“AI will become infrastructure, just like electricity or computers. If you can harness its power, you’ll achieve much greater results.” This profound statement from Taku Ichibayashi, Manager of R&D Digital Group at ENEOS Materials, encapsulates the transformative vision driving one of Japan’s earliest and most successful deployments of ChatGPT Enterprise. The video showcases ENEOS Materials’ journey, detailing how this industrial giant has not merely adopted AI, but deeply integrated it into its operational fabric, fostering a culture of efficiency and innovation across its diverse functions.
Ichibayashi, alongside Koshiro Sakura, Manager of Production Technology Group, Ken-ichi Sakemi, Senior Engineer, and Marie Takeda, Senior Staff at the Yokkaichi Training Center, spoke about the profound impact of generative AI on their organization. ENEOS Materials, a core business within the ENEOS Group, specializes in high-performance materials like synthetic rubber. Like many manufacturing enterprises in Japan, they faced the dual challenge of a persistent labor shortage and the imperative to boost operational efficiency through digital solutions. Their strategic response was to leverage AI, not as a mere tool, but as a critical factor in strengthening their global competitiveness.
The decision to implement ChatGPT Enterprise was not taken lightly. A paramount concern for ENEOS Materials was the secure handling of internal data. After careful evaluation, Ichibayashi confirmed their choice, stating, “After careful evaluation, we decided to adopt ChatGPT Enterprise, as it meets our internal cyber security requirements and delivers excellent accuracy in its outputs.” This focus on security and accuracy underscores a core insight: for large enterprises, foundational trust in the AI platform is non-negotiable, acting as a prerequisite for widespread adoption and the unlocking of genuine business value. Without this robust security, the ambitious scale of their deployment, over 1,000 custom GPTs, would be untenable.
The impact on the R&D and Engineering departments has been particularly striking. Ken-ichi Sakemi highlighted a significant shift in how complex investigations are conducted. Previously, the team relied heavily on external research firms, a process that was often time-consuming and lacked immediate, targeted insights. With ChatGPT Enterprise, Sakemi notes, “By asking specific, targeted questions, we feel we’re achieving even better results than those provided by our external research firms.” This immediate access to deep research and detailed reports has dramatically accelerated their problem-solving capabilities. Meetings, once prone to pauses due to unanswered questions, now benefit from on-the-spot deep research, allowing for swift issue resolution and clearer conclusions. For instance, the ability to prompt the AI to generate dynamic simulations using Python and visualize complex data in graphs has made results more accessible and explainable, fostering a more data-driven decision-making environment.
Beyond the technical departments, AI has permeated critical human resources functions. Marie Takeda from the Yokkaichi Training Center detailed the "Training Report GPT," a custom solution that analyzes training reports and suggests improvements for future sessions. This application exemplifies another core insight: AI's power to democratize advanced capabilities. Tasks that once demanded substantial human effort and time are now streamlined. Takeda proudly reported, "Tasks that previously took about an hour now take roughly 20 seconds." This dramatic reduction in processing time not only frees up HR staff for more strategic initiatives but also ensures that training programs are continually refined based on objective, data-driven insights.