SK Telecom Launches CEO-Led AI CIC to Sharpen Strategy and Unify Products, Partnerships, and Data Centers
SK Telecom forms an AI CIC led by CEO Yoo Young-sang to sharpen strategy and speed delivery. It unifies products, partnerships, infrastructure, and talent.
Published on: Sep 26, 2025
SK Telecom creates AI CIC led by CEO Yoo Young-sang to sharpen strategy
Seoul, 25 Sep - SK Telecom announced a new Company in Company (CIC) focused on AI, to be led directly by CEO Yoo Young-sang. The move consolidates the operator's AI initiatives under one leadership structure to tighten execution and speed up delivery.
The AI CIC unifies workstreams across customer-facing products, global partnerships, data center operations, and internal AI adoption. It also covers upgrades to internal systems and workforce capability so teams can build, deploy, and scale AI consistently.
Scope of the new AI CIC
- Consumer and enterprise AI products and services
- Global partnerships and ecosystem development
- Data center and infrastructure strategy for AI workloads
- Internal AI innovation, process automation, and tooling
- Employee upskilling and AI capability building
Why this matters for executives
- Clear ownership: one accountable leader to set priorities and resolve trade-offs
- Faster cycle times: shared roadmap, shared metrics, fewer handoffs
- Commercial focus: tighter link between AI investment, infrastructure, and monetization
- Talent leverage: centralized standards, platforms, and training to reduce duplicated effort
What to watch next
- Operating model: decision rights, funding model, and P&L treatment for the CIC
- Infrastructure: data center capacity plans and partnerships for compute and models
- Product pipeline: generative services for consumers and B2B vertical offers
- Capability building: internal AI academy and measurable productivity gains
Action checklist for telecom and enterprise leaders
- Appoint a single executive owner for AI with end-to-end delivery authority
- Create a CIC-like unit or virtual business unit to centralize AI platforms and standards
- Tie data center planning to AI product roadmaps and cost-to-serve targets
- Stand up an internal AI academy and set adoption KPIs by function; consider curated training resources such as role-based AI courses
- Establish a common architecture review board and a product ops cadence (quarterly priorities, monthly demos, weekly metrics)
- Measure impact with a simple scorecard: time-to-value, active usage, unit economics, and ARR from AI-enabled products
