Why "Judgment" Has Become a Challenge in Companies in the Age of AI (Organizational Behavior Science®)

Work Style Reform, Efficiency Improvement, Standardization, SFA, Process Management, IT Implementation.

As a result of improvements that companies have pursued with good intentions, the value of work that involves thinking while verifying facts has become less visible in terms of short-term efficiency, and work methods that proceed based on precedent have been strengthened. Furthermore, even if problem-solving skills and various frameworks are learned, the foundation for using them has expanded in the field, making them difficult to apply, and the limitations have become apparent in the age of AI. We are releasing a report that organizes this background based on the practices and analysis of 338,000 people and 980 companies, as well as the theories of Organizational Behavior Science® and experiential learning.

Request Co., Ltd. (Headquarters: Shinjuku-ku, Tokyo, Representative Director: Tomoyasu Kouhata), which provides Organizational Behavior Science®, has released a report that organizes why, fundamentally, "judgment" has become a challenge in companies today, based on the practices and analysis of 338,000 people and 980 companies.

Download the Report

What we want to convey this time is not simply "judgment is important from now on." What we truly want to convey is the background of why, despite entering an era where judgment is necessary, judgment experience has been decreasing in the field in many companies.

In the previously released analysis, it was confirmed from the analysis of 338,000 people and 980 companies that judgment experience is decreasing in 82% of companies. Furthermore, the composition of the 980 companies in this analysis consists of approximately 80% large corporations and approximately 20% medium-sized corporations. In other words, this issue is not a special problem occurring in only a few companies. It needs to be viewed as changes in the environment and changes in work that are commonly occurring in many companies.

There were originally jobs that required fact-checking

First, it is important to note that before the advent of generative AI, there were "jobs requiring fact-checking" in companies. For example:

• Circumstances differ for each customer.

• Constraints differ for each project.

• Conditions differ for each site.

• What is seen differs for each stakeholder.

For such jobs, simply knowing precedents is not enough.

• "What is different this time?"