Most companies are stuck at Level 1 AI maturity today — running pilots, wondering why nothing transforms. The shift to Level 4 agentic workforces AI changes everything: 3x operational capacity, costs cut by 80%, expertise that compounds permanently. This isn't optimisation. It's a new workforce model. And for those who move first a 24-month implementation lead creates permanent advantage.

By 2028, knowledge-intensive companies will occupy one of two positions. Position A: 3-5x operational capacity, serving markets competitors can't profitably access, growing without proportional headcount. Position B: Explaining why they saw the transformation but approached it tactically. The difference isn't technology access — everyone has that. It's Level 3-5 Agentic AI implementation capability.

Insurance is uniquely exposed to ‘Agentic Commerce’ - AI agents buying and selling insurance on behalf of humans - due to five factors:

1. Standardized products, price-sensitive consumers: Insurance comparison is tedious—consumers want to delegate this.

2. Complex comparison processes: AI can do it better.

3. Renewal vulnerability: Consumer agents will conduct automated policy reviews.

4. Intermediary commoditization: AI makes aggregation instant.

5. Hidden information architecture: Carriers with agent-readable APIs will capture disproportionate share in early pilots.

Agentic AI drives the greatest growth and value potential when deployed strategically, rather than focused on existing processes and short-term efficiency gains. This video explains why and how, using cutting-edge case studies and proven frameworks.

The most urgent risk facing modern businesses — especially in insurance — isn’t cyber threats or bad AI investments. According to Simon Torrance (Founder of AI-Risk), it’s being outcompeted by rivals who deploy agentic AI better and faster than you.

100 trillion AI tokens processed last quarter prove the Infinite AI Workforce is already here. When Satya Nadella announced that Azure processed "over 100 trillion tokens [in Q3]" during Microsoft's recent earnings call

The Economist's lead story last week outlined the macro impact of AI: If Silicon Valley's AI predictions prove even partially correct, we're facing economic disruption comparable to the Industrial Revolution.

Why 'use cases' and bottom-up experimentation is exactly the wrong way to think about Agentic AI. It builds on our last article on the status of Agentic AI maturity.

Agentic Al in Insurance: what it is, how it works - and why you should adopt it... fast - Webinar with Simon Torrance

Through its five-phase methodology (Executive Illumination, Strategic Alignment, Rapid Prototyping, Scale-Ready Strategy, and Enterprise Activation), we're helping forward-thinking organizations deploy autonomous digital workers that can both operate independently and collaborate intelligently with human teams.

We look at how tomorrow's market leaders will use 'AI teammates' to capture 70% cost advantages while competitors remain stuck with basic co-pilots.

When executives discuss "Agentic AI", the conversation typically centres on futuristic-sounding concepts: intelligent digital workers, autonomous teams, and real-time orchestration across complex enterprise systems.

New global research just revealed something few enterprise leaders want to hear: AI maturity is falling, not rising.

Many Insurance companies still use AI as a “tool” — to write content or summarise documents. But the future lies in agentic teams, not just productivity hacks.

Agentic AI has gone from niche research to front-page tech in a matter of months. With OpenAI releasing customer service agents, and giants like ServiceNow demoing agent studios with thousands of synthetic workers, the conversation around AI has shifted — again.

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The article is 2130 words long and takes 7 minutes to read (but longer to digest…). It was updated slightly in June 2025.