5-20. The Future of Data-Driven EHS Management: Collaboration Between Humans and AI

EHS (Environmental, Health, and Safety) management is evolving beyond traditional compliance and accident prevention. It's moving into a new phase that enables data-driven business decisions. The use of data, especially through collaboration with AI (Artificial Intelligence), is expected to play a crucial role in improving a company's risk management and sustainability. This article explains the future of data-driven EHS management and the ideal way for humans and AI to work together.

1. Characteristics of Data-Driven EHS

Data-driven EHS management is a system that uses a vast amount of data—collected from sensors, IoT devices, wearable devices, and cloud systems—to predict risks and guide improvement measures. By enabling real-time detection of anomalies and analyzing past near-miss incidents, it becomes possible to prevent accidents. Additionally, integrating this data with environmental information allows companies to directly reduce greenhouse gas emissions and improve energy efficiency.

2. The Role of AI and Human Judgment

While AI excels at recognizing patterns in large datasets and performing predictive analysis, it cannot fully grasp on-site conditions or the psychological aspects of employees. Therefore, an ideal model is one of collaboration, where humans evaluate the risk predictions generated by AI and combine them with on-site knowledge to make decisions. For example, if an AI predicts equipment failure, a human would then conduct an on-site inspection and decide whether to perform repairs or change operational procedures.

3. Establishing a Data Platform

The future of EHS management requires building a platform that integrates data from both inside and outside the company. Centralizing data from different areas—such as occupational safety, environmental impact, compliance, and health management—and visualizing it on a dashboard will enable management to make quick decisions. From an ESG investment perspective, transparent data disclosure directly enhances corporate value.

4. Human-Centered AI Use

Even as AI becomes more prevalent, humans remain at the core of EHS management. By improving employee safety awareness and using on-site feedback to train the AI, companies can achieve more accurate risk predictions and better improvement measures. It's crucial to position AI as a supplementary tool that supports human judgment.

Conclusion

The future of data-driven EHS management lies in a collaborative model that fuses human experience with AI's analytical capabilities. By leveraging IoT, big data, and AI while keeping humans in charge of final decision-making, companies can strengthen accident prevention and reduce their environmental impact, thereby achieving sustainable business management. This is the direction in which EHS management is evolving, and it is the approach that companies must take going forward.