CIMTOPS Co., Ltd. (Headquarters: Shinagawa-ku, Tokyo; Representative Director: Kazuyuki Okuhata), provider of the No. 1 market share* on-site form system "i-Reporter" in Japan, conducted a survey on the actual state of AI agent utilization in the manufacturing industry targeting 111 individuals in charge of DX and AI promotion at manufacturing companies with 500 or more employees. The survey revealed that both the preparation of on-site data and human resource development are indispensable for expanding results.

01 | Over 90% of DX/AI Promotion Managers Have Started Utilizing AI Agents

02 | 86.4% in the Implementation/PoC Stage Feel "Results are Being Achieved"

03 | Biggest Challenge for Utilization Promotion: "Lack of Internal Staff Who Can Master It" is Most Frequent at 46.6%

Download this survey here: https://application.i-reporter.jp/download.research22

Survey Overview

Survey Name: Survey on the Actual State of AI Agent Utilization in the Manufacturing Industry

Survey Method: Internet survey conducted as part of the research marketing "Resapii®︎" provided by IDEATECH

Survey Period: June 18, 2026 - June 19, 2026

Valid Responses: 111 individuals in charge of DX and AI promotion at manufacturing companies with 500 or more employees

* The sum may not be exactly 100 due to rounding of figures to two decimal places.

≪Usage Conditions≫

1. Please clearly state "i-Reporter" as the source of information.

2. When using on a website, please include the following link as the source.

URL: https://i-reporter.jp/

Over 90% of DX/AI Promotion Managers Have Started Utilizing AI Agents, with Implementation at 44.1% and PoC at 48.6%, Indicating Full-Scale Initiatives

When asked, "Q1. Please select the one option that best describes the current stage of AI agent utilization initiatives at your company." (n=111), the responses were "Fully implemented and in operational use" at 44.1% and "Engaged in PoC (Proof of Concept) stage" at 48.6%.

Q1. Please select the one option that best describes the current stage of AI agent utilization initiatives at your company.

・ Fully implemented and in operational use: 44.1%

・ Engaged in PoC (Proof of Concept) stage: 48.6%

・ In the consideration stage, not yet implemented: 4.5%

・ Not particularly engaged: 2.7%

・ Don't know/Cannot answer: 0.0%

Business Areas with Advancing Utilization and Consideration: "Manufacturing Line Maintenance/Predictive Maintenance" is Most Frequent at 55.6%, with Equipment-Related Operations at the Forefront of AI Utilization

When asked, "Q2. For those who answered anything other than 'Not particularly engaged' or 'Don't know/Cannot answer' in Q1, please tell us the business areas where you are utilizing (or considering utilizing) AI agents at your company. (Multiple answers allowed)" (n=108), the responses were "Manufacturing line maintenance/predictive maintenance" at 55.6%, "Optimization of production planning/production management" at 49.1%, and "Inventory management/procurement operations" at 42.6%.

Q2. For those who answered anything other than 'Not particularly engaged' or 'Don't know/Cannot answer' in Q1, please tell us the business areas where you are utilizing (or considering utilizing) AI agents at your company. (Multiple answers allowed)

・ Manufacturing line maintenance/predictive maintenance: 55.6%

・ Optimization of production planning/production management: 49.1%

・ Inventory management/procurement operations: 42.6%

・ Quality control/inspection in manufacturing sites: 36.1%

・ Sales/customer support: 34.3%

・ Document creation/internal business efficiency improvement: 28.7%

・ Design/development support: 22.2%

・ Other: 0.0%

・ Don't know/Cannot answer: 0.0%

86.4% of Managers Feel "Results are Being Achieved" with AI Agent Utilization in Implementation/PoC Stages, Entering a Phase Where Investment Yields Tangible Returns

When asked, "Q3. For those who answered 'Fully implemented and in operational use' or 'Engaged in PoC (Proof of Concept) stage' in Q1, are you achieving the results you initially expected with AI agent utilization at your company?" (n=103), the responses were "Sufficiently achieved" at 25.2% and "Somewhat achieved" at 61.2%.

Q3. For those who answered 'Fully implemented and in operational use' or 'Engaged in PoC (Proof of Concept) stage' in Q1, are you achieving the results you initially expected with AI agent utilization at your company?

・ Sufficiently achieved: 25.2%

・ Somewhat achieved: 61.2%

・ Not very achieved: 10.7%

・ Not at all achieved: 1.9%

・ Don't know/Cannot answer: 1.0%

Specific Results of AI Agent Utilization: 1st Place "Resolution of Labor Shortages/Labor Saving," 2nd Place "Stabilization of Product and Service Quality," Demonstrating AI's Impact on Both People and Manufacturing

When asked, "Q4. For those who answered 'Sufficiently achieved' or 'Somewhat achieved' in Q3, what specific results have you achieved with AI agent utilization? (Multiple answers allowed)" (n=89), the responses were "Led to resolution of labor shortages/labor saving" at 55.1%, "Stabilized product and service quality" at 50.6%, and "Prevented equipment failures and troubles" at 43.8%.

Q4. For those who answered 'Sufficiently achieved' or 'Somewhat achieved' in Q3, what specific results have you achieved with AI agent utilization? (Multiple answers allowed)

・ Led to resolution of labor shortages/labor saving: 55.1%

・ Stabilized product and service quality: 50.6%

・ Prevented equipment failures and troubles: 43.8%

・ Reduced defects and human errors: 38.2%

・ Shortened work and administrative processing time: 34.8%

・ Enabled sharing and inheritance of expert know-how: 20.2%

・ Improved accuracy of demand forecasting and production planning: 18.0%

・ Reduced costs: 12.4%

・ Other: 0.0%

・ Don't know/Cannot answer: 0.0%

Challenge in Promoting Utilization: "Lack of Internal Staff" is Most Frequent at 46.6%, with Top Issues Concentrated in Human Resources, Integration Design, and Tool Selection, Representing Operational Hurdles

When asked, "Q5. For those who answered 'Fully implemented and in operational use' or 'Engaged in PoC (Proof of Concept) stage' in Q1, please tell us what you consider to be challenges in advancing AI agent utilization at your company. (Multiple answers allowed)" (n=103), the responses were "Lack of internal staff who can master AI agents" at 46.6%, "Difficulty in designing the integration between business systems and AI agents" at 44.7%, and "Difficulty in selecting AI agent tools" at 40.8%.

Q5. For those who answered 'Fully implemented and in operational use' or 'Engaged in PoC (Proof of Concept) stage' in Q1, please tell us what you consider to be challenges in advancing AI agent utilization at your company. (Multiple answers allowed)

・ Lack of internal staff who can master AI agents: 46.6%

・ Difficulty in designing the integration between business systems and AI agents: 44.7%

・ Difficulty in selecting AI agent tools: 40.8%

・ Concerns about security and data governance: 23.3%

・ Primary on-site information cannot be referenced by AI agents: 19.4%

・ Gap in AI literacy between management and on-site staff: 18.4%

・ Return on investment is unclear: 11.7%

・ Other: 1.0%

・ No particular challenges: 1.9%

・ Don't know/Cannot answer: 1.0%

Voices Such as "Prompt Adjustment Takes Time and Ultimately Fails" and "Responsibility in Case of Failure" Highlight Operational Burden and Difficulty in Designing Responsibility in Practical Use

When asked, "Q6. For those who answered anything other than 'No particular challenges' or 'Don't know/Cannot answer' in Q5, please freely tell us if there are any other challenges you feel in advancing AI agent utilization besides those mentioned in Q5." (n=100), 43 responses were received.

<Excerpts from Free Responses>

・ I want it to understand work intentions and perform tasks in place of humans or macros, but even simple tasks often fail, and it takes many times longer just to adjust the prompts, ultimately not succeeding.

・ To what extent can we rely on AI, and who is responsible when failures occur.

・ It is difficult to train individuals with advanced construction skills.

・ Guaranteeing the basis and reliability of statements.

・ Handling industry-specific phenomena.

91.0% of DX/AI Promotion Managers Respond "Preparation of Primary On-site Information is a Prerequisite for AI Agent Utilization," Common Understanding is to Prioritize Data Preparation Over Tools

When asked, "Q7. Do you believe that the preparation of primary on-site information (work records, inspection records, maintenance records, etc.) is a prerequisite for operating AI agents?" (n=111), the responses were "Strongly agree" at 34.2% and "Somewhat agree" at 56.8%.

Q7. Do you believe that the preparation of primary on-site information (work records, inspection records, maintenance records, etc.) is a prerequisite for operating AI agents?

・ Strongly agree: 34.2%

・ Somewhat agree: 56.8%

・ Somewhat disagree: 6.3%

・ Strongly disagree: 1.8%

・ Don't know/Cannot answer: 0.9%

Reasons for Considering it a Prerequisite: "On-site Know-how Can Only Be Extracted from Primary Information" is Most Frequent at 56.4%, Widely Shared Recognition that AI Cannot Operate Without Data

When asked, "Q8. For those who answered 'Strongly agree' or 'Somewhat agree' in Q7, please tell us the reasons why you believe the preparation of primary on-site information is a prerequisite for operating AI agents. (Multiple answers allowed)" (n=101), the responses were "Because on-site know-how can only be extracted from primary information" at 56.4%, "Data quality is essential to prevent hallucinations" at 41.6%, and "AI cannot process handwritten or verbal information" at 35.6%.

Q8. For those who answered 'Strongly agree' or 'Somewhat agree' in Q7, please tell us the reasons why you believe the preparation of primary on-site information is a prerequisite for operating AI agents. (Multiple answers allowed)

・ Because on-site know-how can only be extracted from primary information: 56.4%

・ Data quality is essential to prevent hallucinations: 41.6%

・ AI cannot process handwritten or verbal information: 35.6%

・ Learning data must be prepared to improve accuracy: 34.7%

・ Cannot make decisions without reference information: 33.7%

・ Essential for expanding future AI utilization options: 17.8%

・ Other: 1.0%

・ Don't know/Cannot answer: 0.0%

Investment Priorities for the Next 3 Years: "Preparation of On-site Data Collection Infrastructure" Tops at 58.3%, Investment Focus Shifts from "Tools" to "Data Infrastructure"

When asked, "Q9. For those who answered anything other than 'Not particularly engaged' or 'Don't know/Cannot answer' in Q1, please tell us the areas you believe should be particularly invested in over the next 3 years to ensure the success of AI agent utilization at your company. (Up to 3 answers allowed)" (n=108), the responses were "Preparation of on-site data collection infrastructure (IoT, sensors, etc.)" at 58.3%, "Training of personnel who can master AI agents" at 45.4%, and "Introduction of AI agent tools" at 40.7%.

Q9. For those who answered anything other than 'Not particularly engaged' or 'Don't know/Cannot answer' in Q1, please tell us the areas you believe should be particularly invested in over the next 3 years to ensure the success of AI agent utilization at your company. (Up to 3 answers allowed)

・ Preparation of on-site data collection infrastructure (IoT, sensors, etc.): 58.3%

・ Training of personnel who can master AI agents: 45.4%

・ Introduction of AI agent tools: 40.7%

・ Integration design between business systems and AI agents: 26.9%

・ Digitization of on-site forms (converting paper forms to electronic): 23.1%

・ Strengthening data governance and security: 12.0%

・ AI literacy education for management and on-site staff: 5.6%

・ Other: 0.9%

・ None in particular: 0.0%

・ Don't know/Cannot answer: 0.0%

Summary

This survey was conducted on 111 individuals in charge of DX and AI promotion at manufacturing companies with 500 or more employees regarding the actual state of AI agent utilization in the manufacturing industry. The results revealed that 92.7% have already started utilization, and 91.0% recognize that "preparation of primary on-site information is a prerequisite for utilization."

First, regarding the status of initiatives, 48.6% are in the "PoC stage" and 44.1% are in "full-scale implementation." The most frequent business area for utilization and consideration was "manufacturing line maintenance/predictive maintenance" at 55.6%. Furthermore, 86.4% of those in the implementation/PoC stages responded that they are "achieving results," with "resolution of labor shortages/labor saving" (55.1%) and "stabilization of quality" (50.6%) ranking highest. On the other hand, challenges in promoting utilization included "lack of internal staff who can master it" (46.6%) and "difficulty in system integration design" (44.7%). Additionally, 91.0% responded that "preparation of primary on-site information is a prerequisite," and the area to be invested in over the next 3 years was most frequently "preparation of on-site data collection infrastructure" (58.3%).

This survey suggests that AI agent utilization in the manufacturing industry is expanding to the implementation and demonstration stages, with results such as labor shortage resolution and quality stabilization beginning to emerge. However, in the phase of expanding utilization, in addition to mastering tools and preparing system integration, how to organize the primary on-site information that AI should reference will likely be the deciding factor in ensuring that results are not merely temporary.

Download this survey here: https://application.i-reporter.jp/download.research22

For Digitization of On-site Forms, Choose "i-Reporter"

In this survey, approximately 70% of young employees in the manufacturing industry feel that on-site operations are "less digitized than they expected before joining the company." Specific examples include "manual data transcription" (57.3%), "searching for past records from paper files" (38.7%), and "handwriting on paper forms and daily reports" (21.3%). Furthermore, about 30% (29.9%) of young employees who considered leaving their jobs cited "the analog nature of on-site operations/delay in digitization" as a reason. On the other hand, about 60% (64.8%) of young employees responded that they "would like to continue working at the current company" if on-site operations were digitized, revealing the reality that an analog on-site environment reliant on paper and manual work is a turning point that influences the retention of young talent.

i-Reporter allows you to reproduce the familiar layout of paper and Excel forms on a tablet while replacing manual transcription and handwriting tasks with digital ones, addressing the aspects that young people find "analog."

Digitize Paper Forms As Is: Replicate familiar form layouts on a tablet without disruption. Eliminate manual transcription and handwritten entries, resolving the very aspects of "analog" that young people experience.

No-Code, Site-Led: Promote digitization independently at the site without programming knowledge. Implementable even in sites without dedicated IT personnel, allowing experienced employees to transition smoothly.

Diverse Digital Input and Automatic Aggregation: Input via checks, numerical selection, camera, voice, barcodes, etc., and automate aggregation and report creation. Reduce the burden of manual aggregation and reporting.

Centralized Management and Search of On-site Records: Centralize data upon input and quickly retrieve past records. Eliminate the hassle of searching through paper files and enable secondary utilization as structured data.

With about 80% of young people preferring "a more digitized company when choosing an employer" and 25.9% prioritizing "digitization of on-site operations" when choosing a new job, the digitization of on-site operations is a theme directly linked to attracting and retaining young talent. Amidst challenges such as budget constraints and a lack of IT personnel, i-Reporter enables a small-scale start with no-code and supports the first step in creating an on-site environment where young people want to "continue working."

About CIMTOPS Co., Ltd.

Company Name: CIMTOPS Co., Ltd.

Head Office Address: 10F, Shin-Meguro Tokyu Building, 2-25-2 Kamiosaki, Shinagawa-ku, Tokyo 141-0021

Representative: Representative Director CEO Kazuyuki Okuhata

Date of Establishment: October 1, 1991

Capital: 16.5 million yen

Sales: 2.325 billion yen (Fiscal Year 2025 Sales)

Number of Employees: 92 total (as of the end of March 2026)

<Business Activities>

Development and sales of the production scheduler and production management system DIRECTOR for discrete manufacturing

Development and sales of the no-code on-site form paperless solution i-Reporter

Development and sales of various i-Repo family products and services

Development and sales of the BOP process editor MPPCreator

CIMTOPS was founded in 1991 as a pioneer in domestic production scheduler specialized companies.

Leveraging the know-how gained through the construction and operation of production scheduling and process management systems for many customers, we feed this back into our products. We develop packaged products such as production schedulers, process management systems, IoT data collection solutions, and on-site form digitization systems that can be used in manufacturing sites, supporting our customers' on-site DX.

Corporate Site | https://www.cimtops.co.jp/

Irepo-chan (Official Corporate Character) X (formerly Twitter) Account | https://x.com/i_reporter_jp

CIMTOPS Co., Ltd. Official Facebook Account | https://www.facebook.com/profile.php?id=61550755513117

* Published August 8, 2024, by Fuji Chimera Research Institute

IT Investment/Digital Solution Market by Industry 2024 Edition

I-2 On-site Form Paperless Solution Market Share 48.6%

(Vendor Share, Quantity for FY2023)

FACT BOX

  • Source: PR TIMES
  • Category: Survey結果
  • Organizations: IDEATECH