The Complete Guide to Using AI as a Marketing Professional in Taiwan in 2025

Taiwan's 2025 AI marketing landscape is fast-moving and mobile-first: with internet penetration near 92.8% and roughly 94.7% of users online via smartphones, brands must optimise for short, visual moments on LINE (used by ~95%), Facebook (~90%) and Instagram (~70%) while leaning into video and shoppable social formats, local language nuance and true localization strategies (see the deep-dive on platform and localization trends).

AI is shifting from single tools to task-based agents that will act as new “gatekeepers” for discovery and purchases, so marketers should plan for conversational search and Generative Engine Optimization even as Taiwan's generative AI market scales rapidly (2024 = USD 58.44M; projected to USD 300.98M by 2033).

For marketers who need practical skills now, short, applied training like the AI Essentials for Work bootcamp builds prompt‑engineering and workplace AI fluency to turn these macro trends into campaigns that resonate with Taiwanese consumers.

Taiwan's 2025 AI strategy is now a coordinated, high‑stakes national effort that reads like a modern “Ten Major Construction” for the digital age: the AI New Ten Major Construction aims to build an “AI Island” with cross‑agency leadership from the National Development Council and the National Science and Technology Council (NSTC), heavy industry buy‑in from firms like TSMC and Hon Hai, and targeted bets on silicon photonics, quantum computing and smart robotics to secure Taiwan's chip‑to‑model advantage (details in the plan are summarised in this TechSoda coverage).

Alongside large‑scale capital - roughly NT$190–200 billion earmarked for 2025–2028 - the government is rolling smaller, tactical programs such as the New Silicon Valley promotion plan (NT$36 billion for 2025–2029) and NSTC‑led labs and regional projects to push AI adoption across millions of enterprises; complementary rules, testing sandboxes and a MODA‑run AI Evaluation Center are intended to raise trust and align risk frameworks with international practice (see NSTC for program briefs).

The strategy is explicitly talent‑heavy - targets range from tens of thousands of re‑training slots to ambitions for 1,000,000 AI professionals and large venture funds to seed regional hubs - so marketers and product teams should treat Taiwan's policy mix as both an innovation pipeline and a regulatory roadmap that will shape platform, data and procurement choices in the years ahead.

Without proper AI regulations, Taiwan risks chaotic applications and hindered industrial development; citizens could be “running naked in the AI wave”.

Taiwan's new AI Basic Act has moved rapidly through 2025: after intense committee negotiations it was passed in draft by the Executive Yuan on August 28, 2025 and sent to the Legislative Yuan for plenary review, a milestone that turns high‑level principles into a legal framework marketers must track closely (see the detailed timeline and analysis at Ju‑Chun Ko's AI Basic Act summary).

The draft is framed as a “development‑friendly” basic law rather than a prescriptive ban - it sets out core principles (sustainability, human autonomy, privacy, security, transparency, fairness and accountability), mandates government action on data openness and training corpora, and tasks the Ministry of Digital Affairs (MODA) with building an internationally aligned AI risk‑classification and evaluation system while leaving sectoral enforcement to existing regulators (financial, health, transport, etc.), a hybrid approach explained in legal briefings like the Chambers/Lee & Li practice guide.

For marketing teams in Taiwan this matters in three concrete ways: expect rules or labels for high‑risk AI outputs and required transparency/disclosure; anticipate tighter interplay with the PDPA and sector regulators on data use and model training; and watch MODA's subordinate regulations, sandboxes and the AI Evaluation Centre for procurement, certification and trust signals that will influence platform selection and vendor contracts - think of the law as a new rulebook that prioritises innovation but will increasingly demand traceability, consent and explainability in campaign tools and data pipelines.

"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."

Taiwan's AI credentials rest on a rare blend of world‑class hardware, dense manufacturing know‑how and growing policy support: the island's integrated semiconductor and server ecosystem - from TSMC's advanced process roadmap to a cluster of contract manufacturers and cooling, power and packaging specialists - underpins claims that Taiwan controls up to 90% of global AI server manufacturing capacity, turning the island into a de facto backbone for AI infrastructure (see the Trax Technologies analysis).

That manufacturing muscle is matched by a vibrant innovation stage - COMPUTEX 2025 drew 86,521 buyers and showcased startups to hyperscalers - signalling demand and commercial pathways for AI products and services.

Add government and standards work cited in the Lee & Li legal review and national strategy targets for 1,000,000 AI professionals and major R&D funding, and the picture for marketers is clear: Taiwan is not just good at chips, it's an end‑to‑end AI ecosystem where research, talent pipelines and real customers meet, meaning marketing teams can lean on local technical credibility and supply‑chain stories as part of their brand narrative.

"Taiwan is small, and Taipei is small, and in that small area everything moves super fast."

Treat Taiwan as a mobile‑first, video‑centric market: with internet penetration at roughly 95.3% and 30.4 million cellular connections (about 131% of the population), attention is captured in short, scrollable moments that favour YouTube, Facebook, Instagram and rising short‑form players like TikTok - YouTube alone reaches roughly 18.4 million people and is now the fastest‑growing place Taiwanese go for news (46% use YouTube for news), while LINE remains a near‑ubiquitous messaging layer that shapes discovery and customer care (high single‑platform penetration across APAC).

Marketers should prioritise snackable video, localized language and shoppable creatives, optimise for fast mobile speeds (median mobile download ≈95.7 Mbps) and plan campaigns around platform behaviour - DataReportal's Digital 2025: Taiwan report is the best single source for audience slices and age profiles, and the Reuters Institute coverage cited by Taipei Times explains why video and creator channels are crowding out traditional outlets in news consumption.

That combination - more SIMs than people plus a strong appetite for video news and messaging platforms - makes short, localized conversational creatives and measurable, cross‑platform funnels the practical priority for 2025 campaigns.

Practical AI marketing in Taiwan is less about sci‑fi agents and more about proven, measurable formats: automated creative and localization tools that turn product shots into campaign assets in hours (Appier's Taipei roadshow showed brands cut creative production time threefold and double ROI), hyper‑personalised emails and dynamic websites that raise open and conversion rates, recommendation engines that can drive as much as 35% of e‑commerce revenue, and chatbots that deflect high volumes of support (global forecasts put contact‑centre savings in the tens of billions).

Industrial stories matter locally too - manufacturers use AI for predictive maintenance, quality inspection and supply‑chain optimisation, giving B2B marketers technical proof points to deploy as trust signals (see SotaTek's Taiwan manufacturing case study).

Combine these with the personalization playbook - behavioral, contextual and predictive targeting - and the result is higher engagement (personalization can lift up to 25% of brand revenue) if privacy and consent are handled transparently.

Start with one small, measurable pilot (creative automation, recommendations or a chatbot), validate lift, then scale across mobile and LINE‑first touchpoints to match Taiwanese consumption habits; the memorable payoff is simple: faster assets, happier customers, and campaigns that scale with native technical credibility.

“AI has changed advertising more in the past 12 months than in the past 12 years, and it's only getting started.” - Alexandre Leciel, Co‑founder, AdCreative.ai (Appier blog recap: Integrates AdCreative.ai - Empowering marketers for the new era of AI marketing)

Turn ChatGPT into a practical teammate for Taiwan campaigns by treating prompts like a compact creative brief: assign a Role, define the Task, and give clear Context (R‑T‑C) so outputs match local needs - language, export markets and even city specifics (e.g., Kaohsiung or Taichung manufacturing briefs work better when included) - a technique explained in the GlobalSense guide to ChatGPT for Taiwan businesses (GlobalSense ChatGPT prompt guide for Taiwan businesses).

Use proven frameworks (RACE, AIDA, PAR, CRISPE) from the ButterCMS roundup of prompt frameworks (ButterCMS list of 11 ChatGPT prompt frameworks) to structure asks - tell the model its role, the output format (bullet points, 500‑word brief, table), the tone, and any multilingual targets so copy is export‑ready.

Practically: start with a focused one‑line hook, chain prompts for complex tasks (idea → draft → polish), add examples to lock brand voice, ask ChatGPT to self‑critique, and save high‑performing prompts as reusable templates; MarketingMonk's R‑T‑C checklist shows how these small habits flip AI from guesswork into consistent, on‑brand work.

The payoff is tangible: faster drafts tailored for LINE and mobile‑first channels, multilingual product pages, and repeatable prompts that make AI feel like a trained junior marketer rather than a wild card - keep refining, iterate, and measure each pilot before scaling.

Legal, compliance and procurement decisions are now core marketing workstreams in Taiwan's AI era: the Taiwan Intellectual Property Office warns that using copyrighted works to train models can count as reproduction unless authorised, so creative teams should treat training data and third‑party content as a legal risk (see TIPO guidance on generative AI), while Lee & Li's practical notes stress that copyright protection hinges on demonstrable human creative input - keep a visible version trail, label outputs

AI‑assisted draft; human‑edited

and retain prompts + edit logs for 3–5 years to prove authorship.

Privacy and PDPA rules remain decisive for any biometric or customer data used in model training or personalised campaigns, and MODA's risk‑classification plus the new AI Evaluation Centre mean procurement must move beyond price to require source/rights warranties, process transparency and documented testing histories.

Contract checklists should therefore include: prompt and dataset provenance, indemnities for IP/data breaches, traceability requirements and an escalation plan for takedowns or audits; boards and CMOs should document expert advice to satisfy fiduciary duties when approving AI‑driven spends.

In short: operationalise proof‑of‑authorship, bake PDPA compliance into data flows, and make vendor contracts the first line of governance to keep campaigns agile and defensible (further practical steps are summarised in Lee & Li's guidance on AI content protection).

Salary momentum in Taiwan is clearly running toward technical depth: developer pay ranges from about $22–$48/hour (roughly $3,200–$6,200 monthly) per Second Talent's Taiwan rate card, while local NT$ bands place junior devs in the NT$45,000–65,000 range and senior engineers well into six figures - roles tied to AI and semiconductor software earn notable premiums as demand heats up.

Employers are now willing to pay 30% or more for AI skills (Bookipi's analysis even cites boosts up to 47%), and ADTmag reports that market value for AI‑related skills rose over 3% in the year to July 2025, so hands‑on ML, recommendation systems or NLU experience materially improves bargaining power.

The talent war is tangible - global players have been known to offer packages up to NT$5.5 million to attract senior engineers - so marketing professionals who add practical AI capabilities (model evaluation, data pipelines, or experiment design) will sit in the sweet spot between product, data and growth and capture the best salary upside.

Plan hires and career moves around verifiable project experience rather than certificates, and anchor asks to local NT$ ranges and documented impact.

“Interest in Artificial Intelligence (AI) has grown exponentially in the past decade, driven by employers integrating it into daily operations, the rise of innovative startups, and job seekers eager to break into the industry and enhance their skills. This study provides insight into the highest-paying AI skills and the most sought-after skills that increase one's chances of securing a position in the industry. It also offers valuable guidance on the most effective paths to upskilling for individuals looking to advance their careers in the AI industry. The data also serves as a cautionary tale for sectors such as mining and information technology, where survival rates are notably lower. Entrepreneurs in these fields must be prepared to navigate greater risks and uncertainties. The findings emphasize the importance of thorough market research and strategic planning before launching a business. Understanding the unique challenges and opportunities within each industry is crucial for increasing the likelihood of long-term success.” - Tim Lee, Bookipi

Conclusion - act now, but act smart: Taiwan's AI momentum combines world‑class hardware, new national rules and fast-changing platform behaviour, so marketing teams should follow a tight 12‑step checklist that turns risk into advantage: 1) map MODA's risk classifications and NSTC guidance to every campaign, 2) align data flows with PDPA consent rules, 3) treat training data and third‑party content as IP risk per TIPO/Lee & Li guidance, 4) require vendor test histories and rights warranties in procurement, 5) keep prompts, version trails and edit logs for 3–5 years as evidence, 6) start one measurable pilot (creative automation, recommendation engines or a LINE‑first chatbot), 7) optimise all assets for mobile, short video and LINE discovery, 8) build deep, educational site content so AI search engines can recommend your brand (see the practical tips from GlobalSense on appearing in AI search results), 9) use local LLMs and Traditional Chinese datasets where possible to protect narrative and accuracy, 10) measure lift and iterate - don't scale untested, 11) brief boards with external AI experts to meet fiduciary duty and governance checklists from legal practice guides, and 12) upskill the team with short, applied courses like the AI Essentials for Work bootcamp to make prompt‑engineering and vendor governance repeatable across campaigns; for legal and implementation primers see the Chambers practice guide on Taiwan AI law and the GlobalSense playbook for AI search optimisation, and consider training as the practical bridge between strategy and compliant execution.

AI search engines like ChatGPT to research suppliers and find solutions to their problems.