Recently, the share of artificial intelligence (AI·Artificial Intelligence) items on the boards of major domestic corporations has been increasing. Major corporations including Samsung Electronics(005930), SK hynix(000660), and Hyundai Motor(005380) are putting Generative AI (AI technology that creates new content such as images and code using existing data) investment and organizational transformation at the core of their future growth strategies. AI is no longer a project of the technology department but a management agenda that determines corporate value and competitiveness.
The recent trend has accelerated further. After Nvidia CEO Jensen Huang's visit to Korea, cooperation talks between major domestic groups and global AI companies came to the fore, and SK Telecom(017670) said it would partner with Nvidia to enter the "full-stack AI cloud" business based on AI factories. As AI infrastructure investment gains steam, corporations are facing twin pressures to both speed up investment and prove results. The burden is growing along with the investment fever.
As AI investment announcements, data center build-outs, and Generative AI service launches continue, market expectations are rising. But the timing of actual monetization remains uncertain. In business circles, the view is spreading that "not doing AI is a risk, but investing poorly is also a risk."
◇ CEOs and boards split over the pace of AI adoption
A report released by Boston Consulting Group (BCG), "CEOs and Boards Are Aligned on AI in Theory, but Divided in Practice," illustrates this reality. While CEOs and boards agree on the importance of AI, they show significant differences in views on how to execute, at what speed, and how to structure responsibility.
The biggest gap appeared in the pace of AI adoption. According to the survey, about 60% of CEOs feel boards are rushing AI transformation too much, while boards believe corporations are not moving fast enough.
BCG explains this as an "AI FOMO (fear of missing out)" phenomenon. The less people understand AI, the greater the anxiety about falling behind, which can lead to more aggressive investment pressure.
There was also a gap in AI literacy. Seventy-five percent of board members said their understanding of AI was similar to or higher than that of their fellow directors. But 40% of CEOs said boards overestimate the areas where AI can actually be applied or do not fully understand the impact AI will have on growth strategies.
◇ AI strategy is for management, but execution burdens fall on the CEO
The issue is the structure of responsibility. Both CEOs and boards said the management team should lead AI strategy, but in practice the burden of execution was concentrating on the CEO.
In the survey, 47% of CEOs said they are directly leading the execution of AI strategy. By contrast, the share who said the chief AI officer (CAIO) should lead AI strategy fell short of 10%.
AI is a management task that simultaneously touches organizational structure, capital allocation, workforce operations, and business model transformation. Domestic corporations are increasingly creating new AI units or reorganizing them under the CEO, but the burden of final decision-making still often concentrates on the chief executive.
A notable gap also appears in perceptions of AI investment performance. CEOs recognized that, on average, 35% of their performance evaluations are tied to AI investment results, while boards put that figure at around 27%. This suggests the pressure CEOs feel on AI performance is much greater than boards perceive.
Recently, domestic corporations have likewise experienced rising market expectations following AI investment announcements, data center construction, and Generative AI service launches. But the timing of actual monetization remains uncertain. In the end, from the CEO's standpoint, it amounts to simultaneously managing the "risk of not doing AI" and the "risk of overinvesting without results."
BCG noted that the risks of AI transformation can grow more from the perception gap between CEOs and boards than from the technology itself. The greater the divergence in views on the pace of AI adoption, expected return on investment (ROI), and responsibility structures, the more likely AI strategy will become a source of internal conflict rather than a driver of innovation.
The market is now starting to ask not about the size of AI investments, but who will be accountable and when results will be delivered. In the AI era, competitiveness is more likely to hinge not on which technology is adopted but on the structures that decide where to apply it and how to connect it to revenue. What CEOs need is not a declaration about AI but decision-making that manages investment, execution, and results all at once.