Generative AI Has Shifted from an “Option” to a “Survival Necessity”
PwC’s “Generative AI Reality Survey 2026 Spring: A 6-Country Comparison” presents startling data: AI transformation is no longer a “choice” for companies—it has become a “survival condition.”
What stands out in this survey is Japan’s position. Among the six countries, Japan’s generative AI adoption rates are consistently low. The gap is especially pronounced in executive commitment and company-wide strategy development compared to other nations.
However, I don’t want to end this news on a pessimistic note of “Japan is falling behind.” Rather, I believe this is where executives can truly showcase their skills in turning things around.
Why? Because the essence of AI adoption isn’t “whether you’ve introduced it,” but “how you master its use.” At our company, we generate approximately $50,000 USD in annual value at a monthly cost of about $140 USD. This fact demonstrates that a strategy of starting small and scaling up is effective.
Three Misconceptions Trapping Japanese Companies
The Illusion of “Company-Wide Implementation First”
Many Japanese companies scramble to formulate a “company-wide AI strategy.” But as the PwC survey shows, a strategy alone doesn’t boost on-the-ground usage rates.
The case of Shizuoka Prefectural Government is instructive. Their AI adoption rate, reported in a digital strategy meeting, stands at 56.1%—a respectable figure. Their approach of “building a solid model in Shizuoka for integrating AI into operations” highlights the importance of accumulating success stories rather than enforcing a one-size-fits-all policy.
What executives should do is not force AI on the entire organization. First, they should use AI themselves and experience its effects. I personally use three AIs—Claude, ChatGPT, and Grok—in my daily work. Executives becoming practitioners is the first step toward organizational transformation.
The Shortsighted Thinking of “AI = Cost Reduction”
The idea that “introducing AI will cut labor costs” is dangerous. Yes, operational efficiency is a major benefit of AI adoption. But if that’s the only goal, the organization will resist AI implementation.
Another PwC report, “The Overwhelming Productivity of Individuals Augmented by AI Agents,” points to a shift toward the “Augmented Enterprise.” This is about augmenting human capabilities, not replacing humans with AI.
In our own case, when we introduced automated contract review, the legal team worried about “losing work.” But in reality, by having AI handle the initial checks, team members could focus on higher-level negotiations and strategic tasks. As a result, the entire team’s productivity tripled.
The Assumption That “AI Adoption = SaaS Adoption”
Many executives think “adopting AI means signing up for some convenient SaaS.” However, true AI adoption means breaking free from SaaS dependency.
At our company, we use Claude Code to build our own automated pipelines. From automated social media posts, WordPress article generation, video pipelines, contract reviews, to FX trading—we’ve developed and operate 93 use cases across 29 business areas in-house.
The development barrier has dropped dramatically. With code-generation AI, even non-engineers can create simple automation tools. In many cases, building it in-house once is cheaper in the long run than paying thousands of dollars monthly for SaaS subscriptions.
Three Concrete Strategies for a Comeback
Executives Become “AI Practitioners”
The first step is for executives themselves to fully leverage AI. I recommend the following three steps:
First, use ChatGPT or Claude for daily email and document creation. Second, develop the habit of constantly asking, “Can AI handle this?” in your workflow. Finally, create opportunities to share these insights with your team.
The key is not for executives to say “use AI,” but to show themselves “using it.” This alone can dramatically improve the organization’s AI literacy.
Accumulate “Small Success Stories”
Before aiming for company-wide adoption, create success stories in one department or one task. Shizuoka Prefectural Government’s approach is exactly this.
Specifically, I recommend starting with small automations like these:
・Let AI handle daily social media posts (time required: 1 hour → 5 minutes)
・Automate meeting minutes (time required: 30 minutes → 0 minutes)
・Auto-reply to common inquiries (response time: 1 hour/day → 1 hour/month)
These small successes reduce organizational resistance to AI adoption and fuel the next steps.
View It as an “Investment,” Not a “Cost”
The cost of AI adoption is far lower than you think. At our company, we operate 93 use cases for about $140 USD per month. This translates to approximately $50,000 USD in annual value creation, based on labor cost savings.
The entry barrier is also low. ChatGPT Plus costs $20 USD per month, and Claude Pro is similar. Start with a personal investment of $15–$20 USD per month, experience the benefits, and then scale up.
You can also leverage subsidies. But if you start with subsidies as a prerequisite, you won’t build a sustainable operational structure. First, start small with your own funds, confirm the effects, and then expand. This order is crucial.
To Win the AI Survival Race
The PwC survey sounds an alarm for Japanese companies. But this is by no means a reason for despair. Rather, if we commit seriously from now, we are in a position to make a strong comeback.
What matters is not a “perfect strategy” but the “first step.” Executives using AI, accumulating small successes, and realizing the return on investment. Only companies that faithfully execute this simple process will survive the next era.
AI is no longer a “nice-to-have.” It has become a “must-have to survive.” Right now, open an AI app on your smartphone and delegate one of today’s tasks to it. That single step could determine your company’s fate.
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