Insurance insiders say AI has not met expectations yet but still holds future potential

For example, 22% of insurers in direct and agent channels reported large or very large improvements in sales, while 29% reported similar gains in customer experience due to GenAI. The survey found that 77% of insurance industry executives said they need to adopt GenAI quickly to avoid falling behind rivals. As a result, investments in GenAI are expected to surge by over 300% from 2023 to 2025 as insurers move from pilots to implementations across more business functions. However, the study also revealed a significant disconnect between insurers’ and customers’ expectations and trust in the technology, highlighting the need for careful strategy evaluation and responsible AI practices. IBM surveyed 1,000 insurance C-suite executives in 23 countries and 4,700 insurance customers in nine countries.

COVU, a company specialising in AI-native services for insurance agencies, has successfully raised $12.5m in equity and debt financing as part of its Series A funding round. The company will use mea’s GenAI-powered platform to automate and accelerate inbound submission management, significantly reducing the need for manual interventions. Or perhaps Big Blue could simply listen to customers, only 29 percent of whom are comfortable with generative AI agents providing service, according to IBM’s figures. Early adopters are already seeing benefits in key customer satisfaction metrics compared to insurers not using GenAI, according to IBM.

Agentech raises $3m to revolutionise insurance claims with AI-driven solutions

Claims processing is one of the areas in the insurance value chain ripe for automation, particularly concerning more straightforward claims. While most insurers have started taking steps to integrate AI solutions in the value chain, insurtech DGTAL has gone a step further, developing completely autonomous AI agents. Reportedly, it is the first insurance-focused AI company to use AI agents as a core element of its claims platform DRILLER. You can foun additiona information about ai customer service and artificial intelligence and NLP. Traditional AI solutions are programmed to provide a single response to a prompt, while according to DGTAL, its AI agents can operate real workflows and work together with other AI agents or human experts. Insurers can accelerate claims processing with the use of AI solutions, as these can scan vast amounts of data faster and increase accuracy. An increase in the speed of claims processing, as well as the ability to liaise with an agent 24/7, will naturally be beneficial for customers.

By focusing on ethics, compliance, and trust, the auto insurance sector is poised to tap into AI’s full capabilities while safeguarding the interests of its consumers. This strategic approach ensures that the benefits of AI are maximized, driving forward a future of innovation that is both accountable and consumer centric. Furthermore, the precision and reliability of AI operations depend heavily on the integrity of data. Reinforcing these data management methodologies is essential to ensuring that AI delivers precise, equitable, and ethical services.

Related practices, sectors and business issues

Manual claims processes result in not just high rates of denial, but lengthy delays and errors, as well. Insurers could use AI to accelerate the claims process, simultaneously improving productivity, resolving a longstanding customer pain point and improving access to care. For example, healthcare providers and insurers could tap AI to handle unstructured data sets from multiple sources, significantly streamlining data entry.

While gen AI is poised to revolutionize a whole host of industries, it’s important that the technology is leveraged as a tool to bolster human know-how and expertise, and not the other way around. When it comes to trade credit insurance, gen AI will play a support role, saving time so that the experts can focus on customer relationships and skilled analysis. People will also continue to play a critical role supervising the entire process and making the decisions. From time to time, a new technology comes along with truly transformative potential, and generative artificial intelligence (gen AI) is no different.

These are staggering figures that highlight the enormous potential of AI to overhaul claims management processes. Queen pointed out that while automation is beneficial, the most complex and judgement-based tasks in captive insurance ChatGPT will remain out of reach of AI for the foreseeable future. This reality limits the full potential of AI in the industry, although it underscores the importance of human expertise in areas such as claims management and underwriting.

Despite the known risk of levee breaches in New Orleans prior to the event[3], such scenarios were not incorporated into catastrophe models used for risk management at the time. As a result, many (re)insurers unwittingly had large flood exposure concentrations in the city, which translated into substantial losses when the levees failed, resulting in the costliest insured loss on record at the time. Peter Schwartz, an early pioneer of scenario planning, likens the use of scenarios to “rehearsing the future”[1], where the objective is to run through (or practice) simulated events as if we are already living them. This traditional approach to scenario development is notably time-consuming and resource-intensive. Transparency and accountability in AI systems are essential for fair and ethical operations. Insurers should provide detailed documentation and explanations of AI models, including data sources, algorithms, and decision-making criteria.

• As such, insurers must make sure that the rollout of their AI solutions, including AI-powered bots or digital avatars, is optimized to deliver the right experiences at the right time.
• Transparency and accountability in AI systems are essential for fair and ethical operations.
• With the new funding, Agentech intends to expand its AI-driven technology into adjacent claims processes like First Notice of Loss (FNOL), reserving, and file review.
• Beijing Dacheng Law Offices, LLP (“大成”) is an independent law firm, and not a member or affiliate of Dentons.
• As natural catastrophes become more frequent and severe, a growing number of insurance companies are turning to artificial intelligence solutions for predicting and managing extreme weather  risks.

For example, insurers are focused on using generative AI to improve customer service, but customers prioritize getting the right personalized products. Insurance giant Prudential is tapping Google’s MedLM, a family of foundation models fine-tuned for healthcare industry use cases, to transform the complex and fragmented health insurance experience for its customers. Everest expanded its accident and health (A&H) offerings with the launch of Innovator, an artificial intelligence (AI) powered international private medical insurance product designed to enhance employee health coverage standards. While AI offers automation and efficiency, Schmalbach warns that firms must strike a balance between human oversight and automation. As such, it is important to maintain a human element in decision-making and ensure that AI systems are regularly monitored and updated to prevent errors. “Leaders should have the room to concentrate on their vision for the company and what it can achieve — not be burdened by potential risks that keep them awake at night.

Ethical issues around AI decision-making and the absence of robust regulation are the most prominent concerns. KPMG’s 2023 Insurance CEO Outlook highlights that 52 percent of CEOs see these as highly challenging. And the tech report reveals that nearly two-thirds (64 percent) of respondents say that complex regulatory and tax developments have to some/greater extent made them feel less confident about investing in new technologies.

With 79% of consumers expressing trust in fully automated AI claims processes, insurers are tapping into AI’s potential to create tailored insurance products that meet individual needs. As AI tools analyze vast data sets, they not only expedite processes but also improve fraud detection and introduce efficiency and accuracy in auto insurance. The evolution of artificial intelligence (AI), including the new wave of generative AI (Gen AI), is transforming numerous industries. Despite the use of AI in a handful of areas and pilots taking place elsewhere, insurance organizations are not gaining an advantage on competitors by using this technology more widely.

Our experience shows how important it is to have the necessary tech talent and expertise in-house to effectively develop, fine-tune and deploy such solutions at scale. As such, the rise of AI creates a huge demand for experts in the field in the race to harness the insurance bots full potential of AI. For AI to be trusted and adopted by insurers, stakeholders must be able to interpret AI decision-making processes. Using personally identifiable information (PII) in AI processes poses risks such as data breaches and unauthorised access.

Enhancing Customer Experience

Artificial intelligence (AI) promises to supercharge productivity, improve customer experience and drive new business models, but the limitations and risks that come with technology have also come under the spotlight. The reinsurance industry’s ability to foresee and prepare for future disasters heavily relies on the breadth and depth of its scenarios. A significant challenge insurers face, particularly in the tail of the distribution, is the failure of imagination – when we overlook or underestimate potential risks that have not yet occurred in historical data. In such situations, the mind’s eye narrows, dismissing the unprecedented and sticking too closely to the beaten track of past experiences. This results in potential risk blind spots, leaving organizations vulnerable to highly disruptive events.

Investing in robust data management systems ensures that AI initiatives have the quality input they need to deliver meaningful results. Ilanit Adesman-Navon, Head of Insurance and Fintech at KPMG in Israel, highlights how AI can be used to guide ‘next best offer’ in more sophisticated ways. AI can be trained to understand sentiment, empathize with the customer situation, then guide agents to the most relevant, personalized offers — all of which could ChatGPT App be done in real time”. This collaboration underscores AXIS’s commitment to digital transformation and improving service efficiency for its global client base. Even when implemented, the pay-off from AI projects can be far less than hoped for by overexcited executives. Per the study, investments in generative AI are expected to surge by more than 300 percent between 2023 and 2025 as organizations move from technology pilots to implementation.

This naturally makes gen AI a great fit to augment our work, as the technology can be used to sort through huge quantities of data, extract any relevant information and be even more precise in how we analyze risk. It can also free up much of the time spent on repetitive tasks, making use of people’s expertise more efficiently and further tailoring the support and guidance we provide to our customers. One reason many insurers struggle to scale AI initiatives is their reliance on isolated use cases that fail to deliver significant ROI. Instead, companies should consider reimagining entire business domains—like claims processing, underwriting, and distribution—by integrating GenAI with traditional AI and robotic process automation (RPA). This holistic approach allows for a complete overhaul of how data is collected, processed, and utilised across the organisation.

As AI solidifies its position in the auto insurance industry, it is vital to foster a continuous and open dialogue among all stakeholders—insurers, regulators, technologists, and consumers. This collaborative approach will be instrumental in achieving balanced AI adoption, ensuring that innovation is pursued thoughtfully with ethical considerations at the forefront. The data lake used in Gradient AI’s AI-powered underwriting, called SAIL, allows insurers to gain predictive insights, enabling them to assess risks with speed and accuracy.

• This translates to faster payouts for customers and allows Prudential to manage a higher volume of claims, he added.
• By harnessing advanced AI and climate data, Adaptive Insurance offers businesses parametric coverage specifically designed for short-duration outages.
• They also know that innovation is a journey that requires ongoing effort, investment, and most importantly, a willingness to embrace change at all levels of the organization.
• In addition to the AI features, Alan unveiled a mobile shop from which users can buy dietary supplements, sports accessories, baby-related goods, and other health-adjacent products.
• Moreover, 73% believe that AI models help better manage climate-related losses, and the same percentage agree that carriers adopting AI models will gain a competitive edge.

Waiting times for queries that require human input will likely be reduced and customer service agents can focus on customer queries that require human input. You can’t go anywhere without hearing about the impact of generative artificial intelligence on … well, everything. Agentech’s platform currently automates up to 50% of manual tasks for desk adjusters, resulting in faster claims processing, improved customer satisfaction, and increased accuracy.

Also, it is paramount to ensure the proper guardrails are in place before releasing new AI-powered solutions, also to gain the trust of our clients and make them part of this journey. Industry applications today predominantly rely on traditional AI methods with a focus on automating routine tasks and extracting insights from vast datasets. This technology has played a vital role in portfolio management, risk assessment, streamlining claims and submissions processing, making it more efficient for insurers and customers alike. Founded in 2012, the company specializes in providing AI solutions for the insurance industry, particularly focusing on automating underwriting processes and improving operation efficiencies. The company’s software-as-a-service platform is designed to help commercial insurers enhance their underwriting results, reduce claim costs and streamline operations.