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 usage status and satisfaction levels of generative AI output quality, conducted among 500 business professionals currently utilizing generative AI in their work.
The survey report reveals that 70% of users are dissatisfied with the accuracy of AI outputs, and highlights the reality that verifying these outputs consumes an unexpected amount of time.
To improve productivity through generative AI, it is increasingly necessary for companies to commit to "high-quality data management." Please download the report to review the detailed findings.
Click Here for 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 jump to the free download page for the materials).
Background and Purpose of the Survey
While the use of generative AI in business is expanding, dissatisfaction persists, with users noting that outputs are "not ready for direct use" or that "poor accuracy leads to unexpected time spent on verification." This is often attributed to "prompt engineering skills." However, we conducted this survey to investigate whether the issue lies not only in prompt skills but also in the "quality of data" referenced by the generative AI.
• Quantify the Real-World Status of Business Professionals Using Generative AI for Work
• Identify the Root Causes of Dissatisfaction Regarding AI Response Quality and Reliability
• Explore the Relationship Between AI Performance and the Necessary Data Management Practices
Survey Overview
• Survey Name: Survey on Generative AI Usage Status and Quality
• Methodology: Internet 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% have experienced dissatisfaction with the "accuracy and reliability" of generative AI (70.4%)
70.4% of respondents answered that they "frequently" or "sometimes" feel dissatisfied with the accuracy and factual reliability of generative AI responses. While the use of generative AI is becoming mainstream, it is clear that concerns regarding reliability remain widespread.
2) The cause of dissatisfaction is "data quality" — 61.4% attribute it to data
When asked about the causes of dissatisfaction with AI responses, 23% cited "AI lacks specialized and 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 "lack of 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 — 72.8% spend time validating or correcting answers
72.8% of respondents spend 5 minutes or more per instance on "error checking and verification" of information provided by AI. Some spend over 30 minutes. This highlights the reality that the benefits of AI adoption are being offset by the effort required to verify outputs.
4) The key to elevating AI usage is the "data environment" — 61.6% cite 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 important factor. This result surpasses "improving prompt skills" (20%).
Implications of 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 outputs 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 further advancement and improvement of AI usage in the future, it is becoming increasingly important for companies to establish an environment that connects to reliable and accurate data.
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 prospects, inevitably becomes obsolete over time and is often compromised by inconsistencies caused by manual entry. Companies that implement uSonar can build a data environment with comprehensive, accurate, and up-to-date information, as the high-definition data necessary for business is constantly supplied by our company.
For 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 built 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. We maintain attribute information such as corporate numbers, industry types, sales scale, capital affiliation, and head office/branch relationships, enabling a grasp of the entire country and affiliation structures. We cover 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 for Inquiries:
uSonar Co., Ltd. Public Relations (Hiyama, Ehara)
Email:pr@usonar.co.jp
