Will AI Replace Legal Jobs in Taiwan? Here’s What to Do in 2025

Taiwan lawyers should care about AI in 2025 because regulation, government projects and court tech are already changing legal risk and practice: the NSTC's draft “Basic Act” and the government's Taiwan AI Action Plan embed principles on transparency, data governance and accountability that will affect liability and procurement, while sector rules such as the FSC's Financial Industry AI Guidelines and the Judicial Yuan's AI sentencing system show how courts and regulators expect explainability in practice (Lee & Li - Artificial Intelligence 2025: Taiwan practice guide).

Media reports also say a government AI Basic Act was slated for parliament by mid‑2025 (The Legal Wire - Taiwan's first AI law expected by mid‑2025), so upskilling matters: practical courses like Nucamp's Nucamp AI Essentials for Work bootcamp teach promptcraft and workplace workflows that help lawyers reduce malpractice risk and turn AI from a threat into a productivity tool.

Bootcamp	Length	Early bird cost
AI Essentials for Work	15 Weeks	$3,582

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Taiwan's AI rulemaking has moved fast enough to feel like a relay: NSTC kicked things off with the public release of its draft Artificial Intelligence Basic Act on July 15, 2024, laying out seven human‑centric principles and a regulatory sandbox approach (NSTC Artificial Intelligence Basic Act draft (July 2024)), then the Executive Yuan shifted the baton to the Ministry of Digital Affairs (MODA) in early 2025 to lead legislative promotion and a risk‑classification framework that ministries will implement sector‑by‑sector.

2025 saw heated committee reviews and public hearings - including marathon, cross‑party sessions - and by late August 2025 the bill had cleared key committee stages and been pushed forward by the Executive Yuan, signalling that ministries, not a single new regulator, will carry out implementation and subordinate rules (AI Basic Act timeline and MODA agency handoff).

For lawyers, the takeaway is concrete: watch MODA for technical standards and your industry regulator for the sectoral rules that will determine explainability, data governance, and liability - the change is systemic, not theoretical, and happened on a fast legislative clock.

Date	Event	Lead/Responsible
15 Jul 2024	NSTC publishes draft AI Basic Act for public comment	NSTC
26 Feb 2025	Executive Yuan directs MODA to promote the draft	MODA
4–28 Aug 2025	Committee reviews, negotiations, and Executive Yuan passage of draft to plenary	Legislative Yuan / Executive Yuan / MODA

“This AI Basic Act is Taiwan's AI constitution for the next 10 years, advocating development priority, equitable sharing, valuable data opening, and investment encouragement, ensuring Taiwan doesn't lose its way or fall behind in the global AI competition.” - Legislator Ko

The NSTC's draft Artificial Intelligence Basic Act reads like a playbook for practical, Taiwan‑specific AI governance: it codifies seven core principles - sustainable development, human autonomy, privacy and data governance, security and safety, transparency and explainability, fairness/non‑discrimination, and accountability - and pairs them with concrete tools such as a risk‑based management system, a regulatory sandbox and a strong push for data opening and reuse to feed local models (the draft even highlights a “data value‑based opening” clause to improve training datasets) - see the detailed analysis at Lee & Li analysis of Taiwan's AI Basic Act and K&L Gates analysis of Taiwan's AI Basic Act.

Rather than creating a single new regulator, the draft positions the NSTC as the central coordinating authority while charging MODA and sector regulators with implementing a risk‑classification framework and certification mechanisms, and it explicitly protects R&D activity pre‑market by exempting development-stage work from full application liabilities to encourage experimentation.

For Taiwan's legal sector that means watchlists and checkboxes - explainability, traceability and data provenance will move from best practice to statutory expectation, and firms that build processes to document model inputs and impact assessments will be far better placed to manage liability and client trust (background at AmCham Taiwan explanation of the AI Basic Act).

Feature	Summary
Seven core principles	Sustainability, autonomy, privacy, security, transparency, fairness, accountability
Risk‑based framework	MODA coordinates classification; sector regulators enforce
Data opening & reuse	Article 15 promotes “data value‑based opening” for high‑quality training data
Sandbox & R&D exemptions	Regulatory sandboxes and pre‑application exemptions to encourage innovation
NSTC coordination	NSTC serves as central competent authority to align agencies

“Early communication with stakeholders is crucial.”

Existing Taiwanese law already puts a practical leash on AI projects: the Personal Data Protection Act (PDPA) is the primary constraint on any system that ingests or outputs personal data, spelling out data‑subject rights (access, rectification, erasure, portability and objection), cross‑border transfer limits, mandatory privacy notices and heavy security and breach‑reporting duties - with civil remedies, administrative fines (up to NT$15,000,000 for serious violations) and even criminal exposure (up to five years' imprisonment and/or fines) if rules are broken (see DLA Piper's PDPA overview).

Because Taiwan currently lacks a standalone AI statute, regulators and sectoral regimes fill the gaps: the Financial Supervisory Commission's draft AI guidelines and sector laws (fintech sandboxes, medical‑device rules, unmanned‑vehicles experimentation laws) already impose governance, explainability and procurement expectations on deployed systems, while IP guidance from TIPO raises copyright risks for model training data.

Fast‑moving reform is underway - a March 2025 partial PDPA amendment and the creation of a Personal Data Protection Commission (PDPC) are intended to centralise enforcement and tighten oversight - so pilots that neglect consent, provenance or breach playbooks can turn into costly compliance emergencies overnight (see STLI summary and White & Case tracker).

Instrument	Main effect on AI use	Key penalties/notes
Personal Data Protection Act (PDPA)	Limits processing of personal & sensitive data; rights for data subjects; breach notification and security obligations	Civil damages; administrative fines up to NT$15,000,000; criminal penalties up to 5 years' imprisonment / fines
Draft PDPA amendment & PDPC (Mar 2025)	Creates independent data protection authority, centralises incident reporting, strengthens public‑sector DPO duties	Transitionary supervisory changes; phased transfer of private‑sector oversight
Sector rules (FSC, Medical Devices, Unmanned Vehicles, Fintech Act)	Sectoral governance, explainability, certification, sandboxes and procurement requirements	Administrative enforcement by sector regulators; non‑binding guidance often used as de facto standards

Taiwan law firms are increasingly treating AI as a workflow engine rather than a futuristic threat: local surveys from regulators show primary AI goals are boosting operational efficiency and cutting manpower costs, a push that maps directly onto how firms actually use tools today (FSC Taiwan survey on AI objectives for law firms).

Across the legal sector, common applications include drafting correspondence and client letters, speeding legal research and summarisation, automating scheduling and billing, and embedding generative functions into eDiscovery and document review - use cases documented in industry studies and the 2025 eDiscovery innovation research where leading adopters report enormous time savings (one study cites up to 260 hours saved annually for deep integrators) (Everlaw 2025 eDiscovery Innovation Report on law firm time savings).

Firm-level uptake is uneven - large firms and in‑house teams lead while smaller practices often rely on individual experimentation - but the Legal Industry Report 2025 finds drafting, brainstorming and research are already the most frequent AI tasks, making basic governance and staff training the practical next steps (Legal Industry Report 2025 on AI tasks in law firms).

Common AI use	Representative stat
Drafting correspondence	54% of legal professionals use AI for correspondence (Legal Industry Report)
eDiscovery & document review	Leading adopters report up to 260 hours saved annually (Everlaw)
Generative AI adoption	~46% of lawyers reported using AI in recent surveys (LexisNexis)

“Generative AI is breaking new ground across various industries, and its impact on the legal sector in Malaysia and Singapore is significant.” - Gaythri Raman, LexisNexis Southeast Asia

For Taiwan's legal market the split is practical and predictable: AI is already primed to displace high‑volume, rules‑based work - bulk document review and eDiscovery, routine contract redlines and clause extraction, first‑draft correspondence, scheduling and billing automation, and fast statutory or case retrieval where tools can

“scan millions of pages in seconds”

and surface citations in minutes (AI legal research and case handling analysis - UniAthena, Consilio report on Gen‑AI document review).

What AI won't reliably replace in Taiwan is judgement that depends on human values, persuasive advocacy, courtroom strategy, client counselling, and the editorial choices that create protectable authorship - areas where Lee and Li stress visible, substantive human input, version trails and edit logs to preserve copyright and explainability (Lee & Li guidance on AI‑generated content protection in Taiwan).

The right mental model for firms is therefore hybrid: automate repetitive throughput, but invest the saved time into higher‑value legal craft, client relationships and the documentation practices regulators will soon expect.

Tasks AI is likely to displace	Tasks AI won't replace
Document review / eDiscovery, routine drafting, contract clause extraction, scheduling/billing	Advocacy, courtroom strategy, complex negotiations, client counselling, creative legal analysis, proof‑of‑authorship editing

AI is already reshaping what junior lawyers do and how firms hire and bill in Taiwan: routine first‑drafting and high‑volume review are being automated, so firms increasingly want juniors who can QA AI outputs and add judgement rather than only crank out pages - Bloomberg Law notes that a majority of firms now expect new associates to arrive with practical AI experience (Bloomberg Law - Legal Trends 2025).

Hiring data for Taiwan shows a mixed picture - employers are budgeting raises and headcount increases even while reporting acute talent shortages: 52% plan to grow permanent staff, 89% forecast pay rises and 71% say filling key roles is hard, which pushes firms to compete for fewer senior hires and rethink junior pipelines (Robert Walters - Hiring in Taiwan 2025).

The practical result for billing models: expect more value‑based and efficiency‑driven pricing as AI compresses low‑value hours and firms monetise senior review and strategic counselling; paralegals and entry roles will be benchmarked against market pay (paralegal avg ~NT$570,000 per year) and upskilling budgets (Michael Page - Salary Guide 2025).

Picture a junior whose overnight inbox of routine redlines is reduced to a short quality‑control task - that vivid shift is already driving recruiting changes, L&D investments, and new hybrids between billing for time and billing for expertise.

Metric	Value	Source
Employers planning headcount growth	52%	Robert Walters (2025)
Employers forecasting pay rises	89%	Robert Walters (2025)
Employers struggling to fill key roles	71%	Robert Walters (2025)
Paralegal average salary (Taiwan)	NT$570,000 / yr	Michael Page Salary Guide 2025

"It is taking a much longer time to fill key roles. To attract top talent, organisations need to 'sell' their benefits, flexibility arrangements, career development, and support framework to prospective candidates and current employees alike." - John Winter, Robert Walters Taiwan

Hard evidence paints a cautious picture for Taiwan: large real‑world studies - summarised in Fortune's coverage of the NBER workplace study - find only about a 3% average time savings from AI chatbots and that just 3–7% of those productivity gains flow back as higher pay, so the headline AI = instant billable hours is misleading (Fortune: NBER workplace study on AI chatbots and earnings impact (May 2025)).

Managers and researchers add an important wrinkle: the typical time cut can be vivid but small - roughly 25 minutes a day or about 2 hours 50 minutes a week for some teams - and much of that recovered time is reallocated to other tasks unless firms deliberately redesign roles and workflows (Harvard Business Review: How teams spend Gen‑AI time savings (March 2025)).

For Taiwan law firms this means the upside is real but conditional: adoption plus employer training and process change amplify benefits, while passive use mainly creates new QA and oversight work.

Practical first steps - documented prompts, local tool choices and governance - are already available; see the Nucamp AI Essentials for Work syllabus and practical legal AI tools for Taiwan (2025) to move gains from experiment to repeatable practice.

Ethics and malpractice risk in Taiwan already sit at the intersection of data law, tort theory and nascent AI policy, so lawyers need to treat AI governance as a liability-control project: personal data protections and the PDPA (now subject to a Constitutional Court mandate and a May 2023 amendment to create stronger institutional oversight) make consent, provenance and breach playbooks compulsory rather than optional (BNext article: Legal and Ethical Risks of AI Application in Taiwan); at the same time, mainstream legal analysis stresses that AI is not a legal person, so civil claims turn on traditional doctrines - causation, negligence under the Civil Code and product liability rules such as the Consumer Protection Act - while criminal exposure requires proof of human intent or negligence, not machine fault (Chambers practice guide: Artificial Intelligence 2025 - Taiwan (Lee & Li)).

Expect regulators and courts to demand traceability, documentation of testing and impact assessments (the Draft AI Act and Ministry guidelines flag transparency, traceability and explainability), and remember the concrete consequence: pilots that skimp on consent or records - a facial‑recognition trial that sparked privacy pushback is a recent cautionary example - can suddenly become compliance crises.

Practical defence starts with contracts that allocate risk, clear procurement due diligence, retained expert opinions for boards, and meticulous logs to preserve explainability and limit malpractice exposure.

Instrument / Body	Role re: AI risk
Personal Data Protection Act (PDPA) & Amendment	Primary data constraints; Constitutional Court ordered stronger authority and May 2023 amendments strengthen enforcement
Civil Code / Consumer Protection Act	Traditional tort and product liability frameworks apply; causation and negligence determine civil liability
MODA / NSTC / Sector regulators	Risk classification, AI evaluation, sectoral guidelines and procurement standards; expect traceability and documentation requirements

Practical, immediate steps make AI manageable for Taiwan firms in 2025: start with a data‑and‑tool audit that maps where client data flows and whether PDPA notice/consent or TIPO copyright risks apply; build mandatory traceability (preserve data provenance, model inputs, testing histories and decision logs) so every model run can be shown in a later dispute, as the Draft AI Act and Ministry guidelines stress transparency and record‑keeping (Lee & Li Artificial Intelligence 2025 Taiwan practice guide (Chambers)).

Update procurement and engagement templates to allocate responsibility, require vendor testing reports and cyber assurances, and document why an AI tool was chosen over safer alternatives.

Train lawyers through CLE and hands‑on workshops so associates can QA outputs rather than blindly accept them, and give boards a simple expert‑review checklist to satisfy directors' fiduciary duties when approving AI projects.

Use Taiwan's regulatory sandboxes and coordinate pilots with the AI Evaluation Centre/MODA to test high‑risk tools under controlled rules, and watch the NSTC/MODA timetable closely as sector regulators roll out risk classifications and standards (Law.asia Taiwan AI strategy and MODA roadmap).

Treat these measures as routine legal hygiene: document everything, train everyone, and contract for accountability so AI becomes a managed productivity tool - not an uncontrolled liability.

Action	Why it matters (source)
PDPA & IP audit	Limits on personal data and training data; TIPO copyright risks
Implement traceability & testing logs	Draft AI Act and guidelines require record‑keeping and explainability
Update procurement/contracts	Allocate liability, require vendor testing history and security assurances
Use sandboxes & coordinate with MODA/AICoE	Safe testing environment and alignment with risk classification
CLE and hands‑on upskilling	Practical AI literacy for QA and ethical use

New legal careers in Taiwan are shifting toward technical and compliance‑heavy roles that pair law with sector expertise: think patent engineers embedded in semiconductor teams (a TSMC patent role calls the work a “battlefield for gaining experience” and prefers candidates who can draft applications and liaise with US counsel), regulatory affairs and RAQA specialists handling medical‑device registrations for TW & HK, and in‑house compliance or legal ops roles at global tech firms that constantly list openings across Taipei and Hsinchu (Michael Page - Legal jobs in Taiwan, TSMC careers - legal & patent roles).

These openings create demand for lawyers who combine IP, PDPA/compliance savvy and practical AI/tool fluency, so upskilling on targeted resources - for example Nucamp's roundup of the Nucamp AI Essentials for Work syllabus: Top 10 AI tools every legal professional in Taiwan should know - positions candidates to move from document‑centric work into high‑value advisory, risk management and product‑compliance careers that companies are actively recruiting for.

Emerging role	Example / employer	Notes
Patent Engineer	TSMC	Drafting patents, liaison with US counsel; semiconductor focus
Regulatory Affairs / RAQA Specialist	Medical device firms (TW & HK)	Product registration, renewals; salary example NT$900,000–1,055,000
Compliance / Legal Ops (in‑house)	Global tech & finance firms	Policy, PDPA compliance, contract & risk management

“I am excited by how Exiger can expose risk, help manage supply chains, detect threats, and increase transparency in the coming years through our innovative and AI-based technologies.” - Jillian James, Director, Product Management

Keep the feed narrow and the alerts sharp: monitor the NSTC draft and its commentary (start with an accessible summary like K&L Gates analysis of Taiwan NSTC Draft Basic Act on AI), follow the detailed legislative timeline and committee livestreams that tracked fast‑moving reviews in mid‑2025 (Taiwan AI Basic Act legislative timeline and committee livestreams), and watch MODA/AICoE for risk‑classification updates and sandbox guidance; these official streams are where specific sector rules and explainability expectations first appear.

For beginners who want practical, actionable steps, pair that monitoring with hands‑on training - Nucamp's AI Essentials for Work syllabus (Nucamp) - promptcraft, tool choice, and workplace AI workflows teaches promptcraft, tool choice and workplace workflows that turn headline risks into documented, repeatable practice - so alerts, committee recordings and a short, practical course together make an effective three‑point starter kit for staying compliant and useful as Taiwan's AI rules land.

Bootcamp	Length	Early bird cost
AI Essentials for Work	15 Weeks	$3,582