp's AI Essentials for Work syllabus and course overview and Microsoft/LinkedIn career modules so prompt design and prompt‑testing live with staff who will use the tools.

Use the InForum and gener8tor/Microsoft outcomes as a roadmap for cross‑agency governance and success metrics, and require vendor contracts to include citation‑first retrieval, logging, and periodic QA so pilots remain auditable and ready to scale across Fargo and Cass County when results prove policy‑compliant and citizen‑facing benefits are clear - see the InForum report on North Dakota AI training outcomes and workforce reskilling.

Program	Length	Early‑bird Cost	Register
AI Essentials for Work	15 Weeks	$3,582	Register for Nucamp AI Essentials for Work (15‑week program)

“What's the support that our agencies will need around [AI] because they're asking a lot of questions, really excited about the potential of AI.” - Kim Weis