Mosaic Insurance, a global specialty insurer, has announced the launch of an AI Lab and Forward Deployed Engineer (FDE) Programme, designed to accelerate practical artificial intelligence (AI) adoption across its business functions.
Mosaic’s AI Lab is a new unit working across its businesses to develop and deploy in-house AI capabilities that improve day-to-day operations. The lab is focused on rapid delivery and measurable outcomes across functions, including underwriting, finance and global operations, with senior leadership prioritising use cases aligned with Mosaic’s automation strategy.
“Most of the market has spent two years running pilots. We decided early that pilots were not the goal,” said Mosaic Co-CEO Mitch Blaser. “Our AI Lab exists to build AI that runs in production, on real data, solving real problems—and the FDE model is how we scale that without losing the speed and discipline that makes it work.”
Mosaic has hired its first cohort of experts in AI, machine learning and data science to drive the project, with three graduates of the London School of Economics and one from the University of Nottingham, UK, joining the company’s London office.
The FDE Programme marks a shift from the more common pilot-based approaches to AI that have characterised much of the insurance industry’s engagement with the technology to date.
“The FDE model exists because pilots don’t scale,” noted Krishnan Ethirajan, Chief Digital & AI Officer at Mosaic. “You can run a pilot in a corner and declare success; what you cannot do is change how an institution underwrites, reserves, and makes decisions in isolation. Our engineers are embedded within our front- and back-office operations because that’s the only way AI actually changes anything.”
The new team of engineers works with underwriters, claims handlers and operations teams and is involved throughout each project—from understanding a business problem to solving it in production.
“Our AI Lab is built on three foundations,” explained Usha Badrinath, Mosaic’s Chief Data Officer. “It reuses AI infrastructure across projects, so each new delivery is faster to build, and ready for real production work. It draws on Mosaic’s own policy and loss data, so AI learns from the company’s experience rather than generic information. And it is trained on Mosaic’s own knowledge of how the business runs and the decisions we make, so its output fits the way our underwriting, claims, and operations teams work.”
“AI is a true differentiator for Mosaic and we’re well-positioned to scale its impact across our business,” added Ethirajan. “The AI Lab brings together our technology and underwriting expertise to develop practical solutions that strengthen decision-making, streamline operations, and give our specialists more time to focus on complex risks and client needs.”
