The insurance industry faces constant pressure to improve efficiency and personalize customer experiences. This is fueled further by the tech-obsessed world we live in. The industry is now on the cusp of a significant transformation driven by the combined power of artificial intelligence (AI) and automation.

    The powerful duo that is AI and automation is not just streamlining workflows, it’s fundamentally reshaping the way insurance works, with many believing that by 2030, the whole industry will function in a completely different model.1 This technological transformation will touch every aspect, from underwriting and risk assessment to claims processing and customer service.

    The pace of change is accelerating too, as various stakeholders – brokers, consumers, insurers and suppliers – become more adept at using advanced technologies. After all, 14% of insurance companies have already adopted or are testing AI solutions, while a further 55% are considering introducing AI into their processes.2 This tech-driven evolution promises to enhance decision-making, boost productivity, lower costs and ultimately, optimize the customer experience. But only if it’s implemented correctly. 

    So, how will AI solve the industry’s challenges? And how can organizations implement it correctly?

    Why AI is the future of insurance

    Firstly, let’s start with how it can solve the pain points. 

    Like many other sectors, the insurance industry can often be bogged down by manual processes and legacy systems. On average, about 70% of an insurer’s annual IT budget is spent on maintaining its legacy systems.3 These systems increasingly are not fit for purpose, resulting in slow processing times, impersonal interactions and difficulty keeping up with the ever-changing risk landscape. 

    That’s where automation comes in. It eliminates the need for manual data entry and reduces the risk of errors. The benefits of automation range from increasing efficiency and streamlining processes to generating cost savings and improved customer satisfaction. And even low-code intelligent automation, like RPA, can be integrated with existing legacy systems, allowing those unable to upgrade to still streamline their previously lengthy and error-prone, paper-based processes. 

    Automation is essentially the gateway to AI. Think of it like the ‘brain and the body’. Automation is the body of your operations, tirelessly executing repetitive tasks. AI, on the other hand, acts as the brain; it analyzes data, identifies patterns and makes decisions, constantly optimizing and refining your automation processes. 

    Automating key processes streamlines operations and eliminates bottlenecks, ensuring your AI initiatives can scale. With operational efficiency in place, AI can then act as a powerful accelerator, driving significant throughput gains and propelling your business towards growth, with AI at the helm.

    Streamlining processes equals a reduction in costs

    AI and automation’s ability to streamline processes translates into significant cost reductions too. Repetitive tasks like data entry, document processing and initial claims triage can be effectively automated with AI, freeing up staff for more complex tasks. This reduces the need for additional administrative staff, leading to direct cost savings. 

    Additionally, as AI streamlines processes, it allows insurers to handle a higher volume of applications without additional overhead. As well as this, AI can usher in a new era of insurance fraud detection, protecting the industry from considerable financial losses.4

    The power of data

    As the insurance industry essentially runs on data, combining automation with AI allows insurers to analyze vast amounts of data at speed and intelligently extract key information, before making data-driven decisions. It simply allows insurers to deliver a more personalized and efficient experience, particularly for its customers. Automation plays its part here, as it can become a powerful tool for scaling data management as your AI initiatives evolve, making the data more accessible and usable for AI models.

    Conversational AI enhances customer service

    Another crucial aspect of the insurance industry is, of course, its customers. And solutions like AI chatbots are transforming customer service in the insurance industry. More specifically, AI chatbots powered by Natural Language Processing (NLP) and Conversational AI, can understand the nuances of human language and handle complex inquiries. These bots can even learn and improve over time through interactions, improving the process further.

    However, to truly take advantage of the numerous benefits of AI, insurance companies need to make sure that they’re first ‘AI ready’. 

    Building a blueprint for AI success

    More and more companies are recalibrating and second-guessing their initial enthusiasm for AI, most notably Generative AI, as they recognize it’s harder than expected to capture the massive potential for value.5 A haphazard approach won’t yield results. 

    The key to success, therefore, lies in a well-defined strategy – a blueprint for AI readiness. This starts with understanding your company’s objectives and its challenges. Identifying the specific pain points helps pinpoint where AI, combined with automation, can deliver the most value, before implementing specific use cases that will propel you towards that goal. 

    This strategy also requires companies to assess their existing processes and technology infrastructure. For AI solutions to thrive, an enterprise must have a solid infrastructure. Using your existing automation infrastructure, particularly your data infrastructure, offers a cost-effective and streamlined path to AI integration. The specific use cases you target will then guide your tech needs, allowing you to determine how to best use or augment your existing systems with new AI technologies or highlight where you need to prioritize upgrading legacy systems.

    High-quality data fuels AI success

    Data is both the lifeblood of AI and the insurance industry. However, poor data quality will only lead to unreliable AI outputs or poor decisions being made. Imagine feeding an AI model with data riddled with errors, inconsistencies or missing information. The resulting outputs will be unreliable and potentially misleading. 

    Automation, once again plays a crucial role here too. While it can’t fix bad data, automation is a cost-effective way to not only implement AI but also scale data management properly; it can provide AI models with richer data sources to deliver more accurate insights.

    Therefore, data management is essential. A successful AI strategy prioritizes data management, ensuring clean, accurate and well-organized data. After all, data is not static. It’s growing at a faster rate than ever before, with the volume of data across the world doubling in size every two years.6 For an industry that runs on data, processes must be in place early to ensure data is consistently collected, updated and maintained.

    The future of insurance is intelligent

    As AI continues to evolve, the insurance landscape will undoubtedly change. This future will be shaped by insurers who embrace AI. Those that do will unlock a wealth of opportunities to improve efficiency, personalize customer experiences and stay ahead of the competition. However, success requires a comprehensive approach that goes beyond data management and automation. There’s more to unlocking the true potential of AI.

    If you’re ready to find out what it takes to get your organization ‘AI ready’, take the quick, free AI Readiness Assessment.