Current trends are debunking myths about technology use in the insurance industry. Contrary to what’s long been taken as gospel — that those in the industry are slow to adopt new and emerging technologies — technology use is on the uptick. This is especially true for the insurance industry and artificial intelligence (AI).  

According to a report from the research and analyst firm Forrester, fully 63% of data and analytics decision-makers at insurance companies report their organization is adopting AI, with another 24% planning to follow suit. In fact, the report points out that insurers around the globe are currently investing almost half of their resources into data, analytics, and AI.  

Another recent report from research and analyst firm Celent found that insurance IT budgets rose in the last few years for both internal and external technology activities. And the research and analyst firm Gartner projects that most insurance companies have indicated either increasing or maintaining these spending levels. The focus? Improving customer experience, modernizing legacy applications, and expanding analytics capabilities — all with the potential to integrate AI into the insurance portfolio.  

Before your organization can fully engage with AI, it’s important to first consider the technology currently in place. AI won’t be a viable option for those dependent on legacy systems that often don’t communicate with each other, force data to reside in silos, are expensive to maintain, and contribute to a poor user experience.   

The following factors should be considered when implementing AI.  

JUST THE GOOD DATA  

Understanding the type of data you have is a crucial step when preparing to incorporate AI. This process involves data discovery, assessment, and categorization, and it lays the foundation for building effective AI models and systems.   

Good-quality data is accurate and complete and should contain clear and up-to-date information about the insured, such as coverage type, policy term, premium, deductible, coverage limits, and endorsements. This data comes in two primary forms – structured and unstructured. Structured data is organized and stored in a predefined format, making it easy to search, analyze, and process. Unstructured data, such as images, audio, video, and social media posts, doesn’t have a predefined structure and cannot be searched as easily or analyzed by traditional methods.   

Being able to review your data and determine what is structured and what is unstructured is the first step in understanding what it takes to integrate AI into your core system.   

WHERE TO USE AI  

True digital transformation isn’t simply collecting data – it includes the ability to analyze the data you’ve collected. Three key areas where insurers can harness AI are claims processing, policy underwriting, and risk mitigation.   

Organizations can unlock the door to analytical insights when they use data and AI to drive workflow and decision-making processes. Ultimately, this will make an organization more adaptable to market conditions and more responsive to consumer needs.   

INVITE YOUR EXTENDED FAMILY  

Internal and external resources and partners with knowledge of an insurer’s systems and data are critical to AI implementation, especially in the early stages. Partnering with different AI providers can help bridge the gap between what’s possible today and what’s going to be necessary to move the envelope tomorrow.   

When AI algorithms can better predict future claims and calculate associated risk, organizations across the insurance ecosystem can set more appropriate premium levels to not only avoid underpricing policies — which can lead to financial losses — but avoid overpricing that can result in lost business.   

For further information on how insurers can clean up their organizations’ data to make way for AI, read our “Get Your House In Order For…AI” e-book.