Weekly Generative AI Market Pulse Survey

Weekly GAI Market Pulse is a nationwide, weekly online tracking survey that monitors the current state and direction of consumer adoption of generative AI (GAI) services in South Korea. As a market pulse study, it repeatedly measures stable core indicators to read the market’s dynamic movement, check brand/campaign health, and detect early signals of risks and opportunities. Anonymized microdata are released weekly through Harvard Dataverse and KOSSDA (Korea Social Science Data Archive, Seoul National University). Each release includes the questionnaire (instrument) and codebook to support verification, re-analysis, and citation. Certain proprietary brand KPIs for commercial tracking (e.g., detailed brand-level quality and loyalty metrics) are excluded from public files. [Core Analytical Framework - Seven Lenses] • Market Diffusion Status: Diagnose diffusion stage and growth momentum using adoption-funnel and market-health indicators. • Brand Competitive Landscape: Monitor concentration, shifts, and switching in users’ go-to GAI services to detect early threats/opportunities. • Usage Context and Maturity: Assess behavioral maturity (where/how/for what) and identify high-growth 'killer tasks'. • Behavior-Perception-Value (B-P-V) and Monetization: Connect behavior to perceived value to derive levers for paid conversion (pricing/value proof/core tasks). • Brand Audit (SQI and NPS): Prioritize product/UX, trust, and pricing improvements using consistent quality and advocacy KPIs. • Tech Persona: Design positioning, messaging, and channel strategy by segment (Tech-MBTI, MBTI, digital proficiency). • Social Impact and Agentic AI: Monitor expectations/concerns and agent needs to anticipate regulatory/ethical issues and next-wave scenarios. [Key Survey Modules] • Awareness and Experience: Term awareness; recognized vs used services; first used service and triggers. • Recent Usage Behavior: Last-month/week usage (MAU/WAU); frequency; average daily time; usage locations. • Purposes and Tasks: Work/study vs personal share; task experience (search/summarization, writing, translation, coding, image generation, etc.). • Monetization: Paid services (self-paid vs paid by organization/others); monthly spend; maximum willingness-to-pay; conversion intent. • Brand Performance: Up to three primary services and reasons; satisfaction and NPS; time share; continuation and paid intent; SQI attributes. • Tech DNA and User Profiling: Tech-MBTI; personality MBTI; device ownership/screen time; life stage; occupation/role; workplace AI adoption climate. • Social Impact: Ontological definition of AI; trust and risk tolerance; outlook across nine social domains. [Methodology and Sample] Universe: Residents of South Korea aged 18-65 (nationwide). Weekly sample size: 800 completes. Sampling: Quota by gender, age, and region; random selection within frame. Mode: Mobile/web online survey. Fieldwork: Weekly, starting February 2026. Contact: [e-mail]