Generative AI: Does insurance really need it?

Fresh off the heels of the InsurTech Insights conference in London, I find myself reflecting on a recurring theme that seems to capture the spotlight with increasing frequency: Generative Artificial Intelligence (AI).  Every keynote, every panel discussion, and every networking break somehow circles back to the topic of leveraging artificial intelligence to generate content, streamline processes, and revolutionize the industry. But amidst the fervour and excitement, it's essential to take a step back and question whether the generative AI is really what the insurance sector needs? 

Sure, the allure of cutting-edge technology is enticing. The thought of AI crafting policy wordings, generating marketing materials, or even simulating customer interactions can seem like a dream come true for companies looking to streamline processes and enhance efficiency. But, as with any shiny new tool, we must pause and critically examine its relevance and impact. 

One of the primary concerns with embracing Generative AI in insurance is the risk of prioritizing novelty over necessity. It's easy to get swept up in the allure of innovation, but we should resist the temptation to adopt solutions simply because they're trendy or technologically advanced.  

In the eagerness to embrace cutting-edge technology, the industry runs the risk of creating solutions for problems that are more imagined than real. Instead of focusing on enhancing the customer experience, reducing claims processing times, improving data quality and the way and speed in which it is being exchanged with other entities or improving risk assessment methodologies, we might find ourselves chasing after the next big thing without addressing the foundational issues plaguing the industry. 

One of the primary concerns with embracing Generative AI is the issue of trust and reliability. Insurance is built on a foundation of trust between insurers and policyholders. When it comes to critical documents like policy wordings, contracts, and legal agreements, accuracy and clarity are non-negotiable. Can we trust Generative AI to consistently produce content that meets the rigorous standards of the insurance industry? The answer may not be so clear-cut. 

One of the most revealing litmus tests involves considering whether, from the perspective of either a customer or an insurer: 

• Would you trust the wording to be written by generative AI? 
• Would you feel confident in the authenticity and reliability of content generated by algorithms, especially when it pertains to matters as critical as insurance policies and claims?  

That's not to say that Generative AI has no place in insurance. There are undoubtedly areas where it could prove beneficial, such as data analysis, fraud detection, and customer service automation. However, before we rush headlong into adopting new technologies, we must first pause and critically evaluate their relevance, efficacy, and potential impact on the industry. 

So, the next time generative AI takes centre stage at a conference, let us pause, reflect, and redirect our attention towards the real challenges facing the insurance sector. After all, true progress lies not in embracing the latest trends, but in fostering meaningful solutions that make a tangible difference in the lives of policyholders as well as those who serve them.