KT develops Agentic Data Flow to enable autonomous AI business execution

The landscape of artificial intelligence is shifting from generative chatbots that provide answers to AI agents capable of autonomous execution. Unlike traditional tools, AI agents can navigate multiple systems, retrieve information, and perform actual tasks such as sending emails or registering business workflows based on specific conditions.

KT has announced the development of its ‘Agentic Data Flow’ solution to support this transition. This system is designed to connect AI agents with a company’s internal data and operational expertise. The framework consists of four pillars: K Feature Map for standardized data, K Meta for data meaning and security, KT Ontology for structuring business manuals and policies, and K Evaluation for verifying the AI’s decision-making process and execution quality.

As AI agents take on more responsibility, the focus of intellectual property and technical strategy is moving toward how these systems manage state, authority, and error recovery. Experts note that a company’s value in the agentic era will depend not just on the underlying large language model, but on the proprietary workflows, permission structures, and data integration methods used to control the AI’s actions.