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

Topeka public employees should pay close attention to AI because Kansas is accelerating into a tech-forward moment - being named an Consumer Technology Association Innovation Champion announcement for Kansas signals growing statewide investment in robotics and AI - while state policy is already responding: HB 2313 bars state-issued devices from accessing certain models like DeepSeek, and federal OMB federal AI guidance (April 2025) is pushing agencies to catalog and govern AI use.

That mix of opportunity and regulation means administrative staff, call-center teams, and data assistants in Topeka can either be sidelined by automation or seize new roles by learning practical AI workflows; targeted upskilling such as the AI Essentials for Work bootcamp - practical AI skills for public employees teaches prompt-writing and day-to-day AI skills public employees need to stay indispensable - and keep local services efficient and accountable.

“Being named an Innovation Champion for the third time during my administration underscores our efforts to adopt policies that attract technological innovation across a variety of industries,” Governor Laura Kelly said.

To identify the five Topeka government jobs most at risk from AI, the analysis blended Stanford's human-centered survey and task-classification framework - which mapped tasks into Green, Red, and R&D Opportunity zones - with real-world payroll evidence showing early-career declines, then filtered those insights through an equity-and-governance overlay to keep public-service impacts front and center; in practice that meant prioritizing roles where routine, repeatable tasks line up with AI's high-capability “Green Light” work, where entry-level hiring has already fallen (the Stanford payroll findings show outsized declines for 22–25‑year‑olds), and where worker concerns about trust and oversight are acute, so Topeka's call centers, clerical permit workflows, and data-assistant positions rose to the top of the list.

This mixed-methods approach - pairing the Stanford HAI task and preference analysis with empirical ADP-based employment trends - also weighed augmentation vs. automation (since some AI use increases hiring when used as a tool), and flagged roles that agencies can realistically reskill for better human–AI partnerships to protect local services and career pipelines.

Read the Stanford HAI study on worker preferences and the Stanford employment and payroll study coverage for the empirical backbone of this approach.

“We anticipate a declining demand for skills tied to data analysis, where AI has demonstrated strong capabilities, while an increased emphasis will be placed on skills that require human interaction and coordination.” - Yucheng Yang

Customer service representatives in Topeka's state agency call centers are squarely in the crosshairs because much of their work - routine IVR routing, answering repeats of the same FAQ, and the tedious after‑call data entry - maps neatly to proven automation like chatbots, AI IVRs, RPA and post‑call summarization; industry rundowns on call center automation trends shaping 2025 show real‑time agent assist, predictive routing, and automated QA are already cutting handle time and shifting work from humans to systems, while other analyses warn that government has lagged the private sector in adopting these tools and must balance speed with security and oversight.

That combination means Topeka reps could see routine workloads shrink fast - but there's a practical path forward: focus on complex dispute resolution, empathy‑led escalation, and AI‑supervision skills (interpreting voice‑analytics flags, auditing auto‑summaries, and coaching augmented teams) so the job becomes higher‑skilled and less replaceable; imagine the stack of unresolved follow‑ups that used to swallow afternoons now reduced to a two‑line AI summary, freeing trained staff to handle the one call a week that truly needs a human touch.

Read what leaders say about public‑sector pacing and the tradeoffs when adopting these systems.

“The natural safety, security and disposition of the government causes some lagging and the process is required to get there.” - Dave Rennyson

Permit and licensing clerks in Topeka face clear exposure as the City already “moved to an online process for license renewals” and vendors promise big speedups: digital portals and permitting platforms can cut routine intake, payments, and status‑checks that used to require hours of data entry, routing, and paper handling (see the City of Topeka Permit/Licensing Portal).

That doesn't mean the job disappears - rather, the work shifts toward exceptions, quality‑control, and supervising automation: clerks who can audit automated plan reviews, resolve flagged compliance edge cases, manage GIS‑linked records, or run the citizen portal will be harder to replace.

Local agencies considering Accela, SmartGov, OpenGov, CivicPlus, GovBuilt or Softdocs already show faster turnarounds and fewer walk‑ins, so reskilling should focus on digital workflows, electronic document review, simple RPA oversight, and customer‑facing dispute handling so staff handle the one tricky permit worth human time instead of dozens of routine renewals; one vendor even documented an application submitted at lunch and fully processed by 12:40, a concrete reminder of how fast mundane admin can move.

Links and vendor case studies offer practical short courses and tools for those career pivots.

“I looked at the workflow. They applied at lunch at 12:10. It was processed, paid, and issued by 12:40.” - Douglas Dancs, Public Works Director (OpenGov case study)

Topeka's press-office writers and editors should treat generative AI as both a tool and a threat: platforms that synthesize web content can already siphon audiences - Google's AI Overviews have been linked to a drop of more than 34% in traffic to outside sites - so a carefully worded city press release risks being flattened into a two‑line AI summary that never sends a single click back to topeka.org (The Atlantic analysis of generative AI content piracy and traffic loss).

At the same time, roughly one in four PR pros say they're using generative tools for press releases, headlines, or proofreading, so press shops that learn safe, verifiable AI workflows can gain efficiency without sacrificing accuracy (MarketingProfs study on the impact of generative AI on press releases).

Risks - hallucinations, copyright exposure, and lost referral traffic - call for concrete measures: adopt a generative‑AI disclosure and editorial policy, train staff in verification and source‑checking, and double down on reporting that requires human judgment (investigations, contextual framing, and complex public‑records work) where machines can't substitute for a reporter's judgment.

For civic communicators, the smart bet is to use AI to speed drafts and data‑sifting, not to replace the human editors who protect accuracy, trust, and public accountability.

“I would never use current generative AI tools to publish directly without human oversight. It is just too risky.” - Charlie Beckett

Entry‑level policy analysts and research assistants - the political‑science grads and news‑analysis juniors who traditionally cut their teeth on literature reviews, data pulls, and briefing memos - are among the most exposed in Kansas and across the U.S. because AI is reshaping the career ladder for newcomers: global reporting flags big declines in entry‑level roles and job openings, while targeted analyses show high task automation risk for research‑heavy work (for example, a 53% task automation exposure for market research analysts) that mirrors the chores many junior policy staff perform; see the World Economic Forum analysis on AI and jobs and the SHRM analysis of task automation risk.

Yet the outcome isn't inevitable - Stanford HAI's assessment on AI augmentation reminds leaders that automation can either strip routine tasks or augment expertise, so Topeka agencies can protect pipelines by redesigning junior roles around verification, stakeholder coordination, investigative judgment, and AI‑supervision skills (trainings that teach prompt‑use, source‑checking, and audit trails will matter).

In short: without proactive upskilling, the apprenticeship ladder that produces senior public‑policy talent could fray; with it, AI becomes a gateway to higher‑value analytical work rather than an exit ramp.

“The risk is that automation could exacerbate wage polarization, income inequality, and the lack of income advancement that has characterized the past decade ...” - McKinsey researchers

Data-focused roles in Topeka - statistical assistants and market-research analysts who keep city programs running on evidence - face real pressure as AI eats routine data cleaning, basic aggregation, and repeatable reporting: one automated-risk model flags statistical assistants at roughly 74–75% exposure to automation, while industry lists place market‑research analysts among roles with high AI applicability.

AI tools can free staff from grind but also shrink entry‑level openings, so the smartest adaptation is to pivot toward algorithm oversight, bias audits, and translating model outputs into policy-ready recommendations; local hires who master prompt‑aware workflows, uncertainty communication, and quality‑gate checkpoints become the human safeguard that machines lack.

Practical upskilling - courses that teach algorithm auditing, prompt engineering, and data‑ethics checks - matches the advice from analysts who caution that AI automates the easy bits but needs human context (and sometimes human rescue: a retailer's automated order spike cost millions until an analyst caught the viral‑trend error).

For more on the automation risk and how analysts can prepare, see the AI Essentials for Work syllabus and register for AI Essentials for Work to begin practical upskilling.

“Every job will be affected, and immediately. It is unquestionable. You're not going to lose your job to an AI, but you're going to lose your job to someone who uses AI.” - Jensen Huang

Practical next steps for Topeka government workers and agencies start with pairing policy and training: adopt Kansas's generative‑AI guardrails as a baseline for safe pilots (Kansas statewide AI policy guidance), then use new workforce investments to upskill staff - Governor Kelly's DOCK awards will expand digital training to nearly 50,000 Kansans and create immediate partnership opportunities with local nonprofits and community colleges (DOCK digital skills programs announced by Governor Kelly); practically, audit routine tasks in call centers, permitting, research, and data units, stand up small verification‑first AI pilots, and enroll affected teams in short, job‑focused courses so humans keep the judgment work.

For staff-ready, hands‑on instruction in prompt use, verification, and day‑to‑day AI workflows, consider a practical course like Nucamp's AI Essentials for Work to accelerate prompt literacy and AI supervision skills (AI Essentials for Work registration).

Combining local training pipelines, campus certificates, and state policy makes AI an augmentation strategy - not a job‑destroyer - for Topeka's public workforce.

“Community organizations across Kansas will use this funding to create immediate opportunities for those aiming to increase digital skills and knowledge. The DOCK program reinforces my administration's commitment to empowering Kansans and meeting the evolving needs of today's workforce.” - Governor Laura Kelly