KTO uses big data to attract 30 million tourists

The Korea Tourism Organization (KTO) set an accelerated target to reach 30 million foreign visitors by 2028, presenting a "10 flagship projects plan" at a press briefing, according to reporting by Chosun (Feb 2). Chosun quotes Park Seong-hyeok, president of the KTO: "We will achieve the early goal of 30 million foreign tourists visiting by 2030. We will open the era of 30 million inbound visitors by 2028."

Asiae reports that KTO is publishing roughly 7.5 million pieces of tourism data through the Korea Tourism Content Lab open API and has launched the 2026 Tourism Data Utilization Competition in partnership with Kakao (Asiae). The competition is structured across development, implementation, and advancement phases, will select 31 teams for awards, and offers a Kakao-channel testbed for winners and additional support such as extra points in the Korea Credit Guarantee Fund program "Start-Up NEST" (Asiae).

Asiae documents the open dataset as including tourist information, images, and big data accessible via API; the competition will provide customized consulting to teams that pass preliminary review and will stage implementation and advancement categories in July (Asiae). Chosun reports KTO will deploy market-specific strategies, focusing repeat-visit demand in Chinese-speaking markets and Japan, stimulating growth markets like Southeast Asia and the Middle East through K-culture products, and targeting high value-added segments such as medical, wellness, and MICE (Chosun).

Opening large public datasets and creating a developer prize/testbed pipeline is a common pattern for public-sector data programs seeking third-party innovation. Industry observers note that combining open APIs with platform testbeds accelerates prototyping for data-driven recommendation, personalization, and demand-forecasting features, while lowering go-to-market friction for startups and internal teams.

National-scale tourism targets translate into predictable demand signals for vendors of analytics, real-time visitor profiling, recommendation systems, and location-based services. For AI/ML practitioners, an openly available corpus of multi-modal tourism data at the scale reported (~7.5 million records) presents material opportunities for building and benchmarking recommendation engines, image-based POI recognition, and demand-forecast models using real-world traffic and event signals.

• •Uptake and quality of the entries from the 2026 competition and which technical approaches winners use on the Kakao testbed (Asiae).
• •Availability and schema documentation for the advertised 7.5 million dataset: whether it includes real-time signals, anonymized mobility traces, or only static POI and image assets (Asiae).
• •How KTO reports outcomes against the 30 million by 2028 target in subsequent public updates and whether metrics will include spend-per-visitor or segment-level KPIs (Chosun).