Jiali Digital Intelligence Transformation, Listed Insurance Companies' AI Competition Enters Deep Water Zone

The insurance industry is undergoing an AI-led “smart transformation.” Recently, top insurers in China—including China Life, China Ping An, China Taiping, PICC, New China Life, China Taiping, and others—have successively released their 2025 performance report cards. On April 1, a Beijing Business Daily reporter found that “digital and intelligent transformation” has evolved from a slogan into real operational investment for listed insurers. In an era when artificial intelligence is developing rapidly, many insurers have discussed the construction of financial technology capabilities in contexts such as annual reports and earnings briefings, including topics related to AI technology development and applications. Unlike earlier technology digitization focused on single lines of business, today’s “AI+” covers end-to-end business processes across insurers’ C-end and internal employees as well.

AI Penetrates End-to-End Business Processes

According to annual report data, in top-level planning, multiple leading insurers have increased the strategic weight of AI. At the same time, AI technology is breaking through traditional process bottlenecks, enabling a shift from “human-led” to “intelligent-driven,” significantly improving service efficiency and customer experience, and becoming the core engine for “efficiency gains.”

Since 2025, AI applications in China’s insurance industry have entered a new stage of large-scale deployment. Listed insurers have increasingly taken AI as a core strategic lever and ramped up resource investments. As Ping An explained, the group adheres to the principle of “AI in ALL,” customer demand-oriented and focused on empowering its main business, continuously investing in R&D to build leading technology capabilities based on four AI elements—algorithms, data, scenarios, and computing power. In 2025, more than 230k employees of Ping An used the company’s internal intelligent agent platform to develop over 70k intelligent agent applications, with 3.65 billion model calls throughout the year.

China Life also uses AI to improve quality and efficiency. In its annual report, it mentioned that it proactively aligns with the national “Artificial Intelligence+” action plan, building an AI capability system in an all-around way, covering every link of the company’s operations and management; and building a data space of “a hundred-dimensional labels from millions of data—thousands of features.”

When AI becomes “infrastructure,” what it brings is not only cost reduction, but more importantly “efficiency + quality,” penetrating end-to-end business processes. For example, China Life mentioned that large models empower agents to engage in professionalized and personalized business development, improving customer outreach efficiency; the number of annual customer visits increased by over 15% year over year. Allianz Insurance stated that AI technology has been deeply integrated into the entire chain of product design, marketing, underwriting, service, claims, and quality control. In private domain scenarios, AI customer service helps a single seat serve more than 100k terminal users. For health insurance cases, the rate of automated review exceeds 45%, enabling claims to be settled in as fast as 15 seconds; more than 76% of customers receive claim payouts within one working day. In the auto ecosystem, over 50% of cases achieve “instant connection, instant video, instant claim” via video; the fastest AI damage assessment time has been reduced to 116 seconds.

As Wang Peng, an associate researcher at the Beijing Academy of Social Sciences, analyzed, against the backdrop of fluctuations in industry labor scale, AI can significantly enhance total factor productivity. Through tools such as intelligent underwriting and instant claims settlement, insurers achieve second-level case closure and very high automation rates, greatly reducing operating costs and improving customer experience.

From Support Tools to a Strategic Engine

Looking ahead, multiple listed insurers have clearly identified AI as a long-term strategic direction. At a key stage of the industry’s digital transformation, AI is no longer merely an auxiliary tool for improving efficiency, but has become the core strategic engine driving business growth and reshaping the competitive landscape.

“AI is not an optional question—it’s a required question.” At the company’s earnings briefing, Zhou Xiaotao, the co-CEO of Ping An, stated clearly that Ping An is advancing the “integrated financial ‘nine-nine returns to one’” plan, aiming to integrate more than 700 million internet-registered users into a unified super entry point driven by AI. This will achieve comprehensive aggregation of traffic, entry points, and back-end data, enabling customers to complete a closed loop of medical, retirement, and integrated financial services within a one-stop entry point.

Regarding expanding AI applications, Qin Hongbo, vice president of New China Life, said that to achieve “let robots do the things robots should do, and let employees do the things that create more value.” With the arrival of the AI era, technological empowerment at New China Life has penetrated every link of business and management, becoming the core engine for New China Life’s high-quality development. New China Life will continuously maintain strategic resolve, investing both in people and in things, and under the guidance of the new technology plans for the “15th five-year” period, strive to make AI deliver greater effectiveness at New China Life.

At the earnings briefing, Ding Xiangqun, Chairman of PICC, stated clearly that positioning the technology line as an “accelerator,” and proposed that it should “more proactively seize opportunities in artificial intelligence development, deepen reform of the technology system and digital initiatives, accelerate the release of technology productive forces, and seize the commanding heights of digital and intelligent transformation.”

The implementation of strategy requires scientific methodologies and guidance. Fu Yifu, a special research fellow at Su Shang Bank, said that when insurers advance AI capability building, they should focus on three dimensions of coordination. On one hand, build an integrated foundation of data and computing power. The effectiveness of AI depends on data quality. Insurers need to break through the internal “data silos” that have long existed, while building mixed-cloud and private-on-prem computing infrastructure that complies with regulatory requirements, ensuring that data assets can be used intensively in a compliant manner. On the other hand, balance efficiency improvement with risk control. The financial industry has extremely high requirements for accuracy and explainability. AI applications need to establish supporting model governance systems, including algorithm audits, manual fallback mechanisms, and ethical standards, to prevent compliance risks caused by “black-box” operations. In addition, it is necessary to reshape organizational capabilities for human-AI collaboration. Deep penetration of technology requires redefining job responsibilities, focusing on cultivating the ability of front-line employees to collaborate with AI tools, rather than simply replacing roles; through continuous skill reshaping, organizations’ overall cognition levels are upgraded.

Beijing Business Daily reporter Li Xiumei

(Editor: Qian Xiaorui)

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