The buzz around artificial intelligence (AI) in the insurance sector has grown to a deafening roar. Everywhere we turn, new platforms and applications promise groundbreaking improvements and new capabilities using the power of AI. But, if we peel back the layers, it’s evident that many of the ideas underpinning generative AI aren’t exactly new. What’s changed, however, is the speed and ease with which we can execute them.
Generative AI: Not Reinventing the Wheel, Just Turning it Faster
To understand the true value of generative AI, we first need to look back. Before the age of “genAI”, data scientists embarked on arduous journeys, navigating through multiple research avenues and models to identify which technique would work best for a given problem statement in the insurance space. This process was often marked by trial and error, with large teams spending substantial time and resources, only to possibly end up at a dead end.
Upon finding a promising approach, the real grind began: refining the model, improving its accuracy, and ensuring it met the rigorous standards necessary for real-world application. Progressing from 80% to 95% accuracy wasn’t just a leap; it was a marathon.
Enter generative AI. With its advent, the entire initial phase of model selection, ideation, and preliminary testing has been compressed. Instead of embarking on multiple data science tracks, technical leaders now use “prompt engineering.” By effectively instructing the AI on what is required, genAI can quickly generate outputs that are about 80% accurate. This doesn’t just save time—it revolutionizes the entire model development lifecycle.
No More Heavy Lifting: AI for Every Insurance Business
This speed and efficiency are particularly game-changing for the insurance industry, where AI-driven insights are essential for risk assessment, fraud detection, claims processing, and customer service. By leveraging genAI, even businesses without a comprehensive data science division can harness the power of AI, democratizing innovation across the board.
So, while the foundational ideas of generative AI in insurance aren’t groundbreaking in themselves, the speed, scalability, and accessibility it brings to the table certainly are. It’s no longer about having an idea; it’s about how swiftly you can bring that idea to life and make data-driven decisions.
For insurance companies and technical leaders keen on riding the AI wave, the message is clear: with generative AI, you don’t need to run a hardcore data science shop to benefit from AI’s transformative capabilities. The revolution is here, and it’s all about speed and efficiency.