Why now
Why now — use is spreading, and judgment about how to use it matters
Generative AI is being used more and more, by individuals and by companies. We make no sweeping claims here; we show only primary sources from public bodies.
Adult skills compared internationally — Japan ranks high
PIAAC Cycle 2 (2022-23 fieldwork, published 2024-12-10; 31 countries/economies, ~160,000 adults): Japan ranked 2nd in both literacy (289) and numeracy (291). Across the OECD, only Finland and Denmark showed statistically significant literacy gains; the bottom 10% of performers declined while the top 10% improved, widening within-country inequality
EU AI Act, Article 4 — AI literacy
EU AI Act (Regulation (EU) 2024/1689) Article 4: providers and deployers of AI systems shall take measures to ensure, to their best extent, a sufficient level of AI literacy of staff and other persons operating/using AI systems on their behalf. Per Article 113(a), Chapters I and II (which include Article 4) apply from 2 February 2025. This is EU law and does not automatically apply to companies in Japan.
Growth in personal use of generative AI, compared internationally
Individual generative-AI usage experience in Japan: 26.7% (FY2024 survey) to 58.8% (FY2025 survey). FY2024 international comparison: US 68.8% / Germany 59.2% / China 81.2%
Japan’s fundamentals are strong. Precisely because of that: even strong fundamentals rust when unused.
What the research says
Concern about new tools is old; the answer is judgment about how to use them
There is no public statistic that shows people "stopped thinking because of AI". What we do know is that there are patterns in how people relate to automation — and that someone has to be able to judge what to delegate.
Figure: four ways of relating to automation (Parasuraman & Riley 1997). The aim is the top left — deciding for yourself when to use.
"Won’t writing weaken memory?" — concern about new tools is 2,400 years old (a classical analogy).
Plato, Phaedrus 274c–275b
A wealth of information creates a poverty of attention.
Simon 1971
The more we automate, the harder the role left to the human becomes.
Bainbridge 1983
People relate to automation in four ways: use, misuse, disuse and abuse.
Parasuraman & Riley 1997
Handing thinking work to a tool (cognitive offloading) can help — when used well.
Risko & Gilbert 2016
The effect of AI is uneven; it depends on the task and on the person’s skill level.
Brynjolfsson, Li & Raymond 2025; Dell’Acqua et al. 2025
Used by tools, or using them
Used by the tool, or using it — in everyday work
We don’t dismiss AI or social media as tools. The difference lies in who decides what gets delegated.
Meeting notes
Estimates and plans
Explaining to a customer
Code and documents
These examples are our suggestions. In training we build them together from your own work situations.
How we can help
How we can help — with our existing services
We do not sell an AI-specific product. Our existing training and coaching support "organizations where everyone can think" and "a culture that masters its tools" (a proposal, not a description of past results).
TRAINING = CLEAR THEORY Customized Training
Using your own work situations, people — including non-IT teams — learn to judge what to delegate, how to check, and how to put assumptions into words. Built from scratch on request.
TRAINING = PUBLIC COURSE Systems Thinking
Learn to see the connections in the whole rather than the parts — for one or a few people.
COACHING = SUPPORT GROUNDED IN REALITY Coaching
We observe real work and give feedback until deciding for yourself becomes a habit.
Key points for your internal brief
Use as a draft for an internal proposal (our suggestion; take figures only from the public-statistics slots).
- Premise
- Generative AI use is spreading. We do not claim people "stopped thinking". Fundamentals are strong — and rust when unused.
- Problem
- The criteria for what to delegate to tools are left to each individual.
- Approach
- Align the criteria through training built on real work situations; make them a habit through coaching.
- Target state
- Each person can decide what to delegate and how to check.
- Evidence
- The reference list at the end of this page (author, year) and the public statistics shown on this page (MIC Japan; OECD / NIER; Official Journal of the EU).
Theory behind this page
- Plato, Phaedrus 274c–275b
- Simon 1971
- Bainbridge 1983
- Parasuraman & Riley 1997
- Risko & Gilbert 2016
- Brynjolfsson, Li & Raymond 2025
- Dell’Acqua et al. 2025
Full list: Theoretical background and sources
We Promote Improvement
The first consultation is free. We listen to your challenges and goals, then propose what fits best.
Get Your Certification
One or a few people? Start with a public course — certified training and Systems Thinking are open for booking.