As the global life insurance industry grapples with the adoption of artificial intelligence, a pressing challenge has emerged: data quality. A recent study reveals that 78% of insurers struggle to get value from AI due to inadequate data readiness.
Data readiness is the biggest challenge in getting value from AI reported by 78% of global life insurers. This implementation aims to refine risk assessments and improve operational efficiency.
Global Variations in Data Readiness
While some regions excel in data readiness, others struggle to keep pace. Australia tops the list with 38% of carriers being “Optimal”, while Latin America lags behind with only a few carriers achieving this level. In contrast, 82% of carriers in Latin America are considered “Progressive”.
The US Life Insurance Industry: A Mixed Picture
In the United States, 66% of life insurance carriers feel unready for AI. Organisational alignment is identified as the strongest dimension, while sourcing and integration prove to be the weakest areas.
Research Findings
A recent study conducted by Equisoft, LIMRA, and Universal Conversion Technologies (UCT) reveals that most firms consider themselves “progressive” in terms of data perceived readiness. However, 46% of respondents claim they are not ready to implement AI. Furthermore, 87% of respondents currently use AI in operational areas such as underwriting, operations, and new business.
Expert Insights
According to Mike Allee, president of UCT, “Data is foundational to everything a carrier does, now and in the future. But carriers aren’t necessarily data ready for AI because they haven’t yet considered a wholistic view of their data practices.” He emphasizes that high-quality data is essential for any AI initiative, stating that bad data leads to flawed AI outputs.
Kartik Sakthivel, Ph.D., vice president & chief information officer at LIMRA and LOMA, agrees that “Data governance, quality, and integrity are crucial for harnessing the full potential of AI and driving meaningful business outcomes.” He stresses that organisations must prioritise these aspects to achieve success with AI.
Conclusion
In conclusion, data readiness is a significant challenge facing global life insurers. To overcome this hurdle, carriers must focus on improving their data practices, ensuring high-quality data, and aligning their data strategy with their AI goals. By doing so, they can unlock the true potential of AI and drive business success.
