# LLMs and Agentic AI in Insurance Decision-Making: Opportunities and Challenges For Africa

arXiv: https://arxiv.org/abs/2508.15110 · HTML: https://mlsanity.com/paper/2508.15110/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Placed in Financial trading and forecasting agents, one of 16 directions in LLM agents and tool use.
- Builds on 31 of its 91 references that are in the map.
- First posted on arXiv 20 Aug 2025.

## Placed in

- LLM agents and tool use / [Financial trading and forecasting agents](https://mlsanity.com/agents/financial-trading-and-forecasting-agents/)

## Builds on (most cited first, 30 of 31)

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- [Exploring the Limits of Language Modeling](https://mlsanity.com/paper/1602.02410/) (2016)
- [Collective Constitutional AI: Aligning a Language Model with Public Input](https://mlsanity.com/paper/2406.07814/) (2024)
- [AfroBench: How Good are Large Language Models on African Languages?](https://mlsanity.com/paper/2311.07978/) (2023)
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- [Charting the Landscape of African NLP: Mapping Progress and Shaping the Road Ahead](https://mlsanity.com/paper/2505.21315/) (2025)
- [GenRewrite: Query Rewriting via Large Language Models](https://mlsanity.com/paper/2403.09060/) (2024)
- [Large Language Model Capabilities in Perioperative Risk Prediction and Prognostication](https://mlsanity.com/paper/2401.01620/) (2024)
- [Actuarial Applications of Natural Language Processing Using Transformers: Case Studies for Using Text Features in an Actuarial Context](https://mlsanity.com/paper/2206.02014/) (2022)
- [PuoBERTa: Training and evaluation of a curated language model for Setswana](https://mlsanity.com/paper/2310.09141/) (2023)
- [Business and Regulatory Responses to Artificial Intelligence: Dynamic Regulation, Innovation Ecosystems and the Strategic Management of Disruptive Technology](https://mlsanity.com/paper/2407.19439/) (2024)
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- [InsQABench: Benchmarking Chinese Insurance Domain Question Answering with Large Language Models](https://mlsanity.com/paper/2501.10943/) (2025)
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## Abstract (arXiv)

In this work, we highlight the transformative potential of Artificial Intelligence (AI), particularly Large Language Models (LLMs) and agentic AI, in the insurance sector. We consider and emphasize the unique opportunities, challenges, and potential pathways in insurance amid rapid performance improvements, increased open-source access, decreasing deployment costs, and the complexity of LLM or agentic AI frameworks. To bring it closer to home, we identify critical gaps in the African insurance market and highlight key local efforts, players, and partnership opportunities. Finally, we call upon actuaries, insurers, regulators, and tech leaders to a collaborative effort aimed at creating inclusive, sustainable, and equitable AI strategies and solutions: by and for Africans.