Bringing AI to insurance means improving the customer journey and customer satisfaction in a sector that is struggling to meet today's expectations in terms of customer experience. Always focused on risk management and customer protection, the insurance world is now at the crossroads between operational efficiency, innovation and a new centrality in services to citizens and businesses. Artificial intelligence in insurance is the engine of this transformation.
Table of Contents
- The Main Drivers of AI in Insurance
- How AI in Insurance Creates Value
- Winning Strategies of AI in Insurance
- AI in the Insurance Field: Tips & Tricks
- The Generative AI Transformation
- Conclusions
- FAQ
The Main Drivers of AI in Insurance {#drivers-ai-insurance}
According to Deloitte, AI is redesigning the insurance landscape along three main axes:
- Evolution of the operating model with an increasingly data-driven perspective: the extensive use of data allows for improved processes from risk estimation to claim settlement.
- Role of companies as orchestrators of multidisciplinary ecosystems: insurance companies become hubs of interconnected services that go beyond protection, involving mobility, health, home, climate and cybersecurity.
- Increasing the level of service offered, with more personalized, faster and more accessible experiences.
"Artificial intelligence is a game 'cubed' (AI³), where insurance becomes the protagonist of ecosystems, central not only for businesses, but for the entire society" – Andrea Poggi, Deloitte Central Mediterranean Innovation Leader
How AI in Insurance Creates Value {#ai-insurance-value}
1. Underwriting, Pricing and Claims Management {#underwriting-pricing}
AI in insurance allows for the automation and speeding up of complex activities, making it up to 10 times faster to estimate damages starting from images sent via smartphone, or to predict and settle a climate claim before it even happens, integrating billions of data points.
Generative AI also enhances decision-making processes, supporting professionals in risk assessment or fraud detection. Key benefits include:
- Automation of document analysis for underwriting
- Dynamic pricing based on real-time behavioral data
- Early fraud detection through pattern recognition
- Accelerated claims settlement with automatic damage estimates
2. Increasingly Personalized Customer Experiences {#personalized-experiences}
With AI in insurance, insurance agents become augmented consultants. Chatbots and AI agents help solve customer problems faster, increasing satisfaction. According to Deloitte, the adoption of AI allows intermediaries to resolve up to 40-50% more customer requests.
However, the gap between customer expectations and the services offered is still wide, especially in the life sector. Capgemini's World Life Insurance Report 2025 highlights that only 9% of companies have introduced truly integrated processes, capable of acquiring data from multiple sources to personalize the customer experience. The customer experience, especially among the under 40s, is often lacking in onboarding, assistance and claims settlement. Overall, one in two policyholders declares to be dissatisfied with their experience.
Yet, virtuous models exist: best-in-class companies have achieved:
- Net Promoter Score 38% higher than traditional competitors
- Expense/premium ratio 11% lower
- Revenue growth 6% higher
78% of them have automated underwriting and offer self-service portals, while over half manage claims intelligently thanks to voice and sentiment analysis through generative AI (Capgemini, 2024).
3. AI in Insurance and Embedded Insurance {#embedded-insurance}
Companies are bringing insurance ever closer to customers' life moments, integrating them into purchases and services (telco, e-commerce, banks, retail). This is the case of embedded insurance, particularly in Asia, where the market will grow to $170 billion by 2030 (McKinsey).
Even in Europe and Latin America, bancassurance and digital channels are establishing themselves as strategic levers for distribution.
Artificial intelligence can play a key role in enhancing embedded insurance – i.e. policies integrated seamlessly and contextually into products or services purchased by the customer – contributing in several ways:
- Real-time Personalization: AI analyzes customer behavioral, demographic, and purchasing data in real time to offer the right policy, at the right time, on the right channel. For example, when purchasing a smartphone or a trip, AI can suggest personalized insurance coverage based on the user's history and preferences.
- Automating Subscription Processes: Generative AI can simplify subscription by integrating it directly into the purchasing experience: through natural and modular language, it guides the user without interruptions, avoiding long and complex forms and facilitating membership with just a few clicks.
- Intelligent Claims Management: In the event of a claim, AI can enable automatic and contextual reporting (for example: accident during a covered trip), starting the process in the background and minimizing customer intervention.
4. Conversational AI in Insurance {#conversational-ai}
Conversational AI is transforming the way insurance companies interact with their customers, making assistance more accessible, faster and more personalized. Insurance chatbots are now able to provide immediate support 24/7, answering frequently asked questions about policies, guiding the user in modifying contractual data, activating insurance coverage or requesting personalized information.
These virtual assistants become strategic touchpoints along the customer journey, capable of increasing engagement, reducing abandonment rates and facilitating purchasing decisions. Thanks to natural language, access to real-time data and integration with legacy systems, Conversational AI in insurance allows for smooth and consistent experiences across all channels, helping to strengthen customer trust and reduce operating costs.
Furthermore, through advanced functions such as personality traits detection, these tools can intercept latent needs and offer a truly personalized service.
Winning Strategies of AI in Insurance {#winning-strategies}
According to Deloitte, 60% of AI initiatives in insurance are developed in partnership with third parties – insurtechs, technology providers, research centers and universities. This dynamic pushes towards collaborative and open models, in which companies are no longer just risk players, but solution hubs for the complex needs of people and businesses.
As also highlighted by McKinsey, companies can focus on three archetypes:
- Core players: large operators that focus on technical efficiency, claims automation and centrality of the customer experience.
- Innovators: companies that develop new products for emerging risks (EV, climate, cyber) and adopt alternative channels (embedded, retail partners).
- Niche players: insurance companies focused on specific segments or geographical areas, with strong customization and consultancy value.
AI in the Insurance Field: Tips & Tricks {#tips-tricks}
Integrating AI into the insurance industry is not just a matter of technology, but also of strategy and culture. Here are some practical tips to make the most of its potential:
- Start with low-impact but high-volume processes, such as FAQ automation or claims assistance, to obtain rapid and visible results.
- Leverage existing data, even unstructured (emails, documents, conversations), to train AI models capable of generating useful insights for the business.
- Collaborate with external partners, such as insurtechs, universities and technology providers: according to Deloitte, 60% of successful AI projects arise from strategic partnerships.
- Train your internal team: adopting AI requires new skills (data science, UX, prompt design) and an experimentation-oriented mindset.
- Don't forget empathy: AI can enhance human interaction, but not replace it. The best results are obtained by combining technology and human touch, especially in delicate phases such as claims management.
The Generative AI Transformation {#generative-ai-transformation}
According to Capgemini's World Life Insurance Report 2025, generative AI in insurance is a catalyst for transformation in the life sector, capable of:
- Improving onboarding with intelligent recommendation systems
- Enhancing self-service with chatbots and proactive portals
- Delivering more empathetic and transparent claims experiences with AI co-pilots and sentiment analysis
- Optimizing operational efficiency through automation, data governance and legacy system integration
Capgemini data shows a small group, equal to 5%, of leading insurance companies that use generative AI to offer a high-level customer experience for onboarding, self-service and claims management.
Conclusions {#conclusions}
The potential of AI in insurance is enormous, but it must be activated urgently. "It is still an open game, but it must be played proactively and promptly – because tomorrow could already be too late" (Deloitte, 2024).
To unlock this potential, qualified talent is needed. 67% of best-in-class companies say they are ready to integrate generative AI into their processes, compared to 25% of traditional insurers. However, 34% of leaders highlight the lack of key professional figures, such as behavioral scientists, experience designers and prompt engineers.
In this scenario, adopting scalable solutions such as AI agent building platforms represents a strategic lever. These platforms allow you to design, train and distribute AI agents capable of managing complex processes and advanced conversations, easily integrating with existing business systems. They offer modularity, speed of implementation and an intuitive interface, reducing dependence on highly specialized resources and accelerating time-to-value.
Success will not only depend on technology, but on the ability to attract and enhance human skills. Investing in AI in insurance does not only mean innovating, but also retraining people, renewing infrastructures, rethinking regulation and transforming the entire insurance system into a lever for growth.
To learn more about how Crafter.ai can support your insurance company, contact us at [email protected].
FAQ {#faq}
How is AI used in insurance?
AI in insurance is used in various areas: underwriting and pricing automation, claims management, 24/7 customer care chatbots, fraud detection, personalization of the customer experience and predictive risk analysis.
What are the benefits of AI for insurance companies?
The main benefits include: resolution of 40-50% more customer requests, damage estimation up to 10 times faster, reduction of operating costs, improvement of Net Promoter Score by 38% compared to traditional competitors and revenue growth 6% higher.
What is Conversational AI in insurance?
Conversational AI in insurance is the use of chatbots and virtual assistants to manage customer interactions naturally. These tools are available 24/7, answer policy questions, guide users through claims management and personalize the experience through natural language analysis and behavioral data.
What is embedded insurance and how does AI support it?
Embedded insurance is the integration of insurance policies into third-party products or services (e-commerce, telco, banks). AI supports embedded insurance through real-time personalization, automation of contextual subscription and intelligent claims management, making insurance a seamless part of the customer's purchasing experience.
How long does it take to implement AI in an insurance company?
Times vary based on the complexity of the project. Solutions such as chatbots and FAQ automation can be implemented in a few weeks. More complex projects of predictive AI or integration with legacy systems require several months, with a gradual approach that allows visible results from the early stages.
What skills are needed to adopt AI in insurance?
Adopting AI requires skills in data science, UX design, prompt engineering and an experimentation-oriented mindset. According to Deloitte, the most advanced companies also rely on external partners (insurtechs, universities, technology providers) to bridge the skills gap, especially in the early stages.
Can AI detect insurance fraud?
Yes, AI is particularly effective in detecting insurance fraud. Machine learning models analyze anomalous patterns in claims requests, compare documents and images, and identify inconsistencies in data provided by customers, allowing companies to significantly reduce losses from fraud.
How does AI improve customer experience in the insurance sector?
AI improves customer experience by making services faster, more personalized and accessible. Chatbots available 24/7, simplified claims processes, guided onboarding and personalized policy recommendations help reduce customer dissatisfaction – currently at 50% in the life sector – and increase loyalty.
