Top 5 Jobs in Government That Are Most at Risk from AI in Orem - And How to Adapt

Orem government workers should pay close attention: AI has moved from a buzzword to a day‑to‑day force reshaping how residents interact with city services, triaging high‑volume tasks and even acting as proactive “digital teammates” that can run rules‑based workflows after hours - a shift noted in Tyler Technologies' analysis of state and local government AI trends (Tyler Technologies report on state and local government AI trends) and warned about by experts on agentic AI (StateTech article on agentic AI transforming local government) that can automate scheduling, monitoring, and outreach.

Utah is among the states tracking AI policy, so Orem agencies must pair opportunistic pilots with governance, transparency, and staff training - practical steps that reduce risk and keep services fair.

For hands‑on skills that help public servants write good prompts, vet outputs, and lead safe adoption, consider training like the AI Essentials for Work bootcamp, which focuses on workplace AI use cases and human oversight to protect residents and preserve public trust.

“What an amazing time to be a public servant,” Dustin said. - Tyler Technologies podcast summary

Methodology: the top‑five list for Orem was generated by matching job tasks to proven AI risk signals from public‑sector studies - applying Deloitte's task criteria for when generative AI can take on government work (Deloitte task criteria for generative AI in government work), cross‑checking with workflow transforms documented by the Public Sector Network on automation, data integration, and predictive insights (Public Sector Network analysis of how AI is transforming public‑sector workflows), and using practical benchmarks from BP3 about where AI already handles routine labor (for example, industry reports show AI managing roughly 38% of data‑entry and 32% of document‑processing workloads).

Prioritization favored high‑volume, rule‑based duties; roles that touch cross‑agency data; and public‑facing positions with measurable inquiry volume in Utah - factors that indicate both near‑term automation risk and strong upside for intelligent augmentation.

Final selections were filtered through responsible‑use guidance for state and local governments to ensure recommendations balance efficiency gains with oversight and fairness (US Digital Response responsible generative AI services for the public sector), so Orem leaders can act on clear tradeoffs rather than speculation.

AI-led tools “Focus more on context and adapting to people and less on task and process flows... [and] AI-led process improvement will take a people-first approach. Context will drive required actions within a single UI experience centered around the customer or employee journey.” - Forrester Twelve Criteria Help Choose Among DPA, Embedded Process Support, RPA, And AI-Led Platforms, Forrester, October 2021

Customer service representatives at Orem City and Utah DMV staff face one of the clearest near‑term shifts: routine, high‑volume inquiries - status checks, renewals, directions to forms, simple permit questions - are prime targets for chatbots and automated triage already deployed across states, and Utah's own AI experimentation makes that transition likely sooner rather than later; NCSL's review of state and local adoption shows chatbots and citizen‑facing automation in many jurisdictions and highlights the policy work states are doing to pair pilots with oversight (NCSL overview of AI in government: state and local adoption).

The upside is practical: virtual agents can handle scripted requests after hours so staff can focus on complex, human‑centered cases, but only if agencies harden systems against model tampering, data leaks, and supply‑chain risks - advice echoed in recent operational guidance on securing AI and protecting continuity of services (CISA-aligned AI protections and data security guidance).

For Orem leaders, the practical next move is low‑risk pilots with clear human‑in‑the‑loop checkpoints, transparent notices to residents, and rapid incident playbooks so convenience doesn't outpace trust.

AI offers a once-in-a-generation opportunity to improve the strength and resilience of U.S. critical infrastructure... I urge every executive, developer, and elected official to adopt and use this Framework to help build a safer future for all.

Clerks and administrative support in Orem - those who manage agendas, public records, FOIA requests, and the steady churn of licenses and minutes - stand at the frontline where AI's promise and risk collide: many tasks are routine and high‑volume, which the GAO flags as most vulnerable to automation unless workers get new skills (GAO report on workers most affected by automation and reskilling recommendations); at the same time, CivicPlus documents the very real barriers clerks face today - patchy document management, backlogs from spikes in public‑records requests, and limited budgets - that make thoughtful digitization urgent (CivicPlus analysis of common barriers to clerks' efficiency, transparency, and compliance).

Practical tools can help: GovPilot and similar platforms show how digitizing and automating routine storage and retrieval lets a clerk pull a record “in a few clicks” rather than rifling through a basement cart of paper, freeing time for judgement‑heavy work (GovPilot case study on digitizing clerk office operations).

Still, deployment must pair technology with training, oversight, and clear workflows so speed doesn't become inaccuracy or offloaded labor for residents.

“Failures in AI systems, such as wrongful benefit denials, aren't just inconveniences but can be life-and-death situations for people who rely upon government programs.”

Translators and interpreters in Orem sit at a crossroads where AI-powered tools - machine translation, automated captioning, and scheduling platforms - are already part of vendor offerings, yet local practice shows humans still matter most: certified vendors in Orem handle official documents across dozens of languages with quick turnaround, while accessible sign‑language and CART options can be stood up for events.

Local resources underscore a practical path forward - partner with professional services for quality and compliance, adopt the translation technology skills taught in university courses, and build internship pipelines to keep oversight local.

See certified, fast document work from Orem translation providers (Orem certified translation services - 35 languages & fast turnaround), rapid VRI/CART and in‑person interpreting coordination in Utah (Deaf Services Unlimited - VRI, CART captioning & sign language interpreting), and UVU's training in translation technology and healthcare interpreting to grow local capacity (UVU Spanish Translation & Interpreting program - translation technology & healthcare interpreting).

“Within minutes” for event captioning and interpreting deployment, and a non‑English speaker can often get a certified form back in a day or join a live captioned meeting the same afternoon.

Writers and communications officers in Orem - public information officers, press teams, and external affairs staff - are already seeing the clearest upside (and risk) from AI: tools that summarize long hearings and bills in seconds, surface real‑time public sentiment, and generate first drafts of press releases or stakeholder emails can free time for strategy and relationship building, but only when paired with human judgment and oversight.

Blackberg Group's analysis of AI in government communications shows how natural language processing and sentiment analysis can improve reach and tailor messaging, while Quorum's reporting on AI for government relations highlights practical wins - automated legislative monitoring, instant summaries, and personalized message variants that let small teams manage larger portfolios more proactively.

For Orem PIOs the practical playbook is clear: use AI to speed routine drafting and monitor issues, insist on source‑linked outputs and human review, and connect training to Utah's growing AI learning efforts so message quality, equity, and trust stay front and center.

“Failures in AI systems, such as wrongful benefit denials, aren't just inconveniences but can be life-and-death situations for people who rely upon government programs.”

Utah Department of Workforce Services (DWS) caseworkers who decide unemployment insurance eligibility sit at one of AI's most consequential front lines: adjudication is high‑volume, rules‑based, and emotionally fraught, which is exactly why the Department of Labor is prototyping an Artificial Intelligence Adjudicator Assistance (AIAA) tool to sort simple claims from those needing deep fact‑finding and to reduce the exhausting back‑and‑forth that can leave claimants waiting weeks or months - a pain point laid bare when initial UI claims spiked 3,000% during the pandemic (DOL Artificial Intelligence Adjudicator Assistance (AIAA) research initiative).

That promise comes with real tradeoffs flagged by national researchers: AI can speed routine summaries and evidence triage, but errors, opaque logic, and worker deference risk wrongful denials or offloading of judgment onto understaffed teams, worsening stress and inequities (Roosevelt Institute report on AI and government workers).

For Utah, the practical path is cautious prototyping - closed, historical data testing, human‑in‑the‑loop reviews, transparent vendor disclosures, clear appeal pathways, and training so DWS caseworkers keep the final say; done right, AI can reduce tedious sorting and leave experienced adjudicators time for nuance, not less oversight.

“Failures in AI systems, such as wrongful benefit denials, aren't just inconveniences but can be life-and-death situations for people who rely upon government programs.”

Practical next steps for Orem leaders are straightforward: treat AI adoption as an organizational change project, not a vendor checkbox - start with a rapid readiness assessment, set clear governance and human‑in‑the‑loop rules, and run tightly scoped pilots that pair measurable service goals with worker oversight and transparent appeal paths; federal and policy research warns that roughly 20% of workers face vulnerability to displacement, so training and reskilling are urgent parts of any plan (FAI recommendations on preparing American workers for AI).

Invest in role‑based AI literacy (basic prompts, verification, data hygiene) and practical governance frameworks so staff can spot hallucinations, audit outputs, and push back when tools nudge decisions - a proven roadmap for agencies is available in public‑sector AI literacy guidance and case studies (AI literacy in the public sector: skills and roadmap for public agencies; EY guidance on agency AI literacy, guardrails, and frameworks).

Use free, public training and workshops to build momentum (for example, InnovateUS's “Artificial Intelligence for the Public Sector” series), and for staff who need hands‑on, work‑focused skillbuilding consider cohort programs like Nucamp's AI Essentials for Work bootcamp: practical AI skills for the workplace - the goal is simple: pilot with worker input, measure outcomes, protect resident rights, and scale only when audits and training prove the tools improve fairness and service delivery.

“Failures in AI systems, such as wrongful benefit denials, aren't just inconveniences but can be life-and-death situations for people who rely upon government programs.”