Environmental health and safety (EHS) is a critical aspect of any workplace. Organizations that prioritize workplace safety create a culture of safety, not just for their employees, but for the company as a whole. Thanks to modern data analytics and artificial intelligence (AI), EHS professionals can now leverage technology to streamline their workflows, automate repetitive tasks, and reduce employee injuries. In this article, we’ll discuss how AI is breaking new ground in EHS, and what you need to know to stay ahead of the curve.
EHS professionals and data management
Effective EHS management involves monitoring and analyzing large volumes of data on a daily basis. Traditional methods of managing data require considerable time and effort, often resulting in information overload. However, advancements in analytics and AI have made it easier than ever to synthesize this information to improve existing risk mitigation activities. These tools allow EHS professionals to uncover hidden insights, trends, and patterns that might have been missed using traditional methods.
Computer vision technology for hazard detection
Computer vision technology, when paired with CCTV systems to monitor images and video footage, can detect objects and workers’ proximity to hazards, such as heavy machinery or unprotected edges. These systems can help identify slip, trip, and fall hazards, as well as potential issues with PPE compliance. Additionally, computer vision technology can alert EHS professionals in real-time when an employee enters a restricted area or attempts to remove PPE. By leveraging this technology, companies can ensure that their employees are working safely, ultimately reducing the risk of employee injuries.
Natural language processing for data extraction
Natural Language Processing can summarize written reports and extract insights, including quantitative data. By analyzing reports and identifying areas of concern, EHS professionals can take proactive action to mitigate those risks. For example, if there is a high incidence of near-miss incidents in a particular area, EHS professionals can address the root causes of the problem and reduce the likelihood of future incidents occurring.
Predictive and prescriptive analytics for incident prevention
Predictive and prescriptive analytics engines can predict incidents and provide recommendations, such as the most suitable PPE for a specific task. By analyzing past incidents, AI algorithms can identify the root causes of those incidents and generate recommendations to prevent similar incidents from occurring in the future. Through this process, EHS professionals can take proactive steps to reduce the likelihood of incidents, ultimately reducing the risks to employees and the organization.
Focusing on workplace safety and ensuring PPE compliance
More companies are focusing on education regarding workplace safety and PPE compliance, particularly to promote a culture of safety. By educating their employees, companies can reduce the likelihood of incidents occurring and create a clear understanding of the procedures involved in carrying out work safely. With a renewed focus on workplace safety, companies can also reduce the likelihood of government or regulatory interventions, which can lead to reputational damage, legal issues, or even financial penalties.
AI-based tools for communication and employee engagement
AI-based tools may play a role in improving communication and helping employees to understand the benefits of certain safety policies. For example, AI-powered chatbots can answer frequently asked questions around PPE compliance or provide online learning resources to employees. Other companies are leveraging augmented reality (AR) and virtual reality (VR) technologies to simulate hazardous situations, providing employees with immersive experiences that can help them understand and avoid dangerous situations.
Recommendations for AI adoption:
1. Identify the business problems that can be solved by AI.
2. Assess the readiness of your organization for AI adoption.
3. Develop an AI strategy and create a roadmap for implementation.
4. Choose the right AI technologies, tools, and platforms.
5. Implement AI in a phased manner and constantly monitor and optimize its performance.
6. Address the ethical and legal considerations related to AI adoption.
7. Invest in upskilling and reskilling your workforce to make the most of AI technology.
Recent recommendations suggest that effective AI adoption should stem from workers’ needs and current automation processes in the workplace. By involving workers in the process, organizations can ensure that AI is adopted in a way that aligns with their needs, and not just the needs of the EHS department. Additionally, organizations should be transparent with their employees about the use of AI, providing education and training to help calm any fears or uncertainties that may arise.
AI has the potential to revolutionize the way EHS professionals manage their responsibilities by streamlining workflows, automating repetitive tasks, and providing insights that might have been missed using traditional methods. By embracing modern data analytics and artificial intelligence, companies can create a culture of safety, ultimately reducing the risk of employee injuries, legal issues, or even reputational damage. With a strategic approach to AI adoption and implementation, companies can become leaders in EHS management and pave the way for safer and more productive workplaces.
