AI for digital insurance: All you need to know

In 2025, AI for digital insurance will be one of the main transformation factors for the Insurance Sector.

According to McKinsey, over 70% of companies are already using AI technologies in at least one core function, and the trend is growing. From conversational chatbots to automated underwriting, to predictive claims management, AI is redefining operating models and customer experiences.

In this article, we explore the main use cases, benefits, risks and strategies for the effective adoption of AI in the insurance sector.

Updated on: June 9th 2025

Estimated reading time: 10 minutes

Why investing in AI for Digital Insurance

AI for Digital Insurance is rapidly transforming the insurance industry landscape, becoming a key element for innovation and competitiveness. Recent data clearly shows how the adoption of AI solutions is no longer a simple option, but a strategic necessity for companies that want to remain relevant and performing in the market.

According to a 2024 McKinsey study, as many as 92% of insurance industry executives expect a significant increase in investments in AI within the next three years. This data demonstrates a strong awareness of the revolution underway and the push towards the integration of AI in multiple business areas.

It is therefore not surprising that already today 78% of insurance organizations use artificial intelligence in at least one core business process, from the automation of back-office operations to claims management, to predictive analysis for risk assessment. This diffusion indicates how AI is becoming an essential element for improving operational efficiency and supporting faster and more informed decisions.

The opportunities for improvement are extraordinary: according to Deloitte, the insurance industry could see an increase in productivity of up to 82% thanks to the widespread adoption of AI. This increase not only reduces operating costs, but also frees up precious resources to be allocated to higher value-added activities, such as developing new products or improving customer service.

Speaking specifically of customer experience, a crucial area for retaining and attracting customers in an increasingly competitive market, Gartner estimates that AI represents an opportunity worth more than 100 billion dollars for the insurance industry. Thanks to technologies such as intelligent chatbots, personalized virtual assistants and advanced data analysis, companies can offer faster, more personalized and higher quality interactions, creating a real competitive advantage.

In short, investing in AI today means not only increasing efficiency and productivity, but above all building the foundations for a future in which insurance will be increasingly digital, personalized and customer-oriented. Ignoring this transformation would mean losing ground in a market that is evolving at an unprecedented speed.

AI Leading the Digital Transformation Process

Among the main trends driving the transformation of the insurance sector, the use of Artificial Intelligence Insurance as a tool for efficiency stands out, together with the focus on the differentiating value of the customer experience and the evolution of digital channels to attract the millennial customer segment.

According to the McKinsey report “The impact of AI in the future of insurance”, the insurance market is undergoing a transition process from a “purchase and annual renewal” model to a “Usage-based Insurance – UBI”, where
insurance product offers constantly adapt to the behavioral models of the individual and the products are disaggregated into sub-categories to meet the needs of micro-insurance coverage (for example: phone battery insurance, flight delay insurance, coverage for household appliances) that consumers can customize according to their needs.

This model is further favored by the possibility of equipping IOT devices with intelligence, which favors data collection by insurance carriers.

The IOT sensors of the devices installed inside vehicles or homes, facilitate the collection of data functional to the verification procedures within the claims opening process.

The information collected by the devices provided by the major companies is aggregated into a variety of data archives and streams.
These sources of information allow insurers to detect the risk profile and specific coverage needs of the buyer, offering tailored policies and rates.

Finally, the artificial intelligence of generative models can be used in the insurance sector to facilitate activities such as extracting information from long and complex documents, or as a tool for writing code for statistical models.

Types of AI for Digital Insurance

Artificial intelligence in the insurance sector is expressed in several specific technologies, each with targeted applications that revolutionize traditional processes, improve operational efficiency and enhance the customer experience. Let’s look at the main types of AI used and their areas of use:

• Generative AI (GenAI)
  Generative AI is able to create textual content, synthesize complex information and support activities that require understanding natural language. In the insurance sector, it is used to automate the drafting of detailed reports, such as the summary of complex insurance policies or the drafting of claim reports. This allows to reduce the time and costs related to document management and to improve the quality and consistency of internal and external communications. Furthermore, GenAI can assist operators in the assessment of claims, generating preliminary analyses based on data and documents provided, thus speeding up decision-making processes.
• Conversational AI and Chatbots
  The self-service insurance market is expected to grow at a compound annual growth rate of nearly 21% between now and 2029. Conversational AI solutions have become indispensable tools for ensuring 24/7 customer service. Chatbots and virtual assistants answer frequent inquiries, support new customer onboarding, guide quote management, and facilitate claims reporting and management. These tools improve customer satisfaction with quick and accurate responses, reducing the workload of human agents and allowing them to focus on more complex or sensitive cases.
• Machine Learning for dynamic pricing and predictive analytics
  Artificial intelligence based on machine learning algorithms allows you to process huge amounts of data to develop dynamic, more accurate and personalized pricing models. This means you can define policy prices that reflect each customer’s specific risk profile in real time, improving competitiveness and profitability. Furthermore, thanks to predictive analytics, insurance companies can anticipate events and behaviors, supporting proactive risk management and fraud prevention, as well as optimizing the customer portfolio.
• AI for regulatory compliance
  Compliance with regulations, especially in terms of anti-money laundering and data security, is crucial for insurance companies. AI tools dedicated to compliance automate the analysis of documents, transactions and suspicious behaviors, promptly identifying potential violations or anomalies. This automation helps reduce human errors, speed up verification processes and ensure continuous and efficient monitoring, keeping the company always aligned with current regulations.

The Potential of Generative AI for Insurance

According to EY, insurance companies aim to exploit the potential of generative AI to achieve three main objectives:

• Improve the experience of customers, agents, staff and employees through generative virtual assistants. AI allows to reinvent customer service and the development of new products, making personalized and empathetic interactions easier, freeing professionals from repetitive tasks.
• Increase productivity and efficiency by supporting key figures such as underwriters, actuaries and claims adjusters. AI synthesizes large volumes of data (transcripts, notes, legal and medical documents), significantly reducing claims cycle times, with particular interest in automation in underwriting and policy issuance, even without medical exams in person.
• Manage compliance and mitigate risks, through automatic monitoring, fraud detection and creation of training content to keep staff updated on regulations, fundamental aspects in a highly regulated sector.

To achieve better business outcomes, insurance companies need to effectively integrate generative AI into their existing technology infrastructure and processes. Generative AI is a tool that fits into a broader set of techniques and technologies. Therefore, insurance companies should improve existing processes and optimize them in parallel to get the maximum benefits from generative AI.

Benefits

The benefits of adopting AI for digital insurance are many and translate into a significant return on investment (ROI).

Reduction of operating costs by up to 30% in processes such as underwriting and claims management

The adoption of artificial intelligence allows for the automation of many traditionally manual and expensive activities, such as underwriting and claims management. Thanks to predictive models and advanced analysis tools, it is possible to assess risks more quickly and accurately, reducing errors and processing times. Similarly, automated claims management accelerates the collection and processing of information, reducing the need for human intervention and thus reducing operating costs by up to 30%. These savings not only improve company margins, but also allow resources to be reinvested in innovation and value-added services.

Improved Customer Experience: +15 NPS points thanks to quick responses and personalized interactions

Artificial intelligence enables more effective and timely communication with customers, through chatbots, virtual assistants and intelligent request management systems. This translates into a significantly improved customer experience, as customers receive quick and relevant responses at every stage of their journey, from acquisition to post-sales management. The personalization of interactions, made possible by the analysis of behavioral data and individual preferences, increases satisfaction and the perception of care, with an increase in the Net Promoter Score (NPS) of about 15 points, a clear signal of loyalty and spontaneous promotion of the brand by users.

Increased productivity: up to 82%

According to Deloitte’s analysis, artificial intelligence can increase the productivity of insurance companies by up to 82%, thanks to the automation of repetitive processes, the reduction of errors and the enabling of faster and more data-driven decisions. This greater operational efficiency allows operators to focus on higher value-added activities, such as managing complex customers or developing new products, increasing the overall production capacity of the organization. The integration of AI also promotes closer collaboration between teams and better allocation of resources, elements that contribute to making the business more agile and competitive.

Greater loyalty and retention, thanks to personalized and multi-channel communication

The ability to offer personalized and consistent communications across multiple channels – email, apps, SMS, chatbots, social media – is one of the most significant advantages of AI in the insurance sector. Thanks to continuous data analysis and intelligent recommendation systems, companies can offer customers customized products and services, anticipating needs and preferences. This approach not only improves engagement, but creates a stronger and more lasting relationship of trust, increasing retention and loyalty. A multi-channel and personalized communication strategy thus translates into a more stable customer base and greater long-term value for the company.

How to implement AI for Digital Insurance

Conclusions

According to McKinsey, the success of insurance companies depends largely on operational efficiency, which represents 60% of overall performance, more than simple product differentiation. Investing in AI for digital insurance, therefore, is not just a matter of technological innovation, but a strategic lever to optimize processes, reduce costs and build a sustainable competitive advantage over time.

Faqs about AI for Digital Insurance

Updated on June 9th 2025

• Insurance Chatbots Solutions
• How to employ AI in Insurance