Resources
The writing readersopen most
Collected from what readers actually search for and read. Grouped by theme rather than ranked — every card opens the full post on the blog, in Korean.
Industry adoption reports
Where other companies are actually using AI
The most-read post
How Korea's major companiesare adopting AI
From Samsung, LG and Hyundai down to startups — a survey of how far AI adoption in Korea has actually come. The most-read post on this blog.
Read the full post- Finance
How the big banks use AI
From Shinhan, Hana and NH to Kakao Bank and HSBC — AI in chatbots, risk and wealth management.
Read the full post - AX
The AX era, company by company
What Korean companies have actually changed under the banner of AI transformation.
Read the full post - Manufacturing
AI on Korean factory floors
From smart factories to quality control — where AI has landed in manufacturing.
Read the full post - Construction
AI on the construction site
Hyundai E&C, Samsung C&T, DL E&C — where AI entered design, safety and scheduling.
Read the full post - Global
Walmart to Klarna: AI inside global companies
How global companies wired AI into internal work, traced across 2023–2025.
Read the full post - E-commerce
AI in e-commerce: revenue and efficiency
Ably’s virtual fitting, Musinsa’s image search, Coupang’s demand forecasts — what the platforms actually run.
Read the full post
Practical guides
What you end up looking for once you start evaluating
- SecurityUsing ChatGPT for business where security mattersBusiness vs Enterprise, where leaks happen, and the settings to lock first.
- Public fundingThe 2026 AI voucher, from a buyer's seatChecking suppliers, eligibility, timeline and selection criteria in one pass.
- Closed networksGenerative AI inside an internal networkHow to run generative AI behind network separation, with real rollouts.
- Market mapKorean AI startups, sorted by fieldChatbots, generative, enterprise platforms, industry-specific — what sits where.
- AgentsKinds of AI agents, and how to chooseThey're all called agents but do different jobs. Criteria for picking by situation.
Concepts
Understand the structure,not the buzzword
Enterprise AI needs clear criteria between data as well as model performance. New to the topic? Start with the ontology introduction.
What an ontology is- OntologyWhy ontology matters for enterprise AIEnterprise AI outcomes depend not only on the model but also on the criteria connecting the data.Read the full post
- LLM × ontologyLLM plus ontology: a blueprint of what the company knowsClearly defined relationships between data can help reduce hallucination.Read the full post
- Manufacturing × ontologyNot a way to collect data — a way to connect itIt starts from why production, quality and equipment read the same defect differently.Read the full post
- MCPMCP, explained for everyoneThe protocol that lets AI reach tools and data, unpacked with plain analogies — plus where Korean companies have started using it.Read the full post
This list follows what readers actually visit and search for, and is refreshed periodically.