The success or failure of AI investments will depend not on size, but on human capabilities and organizational maturity.

Global research firm Gartner predicted on the 16th that global AI spending will reach $2.5278 trillion (approximately KRW 3,736 trillion) in 2026, a 44% increase from the previous year.

Gartner analyzed that AI will no longer be spread around individual projects, but will evolve in a way that naturally permeates existing software and platforms.

Gartner cited human capabilities and organizational maturity, rather than financial scale, as key factors determining AI investment performance.

This means that simply increasing the budget will not maximize the effectiveness of AI adoption; it is essential to improve internal processes and strengthen human resources capabilities.

“AI adoption depends on an organization’s level of preparedness,” said John-David Lovelock, a senior vice president and analyst at Gartner. “More mature organizations are realigning their AI strategies to focus on proven performance rather than uncertain potential.”

He continued, “AI will be & by 2026“It is highly likely that we will remain in the ‘valley of disillusionment’ phase,” he said, adding that “companies will adopt AI by expanding functions through software vendors they are already using rather than pursuing individual AI projects.”

In other words, the analysis is that the trend of AI being naturally integrated into existing work systems rather than being an independent project is strengthening.

“For AI to spread across the enterprise, there needs to be predictable return on investment (ROI),” Lovelock said. “Proven software-based AI capabilities will spread faster than experimental projects with high uncertainty.”

As AI adoption spreads, AI infrastructure spending is also expected to increase explosively.

Gartner predicts that spending on AI-optimized servers will increase by 49% year-over-year, driven by the expansion of AI-based deployments. This represents approximately 17% of total AI spending.

Additionally, AI infrastructure spending is expected to increase by approximately $401 billion year-over-year as technology companies expand their AI-based infrastructure.

This trend demonstrates the continued growth in demand for high-performance infrastructure for AI model learning and inference.

In this outlook, Gartner emphasized that the fundamental challenge in adopting AI is not the technology itself, but rather organizational readiness and human capabilities.

For AI to become a reality across the enterprise, it requires a strategy of integration with existing software and business processes, not a one-off project. The human resources and organizational structure to support this strategy must be in place.