Artificial Intelligence (AI) has established itself as the primary investment driver in the insurance sector. According to Gallagher Re’s Global InsurTech Report Q1 2026, 95.2% of the $1.63 billion invested in the industry during the first quarter of the year was allocated to companies focused on AI. However, the industry is now facing a harsh reality: moving from proof-of-concept (POC) initiatives to large-scale, profitable deployment is proving to be the market's greatest challenge.
Against this backdrop, Jordi Pagès, CEO and Co-Founder of Weecover, argues that the real obstacle no longer lies in developing or acquiring AI, but in modernising insurers’ rigid operational structures. "Many insurers are focused on building their technological future through in-house developments on top of extremely complex legacy systems. The real bottleneck to AI adoption is no longer the technology itself, but the operational architecture that supports it," says Pagès.
Coexistence with legacy systems: gradual modernisation without risk
For Weecover, the solution to this long-standing challenge is not to embark on risky and costly full-scale replacement projects. Instead, Pagès advocates complementing legacy systems with modular, cloud-based core solutions built on APIs and microservices, enabling new capabilities to be added gradually over time.
"Rather than replacing the entire core system overnight, insurers can adopt architectures that allow them to modernise progressively while continuing to operate their existing systems," explains the CEO of Weecover. "AI, automation and advanced analytics all depend on one thing: the ability to access, process and share data efficiently across the entire technology stack. Without that, innovation is simply not viable."
Supporting this view from a technical implementation perspective, Rafael Gallardo, CDO and Co-Founder of Weecover, shared several practical examples during his recent participation in an industry discussion forum: "A traditional core system that works does not need to be switched off. Thanks to modularity, we can connect a specific cloud-based module to launch a new product or pilot into the market within a matter of weeks to assess its viability, all while coexisting natively with the existing core platform."
He also warned of the commercial consequences of failing to embrace this change: "If AI takes two days to assess a customer’s risk because the legacy system blocks or fragments the data, competitors operating in real time will win the business. In the age of AI, slow decision-making exposes companies to highly dangerous adverse risk selection."
Data as the foundation: from disconnected silos to a middleware translator
Another critical issue highlighted by Weecover is the fragmentation of information across disconnected silos (such as isolated databases and manual interfaces), which prevents the creation of the robust, consistent and real-time data layer required by modern AI.
To address this technological gap immediately, Weecover proposes implementing a modular middleware layer. This technological component acts as a highly connected translator, enabling AI to interact efficiently with legacy systems without requiring any changes to their underlying code.
Towards a more human insurance sector
Ultimately, Jordi Pagès emphasises that architectural agility has ceased to be merely a back-office technical support function and has become a top-tier strategic business priority.
"The next chapter of insurance transformation will not be defined solely by algorithms, but by the operational and architectural capabilities that enable those algorithms to generate measurable business outcomes. Over time, AI will become accessible to everyone; however, operational excellence will be far more difficult to replicate. Insurers that invest today in modern, modular distribution platforms will be the ones shaping the future of the industry," concludes the CEO of Weecover.
Furthermore, the insurtech argues that the ultimate goal of this evolution is not to dehumanise the industry, but quite the opposite. By freeing professionals from cumbersome administrative processes through automation, insurance distribution and intermediation can focus on what technology cannot replicate: empathy, personalised advice and customer trust.