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

Sweden's national push to harness AI is already reshaping public-sector work: the government's long-standing strategy and recent updates from AI Sweden and the EU's AI Watch stress investments in education, data infrastructure and ethical frameworks so agencies can deploy tools safely and at scale (Sweden national AI strategy - AI Strategy for Sweden, EU AI Watch report on Sweden's AI strategy).

A high-profile commission even called for a rapid €1.5bn boost and a state-managed “AI-for-all” hub to speed adoption, turning routine clerical tasks, records processing and parts of citizen-facing services into prime targets for automation - a change that makes reskilling urgent.

Practical, work-focused training like the AI Essentials for Work bootcamp can help public servants learn promptcraft, tool selection and risk checks so human oversight stays central (AI Essentials for Work bootcamp syllabus), because policy and skills must move together if Sweden is to improve services without leaving workers behind.

“AI has huge potential to improve the welfare system, enhance the quality of public services and strengthen Sweden's competitiveness. We must ... It will be extremely interesting to read these proposals,” says Minister for Public Administration Erik Slottner.

Selection of the top five at‑risk roles focused on concrete Swedish evidence, practical risk checks and documented legal outcomes: priority went to municipal case studies and routine, document‑heavy job profiles where automation already shows promise or danger, such as the Norrtälje pilot that purchased a 2.7 million SEK RPA/AI system and ultimately shelved it after legal review (Norrtälje children-at-risk algorithm case study (AlgorithmWatch)).

Sources were vetted for Sweden‑specific relevance (municipal reporting, cost comparisons and SKR findings), for operational transparency - avoiding “black box” automation - and for guidance on testing outputs and bias mitigation, drawing on practical checklists like those on safety, bias and appropriateness checks for model outputs and on the national roadmap in the AI & Digitalization Strategy 2025–2030; this mix ensured the list highlights roles where routinized decision logic, cost pressure and weak governance converge, and where careful reskilling and pre‑release testing can realistically protect services and workers (AI output safety, bias and appropriateness checklist, Sweden AI & Digitalization Strategy 2025–2030 national roadmap).

“Using previous decisions reproduces hidden values and norms, which can lead to undesirable effects for social work such as exclusion and embedded beliefs.”

Trelleborg stands out as a concrete Swedish example of how RPA can remake social‑benefits work: the municipality's UiPath pilot automated routine welfare‑support decisions so that a single “robot” now compiles applications overnight, cuts processing for routine cases from an average of eight days (sometimes up to twenty) to one minute or less, and freed two employees to focus on complex, in‑person cases - helping 22% more people and delivering a reported 94% time‑saving in the department (see the UiPath Enterprise RPA case study for Trelleborg Municipality).

While these gains improved morale and let staff spend more time with applicants, the project also sparked transparency and safety debates: investigative reporting found the Trelleborg codebase hard to interpret and, alarmingly, containing names and social‑security numbers for about 250 people, prompting wider scrutiny, legal requests and a political debate about where automation crosses the line (read the AlgorithmWatch analysis of Trelleborg's automation).

The Trelleborg story illustrates the “so what?” plainly - automation can speed services and reallocate human effort, but without rigorous pre‑release checks, explainability and data hygiene those gains can quickly become governance and trust risks.

“UiPath makes their workday more structured and so much better.” - Eleonore Schlyter, Unit Manager, Department of Welfare, Trelleborg Municipality

For administrative clerks and records staff who drown in incoming e‑mails, reports and case files, the RISE‑led “Language models for Swedish Authorities” project shows how Swedish‑trained NLP can do the heavy lifting: models developed with AI Sweden, the National Library and partner agencies can triage e‑mail, tag entities, group related documents and produce summaries so the right case officer sees the right information at the right time - turning a messy inbox into an organised work queue and freeing staff for judgment‑centric tasks (see the project overview on AI Sweden project: Language Models for Swedish Authorities (project overview) and RISE's write‑up on how National Library texts helped build a “language brain” for government RISE article: How National Library texts helped build a language “brain” for government).

The initiative - Vinnova‑funded and completed in 2022 - already produced models, code and use cases that reduce repetitive document processing, but it also flagged real constraints: data readiness, regional language coverage and national hosting needs that affect sovereignty and operational risk, so rigorous pre‑deployment testing and clear governance remain essential if automation is to speed work without undermining trust.

“When you apply language models at the right place in an authority, you can use the technology for increased efficiency or better service to the public,” says Magnus Sahlgren.

Citizen-facing channels - phone lines, web chat and agency FAQs - are among the clearest places Swedish government work will change: language-aware models being built by RISE and partners promise to sort e‑mails, answer common questions and route queries so the right caseworker sees the right file at the right time, reducing the endless menu‑clicking and long queues that frustrate callers (RISE: Language models for the Swedish Government).

International experience shows the same pattern: AI can surface full caller context before “hello,” collapse repetitive inquiries into automated answers, and free staff to handle identity, complex legal or vulnerable‑client cases that still need humans - while improving retention and making service more consistent (ABC News: AI in call centres).

But the Swedish rollout must pair capability with caution: multilingual and regional language coverage, explainability and pre‑release safety checks are non‑negotiable if chatbots and IVAs are to boost trust rather than erode it - so integrate rigorous safety, bias and appropriateness checks into pilots from day one.

“A.I. has taken (the) robot out of us.” - Armen Kirakosian

Legal and para‑legal advisors and administrative‑law support staff face a clear example of how specialised AI can remake routine legal work: AirHelp's “Lara” pipeline - built from thousands of prior cases and paired with the jurisdiction‑finder “Herman” - now handles a large share of initial legal assessment, freeing humans to tackle contested, high‑risk or precedent‑setting matters; Herman can identify the best jurisdiction in less than a second and Lara was reported to process about 60% of legal‑stage claims with accuracy that outperforms humans, which translates into nearly two thousand lawyer hours saved each month in AirHelp's operations, a vivid reminder of the “so what?” for Swedish administrative law teams (triage, first‑draft arguments and document review can be automated, but oversight, appeals and discretionary judgments remain human work).

Read the AirHelp AI expansion announcement and the AirHelp Lara AI launch details for full details, and consider how similar legal‑assessment tooling could accelerate administrative‑law drafting while demanding strong pre‑deployment checks and governance in Sweden's public sector.

“The legal profession is changing with the use of artificial intelligence, and we have only seen the beginning. Integration of bots is streamlining the legal process, and allowing legal teams to focus on more complex work.” - Henrik Zillmer, AirHelp CEO

Municipal education assessment specialists and support staff in Sweden are already seeing how eye‑tracking plus AI can speed early detection and free scarce specialist time: Lexplore, born from Karolinska Institute research, uses camera‑based tracking while a pupil reads and produces instant profiles that help schools spot children at risk much earlier than traditional tests (Lexplore reading AI research and timeline).

The models - refined from a Swedish classroom study and larger international data - report an accuracy of about 97% across grades 1–8 with a test‑retest reliability near 85%, and Karolinska researchers note the screening has now been applied to tens of thousands of children in real settings, identifying roughly 10% who need specialised support (Karolinska Institute study tracking dyslexia risk in children).

In practice a short, five‑minute reading check renders eye movements as circles on the text - an immediate, visual cue that lets staff prioritise interventions, target specialised teachers and cut down on long, costly diagnostic pipelines; the memorable payoff is simple: a quick screen can turn months of waiting into minutes of actionable insight for municipal teams.

“Getting early support is crucial in cases of reading and writing difficulties because it makes it easier for younger students to develop their reading abilities than when they're older,” says Mattias Nilsson Benfatto.

Sweden's path forward is less about avoiding AI than steering it: a cross‑cutting adaptation strategy for public servants should pair clear governance and shared infrastructure with fast, practical reskilling so agencies can pilot safely and scale responsibly.

The AI Commission's 75 proposed measures and recommended investments have created political momentum (Swedish AI Commission 75 proposed measures), while independent studies highlight a large efficiency prize - an estimated SEK 25 billion opportunity in administrative processes and a finding that about 74% of public‑administration roles can be complemented by generative AI (SEK 25 billion eGovernment efficiency opportunity (Implement Consulting)).

Practical steps for employees and managers include mandatory pre‑deployment safety checks, shared national testbeds and language‑aware models, plus short, work‑focused courses so staff gain usable skills quickly - training that can be delivered in compact formats such as the 15‑week AI Essentials for Work bootcamp (AI Essentials for Work 15-week bootcamp syllabus).

When policy, procurement and learning move together - central testbeds, funded retraining, and clear accountability - automation becomes a tool to lift public services instead of a source of disruption.

“AI has huge potential to improve the welfare system, enhance the quality of public services and strengthen Sweden's competitiveness. We ... It will be extremely interesting to read these proposals,” says Minister for Public Administration Erik Slottner.