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

Columbus is more than the state capital; it's the epicenter for Ohio's push to modernize public services - home to recurring events like the OITA Innovation and CyberOhio summits that spotlight AI, cybersecurity, and IT modernization in state and local government (OhioITA summit coverage on AI and IT modernization) - and a testing ground for the InnovateOhio platform, which already supports roughly 15 cabinet agencies and “more than a million” digital identities to streamline citizen access and cross‑agency data use, making routine administrative work especially vulnerable to automation (InnovateOhio platform lessons for state governments).

That combination - policy momentum, statewide digital identity, and public-facing service redesign - creates both risk for clerical and customer-service roles and a clear opportunity: targeted reskilling.

Short, practical options such as Nucamp's 15-week AI Essentials for Work bootcamp offer a direct path to learn prompt-writing, workplace AI tools, and role-specific workflows so displaced workers in Columbus can move from at‑risk tasks to high‑value AI‑enabled roles (Nucamp AI Essentials for Work syllabus and course overview).

"We want to be innovative in creating or rebuilding those solutions in the cloud, rather than just a 'lift and shift' of those systems to the cloud."

Selection prioritized concrete, evidence-backed risk factors drawn from state-focused guidance: NGA and AAAS frameworks that catalog AI harms and mitigation steps, plus examples of current Ohio deployments (e.g., OHIO.gov chatbots and automated benefits tools) guided the ranking; roles were scored by (1) task automability - high-volume, rule-based duties like data entry and benefits adjudication; (2) potential to affect rights or safety, per NGA/OMB/NIST criteria (the NGA brief cites automated benefits errors that wrongly accused 20,000–40,000 people); (3) prevalence in Ohio state and local workflows; and (4) proximity to practical reskilling pathways so displaced workers can move into supervised, AI‑augmented jobs.

Each role's risk score combined technical susceptibility to automation with public‑impact gravity and local adoption signals from AAAS and NGA resources, producing a top‑five list focused on clerical and customer‑facing government jobs most likely to be automated - and most urgent to pair with short, targeted training such as Nucamp's local AI governance and workplace‑AI offerings to preserve service quality and resident protections (NGA mitigating AI risks in state government webinar, AAAS EPI responsible AI use guidance, Nucamp AI Essentials for Work syllabus and course details).

Customer service representatives across Ohio - especially staff at County Departments of Job and Family Services and Medicaid call centers - already face concrete automation: the Ohio Benefits “Family of Bots” has reviewed and processed over 500,000 cases and saved caseworkers more than five years of working hours, shifting routine tasks like data cleanup and eligibility updates to machines so humans can focus on exceptions and in‑person support (Community Solutions report on Ohio Benefits “Family of Bots”).

Targeted automation sits alongside statewide modernization efforts - the InnovateOhio Platform's emphasis on customer experience and single digital identity accelerates adoption of self‑service tools and integrated workflows - so customer‑facing roles that don't adapt risk shrinking while those who gain supervised‑AI skills can move into oversight, complex casework, and quality assurance (InnovateOhio Platform customer experience and platform overview).

Practical local signals also appear on the Ohio Benefits portal, which continues to expand mobile and self‑service features that reduce routine call volumes and raise the premium on empathy, problem‑solving, and bot‑supervision skills for remaining staff (Ohio Benefits self-service portal and resources); one memorable metric: the Baby Bot enrolled over 50,000 newborns into Medicaid same‑day, showing how automation can dramatically shorten timelines and reframe where human judgment adds the most value.

Office and administrative support and data‑entry clerks in Ohio face concentrated risk because two statewide modernization moves directly streamline the repetitive tasks these roles perform: the State's centralized procurement service - OhioBuys - publishes a public catalog and connects buyers with bidders, shrinking manual purchase‑order entry and price‑checking work (OhioBuys centralized procurement catalog and public catalog - Ohio Office of Procurement Services), while the InnovateOhio Platform's push for single sign‑on, just‑in‑time provisioning, access logging and self‑service shifts routine identity and account maintenance into automated flows (InnovateOhio Platform digital identity and automation - InnovateOhio).

So what: instead of dozens of daily line‑item edits and password resets, remaining staff will be judged on exception‑handling, contract oversight, access‑management, and QA of automated outputs.

Practical paths forward that align with state priorities include reskilling into vendor management, identity‑proofing and access roles, and supervised‑AI quality assurance - skills that map directly to InnovateOhio tools and procurement workflows and preserve career continuity while improving service reliability.

Paralegals and legal assistants in Ohio face rapid task compression as AI proves effective at high-volume, rule-based legal work - particularly contract review, redlining, and routine Q&A - tasks experts expect to show

big efficiencies

by 2025 (2025 AI legal tech predictions from 65 experts); concrete vendor tools like LexisNexis Protégé contract review and drafting tool already advertise tailored contract review, document summarization, full‑document drafting in Word, and timeline/analysis features that remove many first‑draft and review chores.

So what: routine drafting and citational pulls that once anchored paralegal hours can be reduced to AI‑generated first drafts, while the human value shifts to supervising outputs, validating sources, handling exceptions, and documenting chain‑of‑custody and compliance.

Practical adaptation for Ohio government legal shops includes learning supervised‑AI workflows, RAG (retrieval‑augmented generation) oversight, and audit‑trail governance so staff can move from page‑turning to QA and risk management - capabilities reflected in local guidance on municipal AI governance (Columbus municipal AI governance and audit-trail guidance), which preserve client protections while making legal teams faster and more scalable.

Bookkeepers and financial clerical staff across Columbus and Ohio face concentrated exposure because AI is increasingly effective at high‑volume, rule‑based recordkeeping and data‑input work - areas experts in a 2014 survey warned could be part of the next wave of white‑collar automation (Elon University and Pew survey on AI and robotics predicting white-collar automation by 2025).

The practical consequence for municipal finance teams: routine line‑item processing and repetitive reconciliations are prime candidates for automation, which raises the premium on exception management, audit‑trail governance, and supervised‑AI quality assurance.

Local leaders can preserve jobs and public trust by pairing modest retraining with clear governance - implementing AI audit trails and compliance guardrails and piloting cost‑saving deployments that maintain human oversight (best practices for AI governance and audit trails in municipal deployments, how Columbus leaders can pilot AI projects to scale savings and improve efficiency) - so what: bookkeepers who learn supervised‑AI workflows and audit‑trail management are positioned to move from transactional recordkeeping into higher‑value compliance and oversight roles that keep Ohio's public finances transparent and resilient.

“Automation has impacted mostly blue-collar employment so far; the coming wave of innovation threatens to upend white-collar work as well.”

Market research and junior data roles in Ohio are most exposed where work is dominated by ingestion, cleansing, and routine reporting - tasks the InnovateOhio Platform explicitly automates with capabilities like data ingestion & transformation, data prep/profile, and real‑time streaming that feed self‑service analytics and visual dashboards, shrinking the time spent on manual consolidation and opening a clear path to higher‑value work (InnovateOhio Platform data and analytics capabilities for government).

At the same time, the State of Ohio's AI policy builds governance and mandatory training into deployments, which means displaced analysts can pivot to roles that governments need - data stewardship, governed pipeline automation, quality assurance, and applied analytics - rather than competing on basic cleaning tasks; the practical upshot: mastering IOP's data‑prep tools and governance practices lets a junior analyst move from repeatable chores into trusted cross‑agency reporting and oversight that state leaders are prioritizing (State of Ohio AI policy on training, governance, and data protection).

“Ohio is at the forefront of the innovative use of technology in the public sector and AI has great potential as a tool for productivity, as well as education, customer service, and quality of life,”

Five practical next steps for Ohio government workers: (1) complete the State's eight‑part Responsible AI training in OhioLearn to learn governance, safe use practices, and hands‑on exercises for public service AI deployments (OhioLearn Responsible AI training); (2) adopt InnovateOhio's AI Toolkit to translate policy into checklists for vendor oversight, audit trails, and classroom‑style local training (InnovateOhio AI Toolkit and strategy); (3) reskill with a short, practical program that teaches prompt engineering and supervised‑AI workflows - e.g., Nucamp's 15‑week AI Essentials for Work - to move from rote tasks to bot supervision and QA (Nucamp 15‑week AI Essentials for Work syllabus); (4) pursue TechCred or agency‑sponsored reimbursement and volunteer on InnovateOhio pilots to gain documented experience with state tools; and (5) target roles in exception management, audit‑trail governance, data stewardship, and quality assurance by asking to own one bot‑QA process or a single audit trail project - concrete, on‑the‑job steps that pair policy awareness with applied AI skills and keep public services accountable.

“AI technology is here to stay, and as a result, InnovateOhio took the lead on hosting forums over the summer to discuss the impacts.”