Emerging Tech Impact Radar: AI in Insurance

In the end, it will assist employees with decision making and productivity, as well as helping improve customer satisfaction and online closure for digital channels. Insurance is a traditional business with many opportunities still for enhanced automation, such as the use of intelligence document processing (IDP). Generative AI will be leveraged by vendors in this market, introducing it to insurers as they purchase new automation tools. The use of digital channels, especially chatbots, is increasing as insurers seek to improve customer interaction and promote self-service. The incorporation of generative AI into chatbots to improve usability and outcomes will drive greater use of generative AI within the industry. Customer experience solutions will also leverage generative AI to enhance call center interaction. Synthetic data that is produced using generative AI techniques supports the accuracy and speed of AI delivery. Synthetic data draws customer and partner attention by helping them augment scarce data, mitigate bias or preserve data privacy. Gartner expects synthetic data to be available as part of most AI platforms. We predict that by 2025, synthetic data will reduce personal customer data collection, avoiding 70% of privacy violation sanctions. However, generative AI has limitations — ensure you do not overuse synthetic data, for example, when you need a real “ground truth.” Generative AI will disrupt software coding. When combined with existing development automation techniques, it has the potential to automate up to 70% of the work done by programmers. ML and NLP platforms are introducing generative AI capabilities, along with transfer learning for reusability of generative models, making them accessible to customers.

Recommended Actions:

Assess automation strategies to identify human-based work that can be augmented through the use of generative AI, including roles such as underwriting, claims, compliance, distribution or the contact center. Identify how generative AI can help with talent issues and productivity enhancement needed for each role. ■ Providers for insurance core systems, CX solutions, chatbots and IDP/automation should prioritize opportunities where generated AI data could benefit your existing product offerings. For example, it might be used to develop new digital channel capabilities that are tightly integrated with systems of record and harmonized data. ■ Examine and quantify the advantages and limitations of generative AI by analyzing where generative AI could bring breakthroughs, as it requires skills, funds and caution, then weigh technical capabilities with ethical factors. ■

Gartner, Inc. | G00786204

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This research note is restricted to the personal use of abhishek.sharma@fractal.ai.

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