Drawing on backgrounds in financial services regulation, governance and insurance technology, Mark and Rob explain why they believe the next generation of AI tools must go beyond black-box automation. Instead, they argue the future lies in combining the pattern recognition power of large language models with structured reasoning and transparent decision-making.
The discussion centres on the practical application of neurosymbolic AI, an emerging approach designed to deliver the benefits of generative AI while improving explainability, consistency and regulatory accountability. Through their placement copilot platform, Agentiv-x is aiming to help brokers compare policies more effectively, evidence the quality of their recommendations and reduce the risks associated with manual decision-making.
Set against a backdrop of growing regulatory scrutiny, increasing compliance demands and rapid AI adoption across financial services, the conversation explores what responsible AI implementation in insurance could look like over the next decade.
At the heart of the episode is a key question: as brokers become increasingly reliant on AI-assisted decision-making, how can the industry balance automation with transparency, accountability and human judgement?
In this conversation, Mark and Rob share:
- What neurosymbolic AI is and why it matters in insurance
- How Agentiv-x combines large language models with symbolic reasoning
- Why they chose to focus on brokers rather than underwriting workflows
- The challenges brokers face when comparing complex commercial policies
- How explainable AI can help reduce E&O exposure and improve client outcomes
- Why consistency and traceability are becoming central regulatory concerns
- How AI-native insurance businesses could disrupt incumbent market models
- Why brokers remain essential in AI-assisted decision-making processes
- How Agentiv-x is approaching claims advocacy using the same technology foundations
- What success looks like as the business moves towards its next funding round
