At MIC Global, we are not planning an AI transformation. We are living one and in 2026, the numbers are starting to show it.
The metric we use to hold ourselves accountable is one we believe every insurance business should be tracking: revenue per employee. It is the clearest way to see the gap between companies genuinely built for the future and those retrofitting for it.
Our target at MIC is $1 million per employee, after cost of goods. We are on track to get there.
The Number That Tells the Truth
Revenue per employee sounds simple. It is not.
In insurance, headline revenue figures mislead if you take them at face value. Claims are the cost of goods. Strip them out and you see what a business actually produces per person: the real output of its people, processes, and technology combined.
In the technology sector, this figure routinely clears $1 million. In traditional insurance, it falls well short. That gap is not incidental. It reflects decades of manual workflows and organizational layers designed long before AI made them redundant. The companies closing that gap fastest are the ones that started without the legacy. AI-native businesses built on embedded, parametric, digital-first models have a structural advantage that no transformation program can fully buy back. What is Embedded Microinsurance?
What Chubb’s Numbers Actually Show
Chubb recently announced plans to cut headcount by around 20 percent, targeting expense savings of roughly 1.5 combined-ratio points. Management expects 85 percent of major underwriting and claims processes to be automated, with a similar share of gross written premium flowing through fully digital channels. It is an ambitious program and a clear signal that even the largest global insurers are waking up to what AInative operations can deliver.
But the numbers deserve honest scrutiny.
Chubb employs around 43,000 people and generated $59.4 billion in revenue last year, roughly $1.3 million per employee on the surface. That looks impressive until one accounts for claims, which represent about 61 percent of revenue. Strip those out and true net revenue per employee sits closer to $540,000.
Solid by insurance standards. Still well short of the $1m net revenue per employee target.
If Chubb executes well, cutting headcount while growing revenue, it may increase this value and may reach $700,000 per employee net of claims. A real achievement at that scale. But still a target we are already aiming beyond.
Once you reach $1 million per employee net of cost of goods, you can grow revenue without growing headcount proportionately. Legacy scale cannot replicate that and this is where Talent and Tech converge to create exponential corporate value.
The compounding advantage of an AI-native model is this: once you reach that threshold, revenue can grow without headcount following it. Legacy scale cannot buy its way to the same outcome. The gap comes from technology, business model, and product innovation, or the absence of it.
Why We Can Get There
The answer is not technology on its own. It is the right technology, with the right people, used the right way.
We call this talent density. The concentration of high performers in a team matters more than the size of the team. High-density teams move faster, hold each other to higher standards, and produce far more output per head. In a lean, cross-functional business like MIC Global, where one person may cover underwriting, product, and partner delivery, talent density is not a philosophy. It is the operating model. We believe in our talent and providing tech that gives them the tools to succeed.
AI has dramatically raised the ceiling on what one talented person can produce. Tasks that once took hours, now take minutes. Work that required days of research and drafting happens in a fraction of the time. Our teams are reskilling around these tools. Our hiring reflects them. We are not replacing capability. We are amplifying it.
Business teams at MIC Global now build the tools they need. Engineering deploys, iterates, and builds on them further creating synergy and efficiency. The cycle from idea to implementation has been compressed in a way that would not have been realistic two years ago. What keeps our people moving is not rigid process. It is curiosity, and that tone is set at the top.
The Human in the Loop Is Not Optional
This part does not get said clearly enough in conversations about AI: the quality of the human in the loop determines everything.
AI is powerful. It is also capable of confident error. It assumes. It fills gaps. It can introduce inaccuracies plausible enough to slip past someone who does not know the business well. This is where talent density and AI intersect in a way that is non-negotiable for us.
Our people need to know this business and be experts in their fields. They need to live our values and understand our partners, our customers, and the specific realities of embedded income protection across global markets including Qatar, sub-Saharan Africa, the US, LATAM, and Southeast Asia. Without that knowledge and experience, AI output cannot be properly reviewed. Errors build quietly.
The best use of AI is not to remove human judgement. It is to free highquality human judgement from low-value work so it can focus where it matters most: catching edge cases, questioning assumptions, and bringing in contextual understanding no model has yet learned to replicate.
Curiosity and vigilance are not soft skills. At MIC Global in 2026, they are commercial advantages.
6 Countries to 24 in Twelve Months
Over the past year we expanded from 6 to 24 countries, growing our partner ecosystem across mobility, financial services, remittance, and telecoms, now protecting millions of people globally. We secured regulatory approval in Qatar, established a GCC expansion strategy with Qatar Insurance Company, and are rolling out across Kuwait, Oman, and Saudi Arabia.
None of this came from scaling headcount proportionately. It came from scaling capability through technology, talent density, and an operating model that was built AI-native from day one rather than adapted to AI after the fact.
This is what embedded microinsurance at scale looks like in 2026. Not a product bolted onto a legacy platform. A complete operating model built from the start around the technologies and principles that make $1 million per employee a realistic, measurable target. How MIC Global’s embedded microinsurance works?
Transforming vs Being
There is a real difference between an organization transforming toward AI and one that was built inside it. The first is retrofitting decades of process, culture, and headcount to a new way of working. The second just operates.
We are not planning to become an AI-native insurance business. We already are one. The $1 million per employee target, net of claims, measured honestly, is how we hold ourselves to account for what that actually means in practice.
For our partners, it means working with a business that moves fast, integrates cleanly, and maintains quality that lean teams sustain rather than sacrifice. For investors, it means revenue that scales without a proportionate rise in operating cost.
The industry is beginning to understand what AI makes possible. At MIC Global, we are already doing it
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About the Author
Harry Croydon is Co-Founder, President and COO of MIC Global. Connect with Harry on LinkedIn
