The IT talent shortage has long been discussed as a challenge in Japan's tech industry. In a 2019 survey, Japan's Ministry of Economy, Trade and Industry (METI) warned that the country could face a shortfall of up to 790,000 IT workers by 2030. Against this backdrop, a Japan-focused survey released by the Linux Foundation on July 29, 2026, at KubeCon + CloudNativeCon Japan (Pacifico Yokohama) reveals a surprising set of figures. Japan's AI-related hiring growth rate is set to reach 54% in 2026—roughly double the global average of 26%—yet only 13% of companies (compared to 53% globally) have dedicated AI personnel. Securing volume and shifting toward quality are advancing at very different speeds.
AI-Related Hiring Growth Accelerates to 54% in 2026
On July 29, 2026, the Linux Foundation released its "2026 State of Tech Talent Japan" report to coincide with KubeCon + CloudNativeCon Japan (July 28–30, Pacifico Yokohama). The survey covered 400 hiring, training, and talent management leaders in Japan, marking the latest edition of the Japan-specific report published for three consecutive years since 2024. The Foundation had also published a Japanese translation of its global report in June 2026, but that version contained data from respondents worldwide and did not include Japan-specific figures. This is the first time the survey has presented concrete numbers on AI talent trends specific to Japanese companies. KubeCon + CloudNativeCon Japan is one of the largest domestic conferences for cloud-native engineers, and it has become a key venue where the Linux Foundation shares annual insights on the Japanese market.
According to the report, the net increase in AI-related hiring in Japan is projected to reach 50% in 2025, 54% in 2026, and 35% in 2027. Over the same period, the global average stands at just 20%, 26%, and 18%, meaning Japan's growth rate is tracking at nearly twice the pace. Meanwhile, the share of Japanese companies anticipating AI-driven workforce reductions is expected to fall from 16% in 2025 to just 3% by 2027, while the global figure is projected to rise from 13% to 22% over the same period—moving in the opposite direction. This paints a picture in which Japanese companies view AI not as a tool for workforce reduction but as a tailwind for hiring expansion. However, the report does not disclose a breakdown of respondents by industry or company size, nor the survey's exact fieldwork period.
The hiring growth rate for entry-level technical roles in Japan has also reached 46%, a trend that stands in contrast to other regions. Based on the numbers alone, Japanese companies' appetite for AI hiring stands out globally.
Despite Hiring Growth, Only 13% Have Dedicated AI Talent
Despite the momentum in hiring, only 13% of Japanese companies have dedicated AI personnel—roughly a quarter of the 53% global average. Similarly, only 18% of companies have dedicated staff for DevOps, CI/CD, and SRE (Site Reliability Engineering, an integrated approach to continuous integration and delivery that unifies development and operations), suggesting the same pattern extends beyond AI into other specialized domains. If companies advance AI adoption without a robust dedicated structure for DevOps or SRE, they are likely to fall behind in continuous model updates and incident response as well. In companies without dedicated AI personnel, existing engineers are, in practice, shouldering AI-related decision-making and operations alongside their original responsibilities.
Looking at specific areas of shortage, 52% of companies cited a lack of talent for AI operations and monitoring, while 49% cited a shortage in AI security and risk management. Twenty-nine percent of companies also identified a lack of infrastructure skills as a major challenge. Even as hiring numbers grow, the reality is that specialized personnel capable of safely operating and monitoring AI systems are not keeping pace.
As the 18% dedicated-staff rate for DevOps and SRE shows, thin dedicated structures are a trend shared across operational domains beyond AI—and if this situation persists, the shortage of personnel for AI operations/monitoring and security/risk management is likely to become even more pronounced. These figures suggest a structural challenge that simply increasing hiring numbers will not resolve.
Organizing this picture with numbers makes the contours clearer. The share of companies without dedicated AI personnel is 87% in Japan versus 47% globally—meaning the proportion of "no dedicated talent" companies in Japan is roughly 1.9 times the global figure. This is nearly the same scale of disparity as the hiring growth rate gap (54% vs. 26%, roughly double). The conventional wisdom that "there isn't enough AI talent" has already been disproven in terms of sheer numbers. What's lacking isn't headcount so much as dedicated, specialized expertise itself.
Why Companies Prioritize Reskilling Inexperienced Staff Nine Times Over Hiring Ready-Made Talent
Japanese companies are nine times more likely to choose upskilling existing employees (improving skills through relearning) over hiring externally sourced, ready-to-deploy talent. Training periods allocated to new hires take 81% longer than upskilling periods for existing employees. Furthermore, 46% of new hires leave within six months of joining, meaning external hiring carries both training costs and retention risk.
Talent brought in from outside takes longer to train, and nearly half leave within six months of joining. Placing these two figures side by side, it follows naturally that investment in internal development is easier to recover than external hiring. The talent management model Japanese companies have built around long-term employment and in-house development tends to have an advantage in the efficiency of internal investment, precisely because external labor market mobility is lower. This preference appears to be showing up numerically even in the new specialized domain of AI talent. For individuals aiming to become AI talent, choosing a company that offers upskilling opportunities—rather than pursuing a job change as ready-made talent—may also be the environment more conducive to staying with a company long-term.
A "From Quantity to Quality" Shift That Overlaps with METI's Forecast of a 790,000-Worker Shortfall
According to a 2019 METI survey reported by Nikkei, Japan is projected to face a shortfall of up to 790,000 IT workers by 2030. The shortage was expected to be especially severe in advanced fields such as AI and cloud. That forecast was premised on a crisis of quantity—simply not having enough people.
Overlaying the Linux Foundation's latest survey results changes the picture. METI's figure of 790,000 is a projected stock shortfall as of 2030, while the Linux Foundation's 54% represents an annual hiring growth rate (a flow), so the two cannot be directly compared. That said, the pace of hiring itself has not slowed, and these numbers show that the effort to increase headcount is not stalling. At the same time, the 13% dedicated-talent rate reflects a reality in which, even as hiring numbers grow, the conversion into personnel with genuine specialized expertise is not keeping pace. This suggests that resolving the 790,000-worker crisis of quantity will require not just securing headcount but also a qualitative shift toward specialization.
METI's 2019 forecast also targeted shortages limited to advanced fields such as AI and cloud. Seven years later, the specific shortages identified in this latest survey—AI operations/monitoring and AI security/risk management—are precisely those advanced, specialized roles. It could be said that the warning long framed as a crisis of quantity always contained within it a crisis of quality.
The Linux Foundation's Japan-focused report has been published annually since 2024. The 2025 edition found that over 70% of companies cited a cloud talent shortage, and 94% said they prioritize upskilling. The shift in focus this year—from cloud talent broadly to full-stack AI skills specifically—suggests that Japanese companies' concerns have moved from "how do we secure cloud talent" to "how do we cultivate personnel who can handle AI at a specialized level." Because survey targets and question design change from year to year, a straightforward numerical comparison isn't possible, but the shift in focus itself reflects a change in the industry's priorities.
Talent Underpinning Sovereign Technology: The Next Challenge
Speaking to coincide with the report's release, Noriaki Fukuyasu, Vice President of Operations at Linux Foundation Japan, said, "Japan has never lacked technical ambition, but it has faced a chronic shortage of IT talent. AI is driving domestic hiring at nearly twice the global average pace, and behind this lies one of Japan's strengths: investment in upskilling existing talent." He further noted that the rapid evolution of AI has pushed the securing of sovereign AI (AI infrastructure developed and operated under domestic leadership), infrastructure, and data "sovereignty" beyond the stage of an aspirational goal into an operational necessity, adding, "Securing the specialized talent to control one's own technology stack is now an urgent priority." This statement can be seen as another way of framing the very challenge this report highlights: how to build up specialized expertise while sustaining hiring momentum.
Even if the hiring momentum Japanese companies have shown over the past year cannot on its own resolve the "quantity shortage" METI warned of in 2019, it has at least proven that the country has the capacity to grow its workforce. What remains is the challenge of how to redeploy hired talent into specialized domains such as AI operations/monitoring (52% shortage) and AI security/risk management (49% shortage). Raising the dedicated-personnel rate from the current 13% to the global average of 53% would, by simple arithmetic, require roughly quadrupling the number of companies with dedicated personnel in place. The strength Fukuyasu pointed to—Japanese companies' investment in upskilling existing talent—offers a clue to that path forward. If the ninefold preference for internal development over external, ready-made hires is directed specifically at shortage areas like AI operations/monitoring and security/risk management, hiring momentum could translate into a substantive increase in specialization.
Given that the Linux Foundation itself provides training and certification programs, this report also serves as material that reinforces the Foundation's own business opportunities. Even so, the picture the numbers paint doesn't change: Japan's AI talent strategy is entering its next phase, moving from securing quantity to a qualitative shift toward specialization.