In 2023, Brazil recorded alarming numbers of work accidents, with almost 500,000 reported events, resulting in nearly 3,000 deaths and hundreds of thousands of injuries leading to worker absenteeism. These accidents are not just human tragedies but also represent a significant financial impact on organizations and the economy as a whole.
Since 2012, the costs associated with work-related diseases and accidents in the country have reached around R$100 billion, due to expenses on medical treatment, loss of productivity, and compensations. Given this scenario, the adoption of advanced technologies for accident prevention has become viable and crucial.
Innovative companies have developed solutions based on generative artificial intelligence (AI) to identify and monitor risk controls in industrial activities, enabling prescriptive actions before an accident occurs. This approach uses data from past incidents to create recommendation models that assist security teams in making proactive decisions.
Felippe Ribas, Occupational Safety Engineer at the startup Dshbird, focused on corporate security and predictive analytics, comments on the importance of tools: “The ability to predict and, especially, prescribe actions based on real data and continuous analysis is a game-changer in industrial safety management. Resources that offer insights based on artificial intelligence allow companies not only to respond to incidents but also to help prevent them, promoting a safer and more efficient work environment”.
These solutions are essential for sectors such as Civil Construction and Road Transport, where the main types of accidents include falls from heights, electrical shocks, and traffic accidents, often exacerbated by worker fatigue and inadequate equipment maintenance.
Continuous monitoring and real-time corrective action recommendations – provided by these technologies – have the potential to significantly reduce accident rates in these sectors and, consequently, save lives.
In a country where workplace safety still faces monumental challenges, the application of generative AI technologies marks a new era in accident prevention. “With adoption, we expect not only a decrease in rates but also a cultural shift in industries, where the proactive method becomes the norm, not the exception”, concludes Ribas.
