Key to Promoting Generative AI in Education: Empowering 'Key Personnel on the Ground'

The Education Policy Committee of the Japan Junior Chamber Tokyo (公益社団法人東京青年会議所) hosted its February 2026 regular meeting titled 'Future Education Co-Created with AI' on Sunday, February 22, 2026, at Tokyo Innovation Base in Yurakucho. The event aimed to clarify needs and barriers regarding generative AI adoption in schools and provide insights for educational boards in formulating policies.

Participants included teachers, principals and vice principals, ICT coordinators, education board staff, general attendees, and members of the Japan Junior Chamber Tokyo. Discussions focused on the potential of generative AI in education, its impact on administrative efficiency, challenges to implementation, and strategies for school-wide adoption.

Key findings revealed in this report:

High interest and willingness to use generative AI exist in schools Participants expressed a positive attitude toward full-scale adoption, provided appropriate environments are established.

Essential requirements for implementation include rules, training, and secure usage environments Major challenges identified were internal consensus-building, staff training, guidelines, and cybersecurity measures.

The key to widespread adoption lies in engaging 'key personnel within schools' Approximately 67% of respondents indicated they could influence 'four or more colleagues,' suggesting that targeting school leaders and ICT coordinators could catalyze internal diffusion.

Current status of education field revealed by survey

Survey respondents included school teachers, school management, education board staff, school administrators/ICT coordinators, and university faculty.

Figure 1: Participant profiles

Regarding schools' current stage of generative AI adoption, the largest group reported already using AI in classrooms (including student use), indicating participation by individuals highly interested and motivated to adopt generative AI.

Figure 2: Current stage of generative AI adoption in schools

When asked when they would begin full-scale generative AI adoption if appropriate conditions were met, a high proportion responded 'immediately' or 'within three months,' confirming that many in the education field are already 'ready to act now.'

Figure 3: Desired timing for full-scale generative AI adoption

On the other hand, major barriers to adoption included:

Lack of knowledge about how to use generative AI

Difficulty gaining internal consensus

Psychological resistance due to lack of precedents

Unclear policies from education boards

Concerns about operational rules and security

Figure 4: Main barriers to generative AI adoption perceived by educators and requests to authorities

These results indicate that successful generative AI adoption requires more than just tool deployment—it necessitates establishing rules, training programs, shared case studies, and support systems that enable safe and confident use.

Requests from educators to government and education boards

Open-ended responses revealed honest concerns and requests from educators to authorities. The main points were:

1. Unified guidelines and clear definition of responsibilities Requests for standardized operational rules and manuals across districts, along with clear delineation of responsibility in case of issues.

2. Concerns about personal information, security, copyright, and misinformation Frequent calls for risk management regarding data leaks, copyright, accuracy of AI-generated content, and student misuse or overreliance.

3. Establishing safe usage environments for teachers and students Desire for closed-network environments, official accounts, and secure generative AI platforms accessible to both teachers and students.

4. Support for staff training and internal dissemination Need for improving teachers' AI literacy, promoting adoption among less interested or older staff, and supporting diffusion led by school administrators and ICT coordinators.

5. Reducing workload and addressing over-concentration in model schools Requests to expand AI use beyond a few pilot schools and to provide implementation support that considers the heavy workloads already faced by educators.

Insights: The key to promoting AI use lies in 'key personnel on the ground'

The most significant insight from this survey is the potential for 'key personnel within schools' to act as catalysts for spreading generative AI adoption.

While some teachers are enthusiastic about generative AI, many others hesitate due to reasons such as 'not knowing how to use it,' 'feeling uncertain,' 'lack of precedents,' or 'absence of guidelines.' Therefore, simply pushing blanket adoption across all staff may not lead to sustainable integration. Instead, if influential figures within schools—such as principals, vice principals, ICT coordinators, academic directors, and grade-level leaders—first experience the benefits of generative AI and share practical usage tips and cautions with colleagues, understanding and adoption can spread organically.

In this survey, about 67% of respondents said they could influence 'four or more colleagues,' suggesting early evidence that a 'one-to-many' diffusion model can be effective in promoting generative AI use.

Figure 5: Ripple effect: Number of colleagues whose practices can be influenced

The Education Policy Committee of the Japan Junior Chamber Tokyo will continue to prioritize this approach, moving beyond one-off seminars to build systems that empower key personnel to bring knowledge back to their schools and drive internal adoption.

Event Overview

Title: February 2026 Regular Meeting 'Future Education Co-Created with AI'

Date and Time: Sunday, February 22, 2026, 13:00–16:30

Venue: Tokyo Innovation Base (3-8-3 Marunouchi, Chiyoda City, Tokyo)

Organizer: Education Policy Committee, Japan Junior Chamber Tokyo (公益社団法人東京青年会議所)

Co-host: General Incorporated Association for Educational AI Utilization (一般社団法人 教育AI活用協会)

Under the auspices of: Tokyo Metropolitan Board of Education, Chuo City Board of Education, Suginami City Board of Education, Meguro City Board of Education, Kita City Board of Education, Adachi City Board of Education

Main lecture topics:

How to engage with generative AI

Generative AI use for teachers

From management to leadership—Creative school management course

Frontlines of educational digital transformation—How AI use is changing schools and leadership

Speakers: Satoshi Nakagawa (EdLog Inc.), Soichiro Hirai (Future Education Design LLC), Kazuhiro Fujiwara (Educational reform practitioner), Yuta Sato (Representative Director, General Incorporated Association for Educational AI Utilization)

Attendance statistics

Japan Junior Chamber Tokyo members and others: 278

General attendees: 92 (Breakdown: 44 teachers, 10 education board staff, 38 general public)

Survey Overview

Survey title: Survey on Intentions Regarding Generative AI Use in Educational Settings

Target: Teachers and education board staff who attended the February 2026 meeting 'Future Education Co-Created with AI'

Number of responses: 58

Method: On-site questionnaire

Note: This survey provides preliminary data on intentions from education professionals highly interested in generative AI and does not represent a statistically comprehensive survey of all educational institutions.

About Japan Junior Chamber Tokyo

Japan Junior Chamber Tokyo is an organization composed of young business leaders aged 20 to 40. It aims to achieve a 'bright and prosperous society' by addressing community challenges.

Inquiries

Education Policy Committee, Japan Junior Chamber Tokyo Contact: Daigo Torii Email: d-educational@tokyo-jc.or.jp

Download links

Preliminary Data on Generative AI Adoption Intentions in Educational Settings

35 Practical Ways to Use AI in Education