There has perpetually been a concern about the influence of artificial intelligence (AI) on employment sectors as it proliferates within the industry. Nevertheless, Richard Hartley, the CEO and co-founder of Cytora, remains hopeful that AI will stimulate the creation of more jobs within the sector.
As per Hartley, the re/insurance industry harbors the potential for expansion and increased efficiency on a global scale. During a recent dialogue with Reinsurance News, he alluded to the capacity of technology to empower existing re/insurance teams, enabling them to achieve more and thereby augmenting customer value and market revenue.
With the continuous advancement of AI in the industry, Hartley stresses the significance of organizations investing in skills training to stay abreast of the evolving technology.
The ubiquitous utilization of large language models (LLMs) in daily operations is progressively becoming a norm worldwide, introducing a distinctive dimension to these models.
It is foreseen that this trend will gain prominence in the re/insurance business landscape, where individuals will employ LLMs to furnish detailed descriptions or responses to inquiries they may have.
Given the interpretive nature of insurance, which holds substantial value, the crux of insurance lies in comprehending intricate and varied information to extract valuable insights.
This intricate process entails extensive reading, comprehension, and synthesis, coupled with a lack of standardization. Nonetheless, through the utilization of AI, the technology can identify areas necessitating attention, thereby curtailing a task that typically consumes four hours to accomplish.
Generative AI, designed to streamline operations and generate unexpected insights, represents a notable technological progression garnering traction in the industry as companies delve into AI experimentation.
Hartley contemplates whether the deployment of conceptual AI in the industry proves more advantageous or disadvantageous.
He perceives it as a significant metamorphosis concerning current capabilities and potentials, deeming it a favorable advancement for the industry. A substantial segment of the insurance value chain operates in an analog fashion, where clients compile and evaluate risk information before transferring it to brokers for further evaluation. This analog process can be substantially streamlined and automated through the relational facets of generative AI, thereby enhancing risk data automation, insight generation, and decision-making efficiency. This efficiency enables individuals to save time and concentrate on pivotal tasks, fostering the creation of new products in underrepresented risk sectors, thereby expanding the industry.
Hartley also underscores that despite the re/insurance industry having employed AI for a while, the extensive training requisite for AI-driven systems has impeded swift deployment and scalability across diverse regions and sectors.
However, with conceptual AI, the learning curve is significantly abridged, often necessitating minimal to no training, thereby amplifying the adaptability of AI. This streamlined approach unlocks transformative business value for major carriers operating globally with varied product portfolios.
Hartley opines that re/insurance companies have promptly acknowledged the potential of large language models (LLMs) and are transitioning from proof of concepts (POCs) to full-scale production, effectively reaping benefits from these advancements.
