Corporate News
uSonar Co., Ltd. (Headquarters: Shinjuku-ku, Tokyo; hereinafter "uSonar") is pleased to announce the release of a report based on a survey regarding the actual usage and satisfaction levels of generative AI output, conducted among 500 business professionals currently using generative AI in their work.
The survey report reveals that 70% of users are dissatisfied with the accuracy of AI output, and that verifying this output consumes an unexpected amount of time.
To improve productivity through generative AI, it is clear that companies must increasingly focus on "high-quality data management." We invite you to download the report for further details.
Download the Detailed Survey Report
To obtain the detailed report, please use the application form on the right side of this page. You can also access it via the "Get the Survey Report" button below (this will redirect you to the free download page).
Background and Purpose of the Survey
While the use of generative AI in business is expanding, dissatisfaction persists regarding AI output, with users noting that it is "not ready for immediate use" or that "poor accuracy leads to unexpected time spent on verification."
This is often attributed to a lack of "prompt engineering skills." However, we conducted this survey to explore whether the issue might also lie in the "quality of data" that the generative AI references.
• Quantify the "Real-World Usage" of Business Professionals Utilizing Generative AI in Their Work.
• Identify the "Root Causes" of Dissatisfaction Regarding AI Output Quality and Reliability.
• Explore the Relationship Between AI Performance and the Necessary Data Management Practices.
Survey Overview
• Survey Title: Survey on Generative AI Usage and Quality
• Methodology: Internet-Based Survey (Cross Marketing Inc. Survey Panel)
• Target Audience: Business Professionals Who Use Generative AI "Daily" or "Occasionally" for Work
• Valid Responses: 500
• Survey Period: March 2026
• Conducted by: uSonar Co., Ltd.
Key Survey Results (Summary)
1) Approximately 70% Experience Dissatisfaction with the "Accuracy and Reliability" of Generative AI (70.4%)
70.4% of respondents answered that they "frequently" or "sometimes" experience dissatisfaction regarding the accuracy and factual reliability of generative AI responses. While generative AI usage is becoming mainstream, it is clear that concerns regarding reliability remain widespread.
2) The Cause of Dissatisfaction Is "Data Quality" — 61.4% Attribute Issues to Data
When asked about the causes of dissatisfaction with AI responses, 23% cited "the AI lacks specialized or up-to-date information," and 22% cited "the possibility that the source data is incorrect," with a combined 61.4% attributing the issue to the "quality of data and information."
Meanwhile, only 12.4% cited "insufficient prompt skills," suggesting that many users believe the core issue lies in the data environment referenced by the AI rather than user-side skills.
3) Time Spent Verifying Responses Offsets Productivity Gains — 72.8% Spend Time Validating or Correcting AI Output
72.8% of respondents spend 5 minutes or more per instance on "error checking and verification" of information provided by AI, with some spending over 30 minutes. This highlights the reality that the productivity benefits of AI are being offset by the effort required to verify the output.
4) The Key to Elevating AI Usage Is the "Data Environment" — 61.6% Identify It as the Most Important Factor
When asked what is most necessary to improve the level of generative AI usage in the future, "improving the accuracy and timeliness of data" (33%) and "access to a broader range of factual data" (29%) topped the list, with a combined 61.6% identifying "data improvement" as the most critical factor. This result surpasses "improving prompt skills" (20%).
Insights from the Survey
• The Bottleneck for Generative AI Usage Is the "Data Environment," Not "Prompts"
This survey indicates that the primary cause of dissatisfaction with generative AI output is not user AI skills such as prompting, but rather concerns regarding the "accuracy," "timeliness," and "expertise" of the information data referenced by the AI.
For the further advancement and improvement of AI usage, it is clear that establishing an environment that connects to "reliable and accurate data" will become increasingly important for companies.
For Corporate Data Management, Turn to uSonar
uSonar provides the "LBC"* corporate database, the largest in Japan, to companies through various cloud services. Corporate customer data, such as suppliers and sales leads, inevitably becomes obsolete over time and can be compromised by inconsistencies caused by manual entry. Companies that implement uSonar can build a data environment characterized by comprehensiveness, accuracy, and timeliness, as the high-definition data required for business is continuously supplied by our company.
For further details or to request materials, please use the inquiry form on our website.
*About the "LBC" Corporate Database
This is the largest corporate database in Japan, independently constructed by uSonar. (Largest in Japan: Based on our own research as of June 1, 2026).
We assign an 11-digit management code to approximately 12.5 million business locations across Japan. It maintains attribute information such as corporate numbers, industry types, sales scale, capital affiliation, and head office/branch relationships, allowing for a comprehensive understanding of the national scale and affiliation structures. It covers a wide range of information, from offline data such as commercial registries to corporate information on the web, integrating and accumulating over 120 data points.
Contact Information for This Inquiry:
uSonar Co., Ltd. Public Relations (Hiyama, Ehara)
Email:pr@usonar.co.jp
