Note: This resource is available in Japanese only. By completing the form, you will receive access to the webinar in Japanese.

Challenges in the AI era and the roadmap toward treating quality as a strategic business asset

As technology advances and digital transformation accelerates, software quality assurance (QA) is becoming more closely tied to business strategy than ever before. At the same time, major system failures and data breaches continue to occur in Japan and abroad, raising the question of whether the pursuit of speed is causing organizations to overlook quality.

This survey, now in its second year, examines the state of software quality assurance frameworks and AI‑driven test automation in Japanese enterprises. It focuses on how organizations perceive quality risks, the bottlenecks related to talent and organizational structure, and the role of AI in improving software quality. Building on insights from last year’s report—‘Application Modernization and Test Automation’—which highlighted delays in test automation and a shortage of IT talent both in quantity and skill level, this year’s report aims to redefine quality assurance as a business‑level priority and provide guidance for identifying the next steps organizations should take.

This survey report revealed the following insights:

• Many companies recognize some form of risk related to system stability and reliability, including information security, the business and customer impact of service outages, and the cost of incident response. Only 2.5% of companies reported that they “do not feel any quality‑related risks.”
• At the same time, the findings show that the biggest constraints on QA in Japanese companies are not simply a shortage of headcount, but structural issues created by the combination of talent quality and organizational design. Nearly 90% of respondents reported challenges in securing or developing QA talent, pointing to a shortage of individuals who can drive test automation, test strategy, and data‑driven quality management.
• Although the adoption of AI‑enabled test automation tools and generative AI is gradually expanding, only a little over 20% of companies report experiencing real value in production environments. For many organizations, AI remains at the PoC stage, and a gap persists between “knowing about AI” and “effectively using AI.”

For more details, please download the full report.