Frontline risks associated with operations, safety, compliance, and customer interactions can have immediate and severe consequences if not properly managed. However, advancements in AI — from generative (content creation) to machine learning (enabling systems to learn from data) to computer vision (interpreting visual information) are now transforming how organisations identify, assess, and mitigate these risks, offering unprecedented levels of efficiency, accuracy, and proactive management.
The challenge of managing frontline risks
Frontline operations are inherently dynamic and often unpredictable. They are experienced every second by over 80% of the global workforce who are deskless workers, and sit across nearly every business industry, including logistics, construction, retail, energy, and manufacturing. However, traditional risk management approaches — entrenched in the pre-AI world — rely heavily on manual processes of data observation and collection, historical data analysis, and reactive measures. These methods can be slow, prone to human error, and often fail to provide real-time insights needed to prevent incidents before they occur. The ineffectiveness of these traditional risk management approaches is further compounded by the rapidly evolving risks generated as AI continues to drive innovation.
How AI is changing the game
AI tools are revolutionising frontline risk management by enabling organisations to move from reactive to proactive strategies. For example: