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

South Korea stands at a crossroads: a fast-growing AI market and sweeping public programs mean roughly half of jobs face AI exposure, with routine public‑sector tasks especially vulnerable, yet the shift also creates paths to new roles and productivity gains.

National plans - from the 30 flagship AI projects that target welfare, tax administration and public services to laws that require transparency for high‑impact systems - show government momentum in both promoting and governing AI (see analysis by IceTea Software analysis of South Korea AI impacts and the policy review by Citi Research review of South Korea AI innovation and investment); workers and agencies that learn to use AI responsibly can move from being displaced to being complemented by tools.

For practitioners, focused reskilling matters - Nucamp's Nucamp AI Essentials for Work bootcamp syllabus (15-week) teaches practical prompt design and workflows that civil servants and municipal staff can use to adapt to Korea's fast‑changing public sector.

"cooperation for people's livelihood."

Methodology: the top‑five list was built by adapting the LMI Institute's 10‑point Automation Exposure Score - a task‑level framework that ranks occupations by how routine, manual, or cognitively abstract their daily activities are - to South Korea's public‑sector job descriptions and common municipal workflows; roles that scored high on routine data entry, rule‑based decision steps, and repetitive document handling were flagged for deeper review (the Score itself stresses that high exposure is not a prediction of job loss, since adoption depends on cost, public acceptance, regulation, and worker resistance).

Each candidate role was mapped against concrete task examples (permit processing, form validation, scripted hotline responses, contract line‑item reviews) and checked for local policy constraints and data‑handling needs using practical guidance for government AI use cases and privacy rules (see the LMI Automation Exposure methodology and the PIPC‑aligned implementation notes in Nucamp's government AI guide).

To make the risk tangible, tasks that repeat hundreds of times a week - like copying ID numbers into legacy systems - were treated as high‑exposure signals and prioritized for reskilling pathways and pilot augmentation strategies.

"cooperation for people's livelihood."

Local government clerks - administrative staff who process permits, register licenses, file records, and copy ID numbers into legacy systems - are among the most exposed roles in South Korea's municipalities because their core tasks are highly repetitive and rule‑bound; technologies like Robotic Process Automation (RPA) and low‑code workflow platforms can take on bulk data‑entry, routing, and document management so clerks can spend time on complex casework and constituent trust‑building instead of rote typing.

International examples map directly to practical steps Korean municipalities can pilot: digital permitting and license workflows cut long backlogs (GovPilot notes an 80% time saving on zoning permit data‑entry in one case), while focused RPA pilots can shrink multi‑minute updates into seconds (Brent Council reduced rent‑change processing from 4+ minutes to about 40 seconds in a PoC, per Boxxe).

Combining RPA with intelligent document processing and a clear governance plan lets local governments protect privacy, keep audit trails, and scale services without hiring waves of temporary staff - making modernization a tool for better services, not just cost cutting (GovPilot municipal RPA case study, Boxxe RPA strategy guide for local government).

“For Brent, RPA isn't about staff cuts. It's about being able to allow staff the time to do their proper jobs. The positive effect of this is that staff can now devote their time to making a difference to people's lives, which is why we're here.” – Manjula Pindoria, Digital Workstream Lead, Brent Council

Vehicle licensing officers and permit/license processors in South Korea sit at the intersection of routine clerical work and decisions that can affect people's mobility and legal status, which makes them a natural target for automated decision‑making (ADM) tools that assess eligibility, detect fraud, or speed up routing; governments are already using ADM for benefits and licensing decisions, so carefully designed pilots could shrink repetitive checks like record matching and renewal validation while preserving human review for borderline cases (see the Open Gov Guide on automated decision‑making).

But the promise comes with clear governance needs: transparent audits, notice and appeal paths, and data‑protection assessments to avoid opaque “black box” outcomes that deny a renewal without explanation - lessons echoed in county‑level primers on Automated Decision Systems that urge agencies to map where ADS already live and to treat even spreadsheet‑based rules as potentially regulated tools (Understanding Automated Decision Systems).

Practical adaptation in Korea should pair modest ADM pilots with the PIPC‑aligned data guidance and workforce reskilling so officers move from manual entry to oversight, dispute resolution, and improving customer trust (PIPC data protection guidance).

“Automated decision system” means any electronic software, system, or process designed to automate, aid, or replace a decision making process that impacts the welfare or rights of any Washington resident, and that would otherwise be performed by humans.

Municipal call‑center agents - the public information and hotline staff who answer routine questions about permits, garbage pickup, and benefits - are among the most exposed roles because a large share of queries are repetitive and scriptable; well‑designed chatbots and voice AI can handle 24/7 FAQs, shorten response times dramatically (one TSA pilot cut average social‑media reply times from 90 minutes to under 2), and let human agents focus on complex disputes, translations, or vulnerable callers who need personal help.

That potential comes with guardrails: bots must be grounded in approved databases, offer clear escalation paths, protect personal data, and preserve non‑digital access for those who can't or won't use online tools.

Cities that spread AI successfully pair small, measurable pilots with staff upskilling and internal “ambassadors” who translate technology into everyday workflows - an approach profiled in Bloomberg's playbook for municipal rollout - and they follow proven chatbot design principles that prioritize accuracy, privacy, and accessibility (see practical guidance on government chatbots and risks).

For South Korean municipalities, modest pilots that mirror these lessons - paired with PIPC‑aligned data controls and training for hotline teams - can convert long queues into quicker service and richer human assistance without sacrificing trust.

“AI is a technology for which top-down adoption just isn't going to be effective.” – Kyle Patterson, Boise Chief Innovation Officer

Procurement analysts and legal contract clerks - who juggle high volumes of purchase agreements, redlines, and vendor records - are prime candidates for AI augmentation in South Korea's municipal and national procurement shops because AI can turn repetitive clause-spotting and line‑item checks into fast, auditable workflows: contract‑analysis tools surface risky indemnities or non‑standard terms, OCR and extraction pipelines populate contract repositories, and redlining assistants speed first‑pass reviews from days to minutes while keeping humans in charge.

Practical pilots should pair capabilities with clear guardrails - an AI playbook, human sign‑off thresholds, and data hygiene steps - so tools act as a consistent “second pair of eyes” rather than an opaque arbiter; vendor and governance frameworks in the market show this is reachable; see LexCheck automated procurement contract review and Art of Procurement AI governance framework for procurement.

For risk‑intensive cases, AI can also supply negotiation playbooks and suggested fixes, letting teams focus on strategy instead of busywork, while contract‑risk platforms map issues to policy so audits and renewals stop being a scavenger hunt and become predictable milestones; see DocJuris AI-powered contract risk assessment.

“Your data needs to be structured, clean, and relevant, because the better quality data that you put into AI, the better results you get”.

Routine tax audit officers and benefits‑eligibility assessors in South Korea face some of the clearest opportunities - and risks - from automation because their work is dominated by repeatable verification: reconciling ledgers, matching payee records, and checking eligibility rules.

Practical tools covered in the tax literature - OCR, NLP, agentic AI and AutoVerification - can extract and cross‑check documents, cut manual entry, and even surface anomalies across entire datasets so auditors focus on judgment and exception handling rather than copying figures (see Thomson Reuters' exploration of Thomson Reuters exploration of tax automation and efficiency and its review of AI's impact on tax work).

Robotic Process Automation has already shown auditors can move from tedious keystrokes to high‑value analysis by standardizing data and automating reconciliations, while government accounting guidance underscores the need for integrated tech, controls, and training to preserve accuracy and compliance (read about CPA Journal article on robotic process automation in auditing and Wolters Kluwer: technology in government accounting).

The “so what” is vivid: what once required a week of paper trawls can become a validated, auditable alert in minutes - if pilots pair clean data standards, human sign‑offs, and clear governance so automation augments oversight rather than obscures it.

“a type of software that mimics the activity of a human being in carrying out a task within a process. It can do repetitive stuff more quickly, accurately, and tirelessly than humans, freeing them to do other tasks” - Leslie Willcocks

South Korea's path through AI disruption will hinge on three coordinated moves: practical reskilling for workers, small measurable pilots inside agencies, and policy that funds transitions while protecting people - not just technology.

Rapid, on‑the‑job courses that teach prompt design and workplace AI workflows can convert exposed roles into higher‑value oversight and customer service work; for a ready‑made example see the Nucamp AI Essentials for Work syllabus.

Municipal pilots should pair tight governance and PIPC‑aligned data controls with clear escalation channels so an automated check becomes “an auditable alert in minutes” rather than a mysterious denial; practical steps are outlined in the PIPC data protection guidance.

Policymakers can accelerate equitable outcomes by coupling pilots with retraining and targeted youth programs - Seoul's recent package, which includes an AI talent track to train 10,000 people and place 2,000 by 2026, shows how workforce support can be woven into AI planning (Seoul youth employment measures and AI talent track).

Together, these steps let technology raise government productivity while keeping human judgment, transparency, and public trust front and center.

“A healthy cycle where AI transformation and a hyper-innovative economy lead to creating the kinds of jobs young people want will be the key to solving the employment issue with the youth.” - First Vice Minister of Economy and Finance Lee Hyoung-il