Weecover, an InsurTech platform specialising in insurance management and distribution technology, has argued that microservices architecture, not algorithms, is the decisive factor in successfully deploying artificial intelligence at scale across the insurance sector.
The intervention comes as AI dominates investment activity in the industry. According to Gallagher Re’s Global InsurTech Report Q1 2026, 95.2% of the $1.63bn directed into the sector in the first quarter of the year went to AI-focused companies. Despite this surge, the industry is confronting a significant gap between proof-of-concept initiatives and large-scale, profitable deployment, which Weecover identifies as the market’s most pressing challenge.
Weecover’s position is that the primary barrier to AI adoption is no longer the technology itself, but the rigid operational infrastructure of traditional insurers. Rather than pursuing wholesale replacement of core legacy systems, an approach the company considers both costly and risky, Weecover advocates a gradual, modular transition. This involves layering cloud-based solutions built on APIs and microservices architecture alongside existing systems, allowing new capabilities to be introduced incrementally without disrupting live operations.
To bridge the data fragmentation that commonly exists across disconnected legacy environments, the company also proposes deploying a modular middleware layer that functions as a translator between AI tools and legacy infrastructure, without requiring changes to underlying code.
Weecover is an InsurTech platform that has developed from an embedded insurance distribution solution into a modular SaaS platform serving as an insurance core system for managing general agents (MGAs) and insurers.
Weecover CEO Jordi Pagès said, “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.”
Pagès added, “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. 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.”
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