Lee Gyu-lee is a business writer at The Korea Times, focusing primarily on IT & telecommunications, the Ministry of Trade, Industry and Energy and KOTRA. Prior to this, she has covered a wide range of cultural news, from film, television and K-pop to lifestyle and fashion.
IBM Korea GM emphasizes company-wide data strategy for AI expansion
IBM Korea General Manager Lee Soo-jung speaks during a press conference at the company’s office in Seoul, Tuesday. Courtesy of IBM Korea
By Lee Gyu-lee
IBM Korea General Manager Lee Soo-jung said Tuesday that the absence of a company-wide data strategy is the biggest roadblock preventing Korean enterprises from implementing artificial intelligence (AI) to advance business outcomes.
“AI has already become a symbol of corporate innovation, but most companies still remain at the experimental stage,” Lee said during a press conference at the company’s office in Yeouido, Seoul.
“To successfully adopt AI and deliver tangible results, Korean companies must urgently strengthen their data strategies.”
Sharing the results of a survey of C-suite executives the company recently conducted, she pointed out many companies still lack the strategy to fully harness their unique proprietary data, urging them to make data strategy a core management priority rather than a technical function.
The survey showed that while CEOs recognize enterprise data utilization as the key to unlocking generative AI value, only 1 percent of enterprise-specific data is used in actual AI products.
Only 13 percent of chief data officers said their companies have the capability to generate revenue from AI — far below the global average — citing challenges such as complex data preparation that cuts into time for actual AI model development and limited real-time data access due to inconsistent formats.
“To drive tangible results from AI transformation, companies must establish clear strategies for securing and leveraging AI-ready data and effectively translate more than 90 percent of unstructured data into measurable business outcomes,” Lee said.
She noted that enterprises should adopt their data strategy company-wide through clear performance indicators, working closely with C-suite tech executives to align data strategy with business objectives.
Adding that AI can’t perform effectively when data is fragmented or inaccessible across systems, she underscored the need for AI agents to access high-quality data, along with flexible, real‑time systems to support it.
She also emphasized the importance of strong data management and governance, warning that poor data quality or compliance gaps can undermine AI reliability.