AI

SK Square Moves to Fully Integrate AI Into Investments and Affiliates' Services

AI TIMES ·

Kim Yong-hoon, head of AI Innovation at SK Square, explains SK Square's AX (AI transformation) strategy. [Photo: SK Square]

✦ AI Summary

According to AI TIMES, SK Square said on September 10 that it has begun in earnest its transition to an 'AI-native' investment company that…

According to AI TIMES, SK Square said on September 10 that it has begun in earnest its transition to an 'AI-native' investment company that places AI at the center of its investment work and portfolio business models. About 80 employees are currently building and applying more than 90 AI agents directly in their day-to-day work, changing both investment review and organizational operations. Centered on its newly established AI innovation organization, the company is creating a system that allows people to freely use a range of AI models and building an internal knowledge hub that links individual work results to the organization’s assets. In the investment area, it aims for a structure in which AI handles repetitive tasks while people focus on judgment, verification, and high-difficulty decision-making. At the same time, it has seen improvements in operating efficiency and profitability at portfolio companies based on workflow automation results, and a move to extend that experience across the group’s ICT services has also become clear. In the end, SK Square appears to be laying out a strategy to make AI not a support tool, but the basic framework for operating an investment company and innovating affiliate services.

Perspective

The key point of this move is not to confine AI adoption to a few pilot projects, but to rebuild both the investment decision-making system and the service operating structure. If that happens, the basis of competition is also likely to shift from simply possessing technology to how much actual work design and decision-making speed can be changed. In particular, if the automation of repetitive tasks and the shared use of knowledge move forward together, productivity gains will not stop at one-time cost savings but will also shape the organization's learning speed. In the industry, this is being read as a signal that the companies that redesign the work itself around AI, rather than merely using AI well, may move ahead.

This perspective is BizCrush's own commentary and is not part of the reporting by AI TIMES.

This article was produced with the help of an automated content generation algorithm.


Source: AI TIMES

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