[Survey Release] Differences in Behavior and Systems Between Members and Non-Members of the Architectural AI Management Research Group — Clear Gaps in Employee AI Education Investment, Organizational AI Utilization, and Company Adoption Rate of Claude.

In the construction industry, the key management challenge regarding AI has shifted from "Where should we start?" three months ago to "How do we achieve internal adoption?" today.

The Architectural AI Management Research Group, operated by LIFEFUND Inc. (Hamamatsu City, Shizuoka Prefecture; CEO: Takuma Shito), has published a comparative report analyzing its June 2026 AI utilization survey targeting construction and building industry executives (n=31), splitting respondents for the first time into research group members (n=17) and non-members (n=14).

Previously, results were reported as aggregate data across all participants. This is the first time a comparison has been made specifically between "members" and "non-members," providing multidimensional insights into differences in AI adoption stages, tool implementation, employee support, and needs.

*This comparison is based on responses from 31 participants in the June 2026 survey, divided into 17 members and 14 non-members. Due to the small sample size, figures should be interpreted as indicative trends.

Why Compare Members vs. Non-Members Now?

Launched in 2025, the Architectural AI Management Research Group has held four sessions to date, with cumulative participation exceeding 200 companies. The most recent fourth session recorded an overall satisfaction rate of approximately 90%. However, until now, there was no objective numerical evidence to answer the question: "What actual changes occur from participation?"

The June 2026 survey adds a new layer of analysis by segmenting respondents into "research group members (executives from participating companies)" and "non-members," revealing differences in AI adoption practices based on participation status within the same survey and timeframe.

Five Key Numerical Differences Highlighting the "Participation Gap"

① AI Use Shifts from "Individual" to "Organizational" — +33.6pt Difference in Level 2+ Adoption

The proportion of respondents achieving "Level 2 or higher AI utilization"—encompassing organizational use and company-wide deployment—was 76.5% among members versus 42.9% among non-members (+33.6pt). Those remaining at the individual-use stage ("Level 1") were 23.5% of members and 57.1% of non-members, indicating that a majority of non-members are still in the individual phase. Despite nearly identical employee size and industry composition, a significant gap in organizational AI adoption is evident.

Members of the Architectural AI Management Research Group demonstrate higher AI utilization levels compared to non-members, with a difference exceeding 1.5 times when expressed numerically.

② Significant Differences in Tool Adoption Rates — +38.2pt for Claude, +40.0pt for Internal Education Investment

The rate of paid company-wide adoption of Claude was 88.2% among members versus 50.0% among non-members (+38.2pt). For paid corporate ChatGPT, the rates were 64.7% (members) and 28.6% (non-members) (+36.1pt). The rate of paid personal use of Claude by executives was 94.1% (members) versus 57.1% (non-members) (+37.0pt). Investment in "internal education and training for AI talent development" also showed a large gap: 47.1% of members versus 7.1% of non-members (+40.0pt).

The rate of paid company adoption of Claude is 88.2% for members and 50.0% for non-members (+38.2pt). A significant difference in Claude adoption rates is evident.

The rate of paid personal use of Claude by executives is 94.1% for members and 57.1% for non-members (+37.0pt). A significant difference in Claude usage rates is evident.

③ Different Management "Barriers" — Members Face "Adoption Phase Challenges," Non-Members Haven't Tried Enough to Encounter Barriers

Top barriers cited by members were "unclear priorities" (35.3%) and "field staff and employees not keeping up" (29.4%)—challenges that arise precisely because they are already engaged in AI initiatives. In contrast, the top response from non-members was "no particular barrier felt" (35.7%), indicating that their AI efforts are still shallow and they haven't tried enough to encounter significant obstacles.

Members perceive challenges in spreading AI to the field and employees, while a majority of non-members report not feeling any barriers.

④ Large Differences in Employee Support — 70% of Members Provide Financial Support

Financial support for employee AI use (full or partial cost coverage) was provided by 70.6% of member companies versus 42.9% of non-members (+27.7pt). The proportion doing "nothing (leaving it to individuals)" was 5.9% for members versus 57.1% for non-members—a complete reversal. Member companies position AI not as a "personal tool" but as an "organizational investment."

There are clear differences in trends between members and non-members. Treating AI use as "up to the individual" is notably prevalent among non-member companies.

⑤ Different Needs: "Practical Deepening" vs. "Implementation Guidance"

When asked what they need most right now, the top response from members was "a practical setting to learn AI" (47.1%), while non-members most frequently selected "success stories and roadmaps" (57.1%). Members are in a stage seeking to deepen practice, while non-members are in a stage wanting to know where to begin—highlighting a clear difference in AI adoption maturity.

Members are proactive in securing and developing AI talent. Additionally, members seek practical learning environments for AI, while non-members tend to seek success stories.

What the Data Reveals: The "Value" of the Research Group

These five differences do not imply a direct causal relationship—"participation automatically leads to these outcomes." There is a natural tendency for executives already proactive in AI adoption to join the research group. However, the fact that gaps of 20–40pt exist across organizational AI use, employee support, and tool adoption—despite nearly identical company size and industry composition—serves as circumstantial evidence that participating companies are experiencing some form of transformation.

Notably, there is a reversed data point: the proportion who answered "AI is already a weapon changing performance" was 5.9% among members versus 35.7% among non-members (–29.8pt), meaning non-members include more executives who already feel tangible results. The research group appears to attract many executives who "believe AI is a weapon but have not yet linked it to performance" (76.5% of members fall into "believe it's a weapon but can't fully utilize it"). This explains their strong desire for practical learning environments (47.1% of members seek "a place to learn").

Both groups share a proactive investment stance (52.9% of members and 50.0% of non-members both answered "no barriers, decision made"). This reveals that forward-thinking executives in the construction industry, whether in the "participation-driven organizational adoption" group or the "early results-achieving" group, are engaging with AI management with equal passion.

The Architectural AI Management Research Group attracts many executives who are actively practicing AI use or are in the internal adoption phase. Beyond knowledge-sharing sessions like AI workshops for executives and case studies from leading companies, the bi-monthly meetings include networking opportunities such as communication time and receptions where around 100 participants exchange business cards and share AI utilization insights. Participation in the research group is valuable as a rare opportunity to meet AI-proactive executives and experience the forefront of AI application firsthand.

Survey Overview

Survey Name: Architectural AI Management Status Survey – Member vs. Non-Member Comparative Report (June 2026)

Conducted by: Architectural AI Management Research Group (Operated by LIFEFUND Inc.)

Target: Executives in the construction and building industry

Survey Date: June 3, 2026

Valid Responses: n=31 (Members n=17, Non-members n=14)

Question Structure: 19 comparative questions

Respondent Profile: Employee size and industry composition are nearly identical across both groups

(Companies with 2–29 employees comprise ~77%; primarily construction firms and renovation companies)

*Due to the small sample size, figures should be interpreted as trends.