| Link(s): | Regulating for Impact: Why MGAs Take A Leading Role in the Next Phase of AI‑Driven Insurance – MGAA |
Context
The Managing General Agents’ Association publishes a webpage which, this week, includes an article on Artificial Intelligence (AI). AI is becoming a major part of strategic decision making in insurance, including dynamic underwriting, real-time pricing, more efficient delivery of insurance, reshaping how insurance products are developed and personalised customer journeys.
The article states that the shift to AI presents an opportunity and MGAs are willing and able to act as early adopters of AI technologies and have an important role to play, but with opportunity comes responsibility, especially as Regulators sharpen their focus on AI’s risks and governance.
Key points to note and next actions
The article highlights key areas such as the following:
AI Regulation: Divergence and Direction: In the European Union, the AI Act is now in force. It implements a risk‑based framework that labels some insurance uses as high-risk – specifically, AI used for risk assessment and pricing for natural persons in life and health insurance. The EU is now also issuing voluntary early guidance for “systemic‑risk” AI models, those with significant economic or societal footprints, urging traceability, explainability, and risk mitigation before full compliance obligations apply.
The UK remains Regulator-led under existing laws (FCA, PRA, ICO, CMA) and the Consumer Duty. A government AI bill has been delayed into the next session; a Lords private member’s bill was reintroduced on 4th Mar 2025 but lacks government backing. This postponement comes amid some debate that the UK’s lack of binding AI regulation may leave businesses and consumers exposed.
Quality Data Is the Difference Between AI That Works, and AI That Hurts: In both the UK and EU frameworks, one principle remains non‑negotiable: AI’s value depends on its data. Without data maturity, even advanced AI systems risk producing unfair, opaque, or biased outputs, exposing firms to regulatory scrutiny and reputational fallout.
Agentic and Multi‑Agent AI: Agentic AI: systems capable of autonomous decision‑making and dynamic adaptation, under expert human-in-the-loop oversight. Soon this will expand into multi‑agent ecosystems, where agents across pricing, claims, fraud, and servicing collaborate in real time.