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

AI is reshaping public administration in Viet Nam: central and local agencies are already piloting systems that automate records, diagnostics and citizen services, and the government's National Strategy to 2030 anchors large-scale deployment and regulation (including a draft DTI law and data-protection steps) to guide that change; see the UNDP note on public-sector adoption and Vietnam Briefing's summary of evolving rules.

Public readiness is high - Vietnam climbed to 6th in the WIN World AI Index and surveys found roughly 60% of residents in four major cities have used AI at least once - yet daily use remains low and a digital divide persists, so training matters.

Practical upskilling options, from short courses to the 15-week AI Essentials for Work syllabus, can help civil servants move from routine tasks toward oversight and policy roles as automation expands.

“With this potential, we believe that Vietnam is an ideal place for NVIDIA to develop R&D centers and build a strong AI ecosystem here.” – Jensen Huang, CEO of NVIDIA

The methodology for identifying the Top 5 at‑risk government jobs in Viet Nam blended practical, evidence‑based criteria with risk governance: roles were mapped by workflow, timed and costed, then scored for AI suitability using the classic checklist of repetitive/rule‑based steps, high volume or frequency, measurable KPIs, and data‑intensity that make automation both possible and impactful (see the AI automation suitability checklist).

Jobs that plug into existing digital systems or rely on routine document processing rose to the top, and pilots were treated as decisive tests - small pilots can turn a 5‑hour report into a 30‑minute task and reveal real savings - so “quick wins” informed prioritization.

To temper opportunity with caution, every candidate job was evaluated against an AI risk framework (govern, map, measure, manage) inspired by the NIST AI RMF and against third‑party vendor checks to catch data, privacy and supply‑chain risks; roles that combined high automation potential with complex governance needs were down‑ranked or flagged for retraining and oversight.

This mix of workflow scoring, pilot evidence, and formal risk controls focused the list on government tasks most exposed to current AI capabilities.

“By far the greatest danger of Artificial Intelligence is that people conclude too early that they understand it.”

Administrative clerks and public‑records data‑entry officers are on the front line of digitisation in Viet Nam: routine tasks - typing, filing, matching forms and answering records requests - map cleanly to current AI tools that can auto‑classify documents, extract fields and flag inconsistencies, which means large volumes of back‑office work can be accelerated but only if data is well governed; that's why a robust public‑sector data governance programme matters, with metadata, retention rules, role‑based access and clear stewardship to keep PII safe and auditable.

Successful automation reduces monotonous keystrokes and error rates, but it also shifts the job toward oversight, exception handling and compliance - roles that need training and a Chief Data Officer or data stewards to coordinate across siloed systems.

Practical first steps for agencies include publishing inventories, tightening records workflows and piloting AI‑assisted classification so officials can move from manual entry to supervision without compromising transparency or citizen trust.

“Organizations really need to prioritize the work of setting out a strategy and carrying out what that vision looks like,” says Dr. Sherry Bennett, chief data scientist at TD Synnex.

Routine tax officers at the General Department of Taxation and customs processing officers face some of the clearest exposure to automation in Viet Nam because their workflows are data-rich, repetitive and already being wired into national systems: the draft Law on Tax Administration pushes a service‑oriented, risk‑based model that layers e‑invoices, bank feeds and suggestive declaration forms to cut duplicate paperwork and speed cases, while broader policy moves such as the new Vietnam Digital Technology Law overview reinforce AI regulation and incentives for automation; together these reforms make routine checks, matching and initial screening prime targets for AI. Practical automation is already mapped out in sector planning - AI risk‑scoring, automatic checks and integrated databases aim to triage returns so human staff focus on exceptions and field audits rather than repetitive verification - and vendors and tax reformers are explicit that inboxes, queues and stacks of invoices will increasingly be replaced by algorithmic flags and chatbots for basic taxpayer queries.

The upside is faster, more consistent treatment for compliant taxpayers; the risk is over‑reliance on opaque models, so modernization must pair automation with clear governance, third‑party control and retraining pathways for officers who will move from processing to oversight roles (Rödl plans for AI in tax inspection in Vietnam).

Frontline public‑service staff - from Social Insurance Agency call‑centre agents to benefits processors at local offices - are already feeling the nudge of automation as chatbots and voice assistants move from pilots into everyday use: Vietnam Social Security has rolled out the OSC Caro chatbot and is expanding AI across VssID channels to handle childcare allowances, sick pay queries and routine case triage, freeing human teams to manage exceptions and complex claims rather than answer repeat questions (OSC Caro and VSS AI services, VssID upgrades).

The switch to fully legal electronic social‑insurance books from 2026 will accelerate that shift - instant access via VssID/VNeID cuts paperwork and makes a citizen's benefits history viewable in seconds instead of leafing through a paper book - while a booming chatbot market (rapid growth in Vietnam's customer‑service AI tools) means 24/7 automated triage, predictive routing and multilingual responses will handle high volumes and reduce queues, so frontline roles will pivot toward oversight, empathy‑led service and complex adjudication rather than routine processing (Vietnam chatbot market data).

Imagine a claims line where routine checks are resolved by a bot in under a minute - a vivid example of why reskilling for exception management matters now.

Traffic enforcement is being transformed in Viet Nam as AI-powered camera networks move from pilot to scale: Hanoi alone has installed 261 AI cameras and three command centres with features like license‑plate recognition, facial ID, green‑wave signal control and around‑the‑clock automatic violation detection - capabilities already able to recognise about 20 types of offences and to push violation notices to drivers via the VNeTraffic app (often within two hours), so routine roadside stops are shrinking while “digital officer” roles - monitoring, exception handling and public‑facing adjudication - grow; see reporting on Hanoi's rollout and timeline to replace street patrols by December and reach full operation by mid‑2026.

That shift promises fairer, faster enforcement and less street confrontation, but it also raises clear needs: workforce reskilling to operate command centres, strict cybersecurity and device standards (QCVN 135:2024/BTTTT), and transparent rules to avoid opaque, high‑stakes automated decisions - in short, cameras will do the watching, people will need to do the explaining and governance (VietnamNet report: Hanoi AI-powered camera rollout and timeline, VNA/VietnamPlus overview of AI camera capabilities and VNeTraffic integration, ASMAG summary of QCVN 135:2024/BTTTT camera cybersecurity rules).

"AI-integrated cameras are capable of automatically capturing and extracting images and video clips of violations, including details such as location, time and specific offense committed."

Routine medical‑admin roles and basic diagnostic triage in Viet Nam are already being reshaped by proven AI tools: VinBrain's DrAid - the first Southeast Asian chest X‑ray assistant to meet FDA standards - can screen 21 lung, heart and bone abnormalities in about five seconds with roughly 91.2% average accuracy, is used across 100+ hospitals by nearly 2,000 doctors and has cut initial screening time by an estimated 80–85%, showing how automation can remove bottlenecks in radiology and triage while freeing clinicians for complex care; agencies must pair these gains with Ministry of Health oversight, strong patient‑safety systems and clear governance so automated flags don't become opaque decisions (see VinBrain's FDA recognition, WHO guidance on patient safety, and recent USAID‑supported improvements to Vietnam's diagnostic networks).

The practical takeaway: AI can turn routine reviews into rapid, consistent triage, but sustaining trust requires regulation, validation in local hospitals, and targeted retraining so medical admins move from clerical checking to safety‑focused coordination.

“This is such a deserving result for the endless efforts during the past three years of the VinBrain team,” said Mr. Truong Quoc Hung, CEO of VinBrain.

Vietnam's path from risk to resilience is a three‑track roadmap: scale skills, harden policy, and redeploy roles so automation becomes an efficiency engine rather than a social shock.

National moves - from the Prime Minister's new Vietnam Digital Literacy Movement nationwide platform that aims to equip every citizen with basic digital skills (a campaign compared to the post‑independence literacy drive) to the planned Vietnam AI Academy staged training coverage to train thousands of AI practitioners - create the supply and civic reach needed to retrain clerks, call‑centre staff and traffic monitors for oversight, exception management and AI‑governance jobs.

Agencies should pair that training with clear rules from the DTI/AI playbook and sector sandboxes so pilots scale safely, while practical, role‑focused courses like the 15‑week AI Essentials for Work bootcamp (registration) offer hands‑on promptcraft, tool use and job‑based AI skills that frontline staff can apply immediately; see the AI Essentials for Work syllabus.

The concrete aim: move workers from repetitive processing to supervisory, audit and citizen‑facing adjudication roles - think command‑centre operators who explain camera decisions, not patrol officers who make them - so technology raises service quality while preserving accountability and jobs.

“AI is simply a tool comparable to electricity in modern society.”