Fewer than 30% of companies are successfully translating generative artificial intelligence into tangible business value, and Hankook & Company Group says the bottleneck lies not in the technology but in how it is applied in the workplace. The assessment was delivered in the grand keynote at “Attention 2026” by Kim Sung-jin, Executive Vice President and Chief Data Officer (CDO) and Chief Information Officer (CIO) of Hankook & Company Group, on the 3rd at the Harmony Ballroom of The Westin Josun Parnas in Seoul.
“Even as AI lowers the barriers to technology adoption, the role of defining the problems to be solved and judging the quality and business value of the output still rests with people,” he emphasized.
Kim said many companies remain stuck at the proof-of-concept (PoC) stage after adopting generative AI, with data scattered across the value chain — from R&D and production to quality, logistics, and finance. He warned that traditional large-scale system development approaches require extensive time and manpower from planning to deployment, making it difficult to respond quickly to changes in the field.
AI transformation: PI on AI and business teams building their own tools
To address these limits, Kim proposed “PI on AI” (Process Innovation on AI), which involves redesigning work processes themselves around AI. The core objective is to create an environment where business teams — those who understand each business most deeply — can directly leverage AI to define problems and evaluate output.
Hankook & Company Group is applying this principle under Chairman Cho Hyun-bum’s “Data·AI Driven” management strategy. The group first built a cloud-based group data platform to connect key business data and established a Single Source of Truth (SSOT) as the enterprise-wide common data standard. This laid the foundation for business teams to more easily find and utilize the data they need and integrate AI into decision-making processes.
The approach shifts responsibility for problem definition and the assessment of AI-derived value to business practitioners, aiming to turn generative AI adoption into measurable business outcomes.
