SK AX is moving to accelerate corporate operational innovation through AI branding.

SK AX (President Kim Wan-jong) announced on the 19th that it has launched a new integrated brand, “AXgenticWire,” and will begin full-scale brand operations. The initiative is intended to optimize corporate systems and maximize operational efficiency based on agentic AI.

AXgenticWire is a brand created by combining “Agentic AI,” which makes decisions and executes autonomously, with “Rewire,” which fundamentally redesigns corporate structures. The brand name is intended to embody the goal of innovating so that agentic AI optimizes corporate decision-making and overall operations.

With the recent development of generative AI technologies, the use of AI agents that automate specific tasks has increased, driving a growing need for an integrated system that coordinates collaboration among AI agents across multiple domains and stably manages corporate operations. While the introduction of individual AI solutions has brought work efficiency to a certain level, the impact on overall corporate productivity improvement has remained limited.

In line with these corporate demands, SK AX provides a multi-agent operating environment in which various AI agents collaborate to perform reasoning, decision-making, and execution based on “AI Readable Data.” AI Readable Data refers to structured data that AI models can instantly understand and learn from. On top of this, SK AX adds the “AI Ops (AI for IT Operations, technologies that automate and enhance IT systems using AI)” capabilities it has accumulated so far to provide a stable AX operating foundation tailored to each company’s systems.

An SK AX representative stated, “The value pursued by the AXgenticWire brand is orchestration that optimizes overall corporate operations, rather than partial optimization by each AI agent,” adding, “Through the AXgenticWire operating framework, companies will be able to secure cost reductions and quality stability, while also managing data security and governance.”

The industrial sector is increasingly being viewed as reaching a fundamental turning point beyond simple AI utilization toward agentic AI, where AI autonomously makes decisions and executes them. In particular, the “multi-agent” operating environment, which coordinates the decisions and actions of numerous AI agents so they do not conflict with one another, is assessed as the core of company-wide optimization and the source of SK AX’s differentiated competitiveness. SK AX’s agentic AI technology is being used to drive supply chain management (SCM) operational innovation at a global advanced manufacturing company. Previously, people manually collected and analyzed data dispersed across multiple systems to establish production plans. Under the agentic AI operating framework, various data are connected in real time, enabling immediate demand and inventory analysis. This makes it possible to dramatically shorten the time required to develop production plans. In the event of issues such as demand fluctuations or inventory shortages, AI agents collaborate to analyze the causes and derive response measures. SK AX reported that this can accelerate decision-making and enable flexible responses to real-time supply chain issues.

The industry expects that the capability gap between companies prepared for the era of agentic AI and those that are not will continue to widen. According to global consulting firms, companies that restructure their operations using agentic AI can achieve higher productivity innovation than those that do not, and can expect approximately double the revenue growth rate and cost reductions of more than 40%.

Cha Ji-won, SK AX’s Chief AI Innovation Officer (CAIO), said, “In the era of agentic AI, competitiveness is determined less by the performance of the AI model itself and more by the structure that enables its decisions to actually operate within corporate operations and workflows,” adding, “The AXgenticWire brand will maximize corporate decision-making and operational efficiency by expanding the ‘end-to-end enterprise AI full-stack execution framework’ that has already been validated in real industrial environments.”

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