To address these challenges, insurers are focusing on enabling their data ecosystems to support and scale AI.
This includes fostering a convergence that supports both real-time and batch environments, and developing data products to support specific use cases such as pricing optimisation and fraud detection.
Many insurers are also transitioning away from massive data warehouses towards a more compartmentalised approach tailored to specific business needs, known as data mesh architecture.
Talent Strategies Evolve to Support AI Adoption
The survey also highlighted a significant talent gap in the insurance sector when it comes to AI implementation. Respondents indicated they were least prepared in terms of talent availability and existing skillsets compared to other readiness factors.
To address this, insurers are rethinking their talent strategies and organisational structures. Many are prioritising candidates with digital literacy and AI knowledge for new job openings, while also focusing on developing their existing internal talent.
Some insurers are turning to AI itself to aid in talent development. For example, Zurich Insurance Group (Zurich) is using analytics to assess workers’ current skills and future skill requirements to curate learning and development opportunities.
Global Tax Rules Impact Insurer Strategies
In addition to AI adoption, insurers are grappling with the impact of new global tax rules. The Pillar Two tax laws, which require multinational organisations with €750m (US$817m) or more in annual revenues to pay a minimum tax of 15% on net income earned in each country where they operate, are set to take effect in many jurisdictions in 2024.
These new rules are expected to have a significant impact on insurers operating in low-tax jurisdictions. Bermuda, for instance, has enacted a Corporate Income Tax of 15% on businesses that are part of multinational enterprise groups with annual revenues of €750m (US$817m) or more.
To respond to these new rules, insurance tax departments are focusing on understanding the regulations, modelling potential tax impacts and analysing corporate restructuring considerations that could help mitigate adverse impacts.
The implementation of these new tax rules is likely to require significant investment in data collection and reporting capabilities, further underscoring the importance of modernising insurers’ data infrastructure.
As insurers navigate these challenges, the ability to effectively implement AI technologies while addressing data and talent concerns will likely be a key differentiator in the market. Sandee adds: “Insurers are building AI technology for the talent, by the talent.”
