AI and rule-based automation in insurance

The Insurance Industry Is at an Inflection Point – and AI Is Leading the Charge From outdated systems and unstructured data to rising customer expectations and talent shortages — insurers are under immense pressure. But with Generative AI, there’s finally a real way out. What’s Changing? 1. 60% of operational costs are still manual – AI can slash that. 2. 80% of data is untapped – GenAI reads, learns, and leverages it. 3. Only 18% of insurers currently use AI – but that’s about to change. Key Impact Areas: ✅ Underwriting: 90% data accuracy + new product models. ✅ Claims: 70% of simple claims can be auto-resolved + up to 50% faster processing ✅ Customer Experience: 48% higher NPS, 85% faster resolutions ✅ Fraud Detection: AI flags 75% of fraudulent claims in real time ✅ Sales & Distribution: AI agents, personalized funnels, smarter upsells ✅ Policy Admin: Real-time compliance, automated changes, predictive lapse alerts ✅ New Products: From behavior-based insurance to once “uninsurable” tech like drones & autonomy It’s not just about automating workflows. It’s about rethinking the very DNA of insurance using AI-first foundations. And those who don’t adapt — risk becoming obsolete. Whether you're transforming an incumbent or building the next vertical AI unicorn — the time is now.

Insurers: EIOPA just dropped a clear AI rulebook. Keep models fair, use clean data, make them explainable, keep a human in charge, and protect them from hacks. Right size controls to the risk. If you use AI in pricing, claims, fraud, or underwriting, follow this shortlist: ✅map every AI use and owner; ✅test for bias before and after launch; ✅document purpose, data sources, and limits; ✅require human checks on big calls; ✅watch drift and quality; ✅lock down vendors and access. This Opinion turns guesswork into a clear playbook. Build to it so your AI stays fair, explainable, human in charge, and secure.

🚨 Hot off the press! 🚨 I’m honored to be featured in Modern Insurance Magazine – Issue 72 📰 with my article: “AI: Promise and Peril – How Insurance Leaders Can Harness the Power of Agentic AI and MARL Without Losing Control” 🧠⚖️🤖 🎯 In this piece, I explore how AI Agents and Multi-Agent Reinforcement Learning (MARL) are rapidly evolving from experimental concepts to enterprise-grade tools poised to reshape the insurance value chain. 🏗️ From automating claims triage to deploying self-learning fraud detection systems and optimizing underwriting in real-time, I break down how insurers can: ✅ Leverage Agentic AI to make smarter, faster decisions ✅ Deploy MARL-powered systems to dynamically adapt across complex processes ✅ Avoid ethical, regulatory, and operational pitfalls through robust AI governance and simulation platforms 💥 The article also outlines the 4 key pillars insurers need to master as they embrace intelligent automation at scale: 1️⃣ Intentional Architecture – Why point solutions aren’t enough anymore 2️⃣ Transparent Orchestration – The need for explainable, observable AI workflows 3️⃣ AI Governance at the Core – Managing risk, bias, and accountability 4️⃣ Business-Led Innovation – Enabling underwriters, claims leaders, and operations to safely experiment with AI Agents without waiting for IT 🔄 I also challenge the industry to move beyond narrow automation and begin simulating multi-agent business ecosystems that evolve, learn, and optimize autonomously. 👁🗨 Think of this as a call to action: Insurance firms must embrace a future where AI doesn’t just support humans—it collaborates, learns, and scales alongside them. 🤝🧠⚙️ I’m deeply grateful to be featured alongside a brilliant group of industry experts and innovators who are each transforming their corner of the insurance world: Katie King, MBA, David Alexander Eristavi Costas Christoforou, PhD, Darren Hall, Will Prest MBCS Lior Koskas Tracey Sherrard Jason Brice Simon Downing Mia Constable Nik Ellis Jane Pocock♻️🚙 Greg Laker – your perspectives on data, automation, ethics, claims, and the customer experience added incredible depth to this edition 🙌 🔗 If you’re an executive, innovator, or transformation leader in the insurance space, this one’s for you. Let’s shape the future of insurance—intelligent, adaptive, and human-centered. 👉 Contact me for more information about leveraging AI Agents in the Insurance Industry 🚀 #AI #Insurance #AIagents #MARL #AgenticAI #InsurTech #ClaimsAutomation #Underwriting #DigitalTransformation #FraudDetection #CX #ModernInsurance #ThoughtLeadership #ResponsibleAI #PX42AI #SimulationFirst #NoCodeAI #Governance

How Do We Audit AI Outputs and Ensure Accuracy? In insurance, intelligent automation isn’t enough. You need explainability, traceability, and operational oversight—especially when decisions carry real risk. At Agentech, we’ve embedded auditability into the core of our platform so Claims, IT, and Compliance leaders can inspect what they expect. Linked Decision Logic Every AI output includes a direct link to the policy clause, regulation, or business rule that informed the recommendation. No black boxes. Tamper-Proof Logs All decision activities are captured in tamper-evident logs—ready for internal compliance teams, regulators, or external auditors. Benchmark-Driven Validation Before deployment, agents are tested against real-world claim scenarios and validated against performance benchmarks set by the customer. Escalation When It Matters If confidence in an output drops or data is ambiguous, the task is automatically flagged and routed for human review—keeping critical decisions in the right hands. Governed Learning Framework Retraining isn’t reactive. It’s governed by structured reviews, not just system usage. That means improvements stay intentional and aligned with your goals. You don’t just deploy our AI. You govern it, trace it, and trust it. #AIinClaims #InsuranceAnalytics #Auditability #AICompliance #InsurtechLeaders #ClaimsExecutives #DigitalClaims