The Complete Guide to Using AI in the Government Industry in Fort Wayne in 2025

Fort Wayne agencies must navigate a new Indiana playbook for responsible AI: the Office of the Chief Data Officer now publishes an AI Readiness Assessment Methodology (published June 27, 2025) and sets a policy “floor” that requires maturity assessments before most projects, so local teams need clear documentation and repeatable controls - see the Indiana Office of the Chief Data Officer AI policies for required steps and timelines (Indiana Office of the Chief Data Officer AI policies).

At the same time federal guidance on AI cybersecurity is arriving from NIST, raising the bar for threat modeling and model protection that municipal systems must adopt (NIST AI cybersecurity guidance for federal agencies).

Practical upskilling matters: Fort Wayne can reduce deployment delays by training cross-functional staff in applied AI skills such as the 15-week AI Essentials for Work course to close the gap between policy and practice (Nucamp AI Essentials for Work syllabus - 15-week practical workplace AI course).

“A lot of [agencies] followed afterwards, and there was a lot of risk associated with that. A lot of work went into making sure that … could be mitigated, so we would avoid some of the fears [of AI].” - Zach Whitman

The dominant new AI technologies in 2025 combine AIOps-driven automation with emergent agentic and multimodal systems, and each has direct, practical value for Fort Wayne agencies: AIOps platforms now deliver real-time analytics, automated anomaly detection and incident remediation across hybrid cloud stacks - meaning a compromised node can be isolated and prebuilt remediation triggered automatically, turning hours of manual triage into minutes and cutting downtime for critical city services (AIOps real-time security and automation trends for 2025); agentic AI can autonomously plan and execute multi-step tasks such as logistics rerouting or casework prioritization, while multimodal and generative AI make it feasible to combine text, images and audio for richer, faster decisions in public health, permitting more accurate record review and citizen communications (Agentic, multimodal, and generative AI trends for 2025).

Locally, pilots like a public-records document triage tool show how GenAI and multimodal workflows speed redaction and reduce legal risk - so Fort Wayne can both protect privacy and reallocate staff to higher‑value services (Fort Wayne public-records AI document triage use case).

By mid‑2025 the generalist ChatGPT ecosystem remains the single most popular public-facing AI assistant - First Page Sage reports ChatGPT with roughly a 60.4% AI search market share (and other industry trackers put ChatGPT use well ahead of rivals) - and that market concentration matters for Fort Wayne agencies because it shapes integrations, vendor support, and user expectations; practical uses include rapid drafting of citizen communications, summarizing case files for managers, and feeding multimodal triage workflows that speed public‑records redaction while reducing legal risk (see a Fort Wayne public‑records document triage use case).

For agencies that must balance scale with security, pairing ChatGPT-powered public interfaces with Azure/Microsoft Copilot solutions (which Microsoft documents as already accelerating case processing and citizen services in government pilots) offers a path to combine broad user familiarity with enterprise controls and Copilot‑native workflows.

The concrete takeaway: prioritize pilots that test ChatGPT‑centered user journeys (API access, clear data‑handling rules, and a redaction triage pilot) so Fort Wayne can deliver faster, more consistent responses to residents while retaining the governance controls required by state and federal guidance (First Page Sage generative AI chatbot market share report, Microsoft Copilot government use cases blog, Fort Wayne public‑records AI triage example and coding bootcamp Fort Wayne).

“I'm very busy, and it makes my life easier…”

Fort Wayne agencies must follow Indiana's enterprise AI policy: submit an AI Readiness Assessment Questionnaire as soon as any AI system is identified, obtain a State AI Policy Exception from the Chief Privacy Officer, and provide annual or post‑change follow‑up reports - submissions are triaged and reviewed by the MPH AI Review Team and OCDO using the NIST AI Risk Management Framework, and the policy also requires a “just‑in‑time” (JIT) notice to users at the point of interaction; critically, the Indiana Office of Technology will not approve Software Authorization requests for systems with AI without either an AI Policy Exception or an Out of Scope Affirmation, so naming your Agency Privacy Officer (APO) and filing early prevents procurement delays and audit risk (contact ResponsibleData@mph.in.gov).

See the State of Indiana AI Policy and Guidance for required forms and processes via the State of Indiana AI Policy and Guidance documentation at https://www.in.gov/mph/AI/, and consult the OCDO policies page for the AI Readiness Assessment Methodology and supporting standards on the OCDO AI Readiness Assessment Methodology page at https://www.in.gov/mph/cdo/policies/.

Independent coverage summarizes the policy's goal to balance innovation with data and ethical safeguards in this CDO Magazine summary of Indiana's AI policy at https://www.cdomagazine.tech/aiml/indiana-introduces-new-policy-for-ai-projects.

“We worked with DWD and their vendor to train a model on workforce data and education data, and then separated the model from the underlying data and handed the model itself to the DWD for use in its app.”

Start small and practical: pick a single, high‑volume pain point - public records redaction is a common one - and run a short, measurable pilot using a public records redaction triage tool to prove value quickly (public records redaction triage tool) ; assemble a cross‑functional team (IT, legal, records, and a service‑line manager), define success metrics (turnaround time, error rate, and legal exceptions), and limit initial scope to a single department.

While the pilot runs, formalize a workforce plan that leverages local partnerships - use AI job‑matching pilots with Ivy Tech to recruit or reskill staff and capture demonstrated wage gains in Fort Wayne (AI job‑matching pilot program with Ivy Tech for workforce reskilling in Fort Wayne).

Finally, convert freed capacity into higher‑value roles by training customer‑facing staff into case management, a proven growth path that preserves service quality and career mobility (case management career pathway for government service representatives); iterate, document decisions, and expand only after the pilot meets the predefined metrics.

speeds redaction and reduces legal risk

Fort Wayne agencies must treat the AI Readiness Assessment as a compact dossier: submit the AI Readiness Assessment Questionnaire as soon as any AI system is identified, document a clear risk classification (high/moderate/low), and include an inventory of data sources and lineage, model documentation (training data, validation results and known limitations), vendor contracts and SLAs, and explicit redaction and escalation workflows so reviewers can reproduce decisions - pilots that capture turnaround time, error rate and the exact triggers for manual review make approvals faster and reduce legal exposure (see the Fort Wayne public‑records document triage tool for documenting redaction controls: Fort Wayne public-records document triage tool and redaction controls).

Timelines matter: name an Agency Privacy Officer early, file for a State AI Policy Exception or Out‑of‑Scope affirmation before procurement to avoid authorization delays, and plan annual or post‑change follow‑ups; include a workforce plan that links pilot outcomes to reskilling pathways (use local partnerships such as the Ivy Tech job‑matching pilot program: Ivy Tech job-matching pilots for reskilling Fort Wayne government staff) and a concrete redeployment pathway for service staff into higher‑value roles like case management (see case management role transition example: case management redeployment and retraining guidance); a single, well‑documented pilot file often shortens review cycles and prevents procurement stalls, making the difference between a stalled project and an approved rollout.

Mitigating legal, privacy and procurement risk starts before code is signed: require vendors to show how a public‑records document triage tool will “speed redaction and reduce legal risk,” include clear data‑separation and export clauses so Fort Wayne can audit or run a model without exposing raw records, and insert SLAs for accuracy, turnaround time and incident response to prevent service‑disrupting surprises - these concrete contract terms shorten review cycles and limit liability.

Negotiate audit rights, breach notification timelines and a rights‑to‑remediation clause that mandates fixes and detailed change logs; when possible, insist on a model‑only delivery or escrow arrangement (separating the model from underlying data is a proven control in government pilots).

Protect the workforce by negotiating vendor support for reskilling and local hiring commitments that link freed capacity to retraining pipelines - build on existing initiatives like the AI job‑matching pilots with Ivy Tech and fund transitions into higher‑value roles such as case management to preserve jobs and capture measurable wage gains (public‑records document triage tool for Fort Wayne government, AI job‑matching pilots with Ivy Tech in Fort Wayne, case management career pathway in Fort Wayne government).

Organize AI operations in Fort Wayne around a tight, repeatable workflow that maps directly to Indiana's approval gates: form a cross‑functional core team (IT/security, legal/privacy, records management, and a service‑line manager), name an Agency Privacy Officer (APO) early, and treat the AI Readiness Assessment as the project's living spec so reviewers can triage risk and approve quickly; the State's process requires a Readiness Assessment submission to the MPH/OCDO before procurement, and IOT will block Software Authorization for systems with AI unless a Policy Exception or Out‑of‑Scope Affirmation is in place, so early APO engagement prevents procurement stalls (State of Indiana AI Policy and Guidance (MPH/OCDO)).

Build two parallel workflows: a rapid pilot lane (limited scope, measurable KPIs, manual‑review triggers) to prove value - examples include a public‑records document triage pilot that speeds redaction - and a compliance lane that collects model docs, data lineage, contracts and JIT notices for MPH review; low‑ and moderate‑risk submissions are often expedited while high‑risk systems receive full review, so design approval artifacts to demonstrate mitigations up front and negotiate vendor clauses that separate models from raw data to simplify audits and approvals (public records document triage tool for Fort Wayne government).

The so‑what: naming the APO and filing the Readiness Assessment before procurement is the single operational move most likely to turn a stalled project into an approved deployment.

“It is wonderful and it is scary.” - Rep. Matt Lehman

Fort Wayne agencies should treat workforce development as a paired investment: run a short redaction pilot to free records staff for higher‑value roles, then use local reskilling pipelines and market data to staff them - examples include a public‑records document triage tool that “speeds redaction and reduces legal risk” and creates predictable capacity for retraining (Fort Wayne public-records document triage tool use case and AI prompts), and AI job‑matching pilots that partner with Ivy Tech to place and upskill displaced workers while lifting local wages (Ivy Tech AI job-matching and reskilling pilot details).

To budget and set competitive pay for new case‑management roles, use regional compensation benchmarks - Western Management Group's COMPBASE survey offers single‑metro reports (single geographic area reports start at $1,800) so agencies can plan realistic salary bands and reduce turnover risk (COMPBASE® USA Compensation Survey - Summer 2025).

The so‑what: pairing a fast, measurable pilot (redaction → capacity) with local training pipelines and market data turns automation savings into retained, higher‑skilled jobs instead of layoffs.

Western Management Group invites you to participate in the Summer 2025 edition of CompBase® USA.

Practical checklist: before buying or launching any AI, name your Agency Privacy Officer, submit the State AI Readiness Assessment Questionnaire to the MPH/OCDO, and request a Policy Exception or file an Out‑of‑Scope affirmation to avoid IOT procurement blocks - questions and submissions go to ResponsibleData@mph.in.gov and full guidance is on the State of Indiana AI Policy page (State of Indiana AI Policy and Guidance - Indiana MPH AI Resources); run a tight, measurable pilot (a public‑records document triage/redaction pilot is a common starter) to prove turnaround and legal controls (Public Records Triage Tool for Government AI Use Cases - Case Study), pair the pilot with a workforce plan and local reskilling partners (Ivy Tech pilots), and close the loop with targeted training such as the 15‑week AI Essentials for Work course to make redeployment to case management practical and auditable (Nucamp AI Essentials for Work Syllabus - 15‑Week Professional Course); the so‑what: early APO assignment plus a single, well‑documented pilot turns opaque reviews into approvable submissions and prevents procurement stalls.

“The so‑what: naming the APO and filing the Readiness Assessment before procurement is the single operational move most likely to turn a stalled project into an approved deployment.”