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AI & Enterprise

AI adoption: Governance design comes before model selection, Amorepacific architect says

Hwang Tae-jin (황태진), a systems architect leading AI projects at Amorepacific, said many companies see AI initiatives stop after the proof-of-concept stage. He cited three reasons: the pace of technology change, a gap between expectations and workplace reality, and challenges around applying corporate data to AI, including security and cost control. He said Amorepacific designed AI governance before choosing models and now runs three AI agents in production.

AI & Enterprise

Samsung SDS says three trends to watch in agentic AI supply chain era

Samsung SDS held the Cello Square Conference 2026 at its Pangyo logistics campus on April 2 under the theme of the agentic AI supply chain era. It invited about 120 shippers, including manufacturers and retailers, to share strategies to respond to global supply chain risks and key trends and cases. Samsung SDS said it identified 10 trends using generative AI analysis and distilled three core insights for logistics.

AI & Enterprise

Trust layer, change management needed for enterprise AI adoption

Yeom Dong-hoon (염동훈), chief executive of MegazoneCloud, said enterprise AI adoption requires both an enterprise trust layer and change management. Speaking at the ICON2026 conference, he said firms must build a reliable environment and manage how employees use AI at work. He cited McKinsey data showing only 7 percent of companies create large value from AI. He also warned many employees use unapproved AI services, raising leakage risks.