Insurance AI Brief: Automation Gains Speed, Funding Heats Up, UAE Market Accelerates
There's clear momentum in insurance automation. Pyq AI launched Mulligan for insurance automation, Stitch raised $3M to build an insurance-first agentic AI platform, and the UAE market is projected to reach $3.56B. The signal is simple: workflows are getting automated, distribution is getting smarter, and budgets are moving.
What's new
- Pyq AI introduced Mulligan to automate insurance tasks and workflows.
- Stitch closed a $3M Seed round (led by ManchesterStory and BrokerTech Fund) to build an agentic AI platform for insurance.
- The UAE insurance market is projected to reach $3.56B, with fintech rails and digital distribution pushing growth.
- Ongoing theme: automation and practical AI are moving from pilots to production.
Why this matters to your day-to-day
- Claims: Intake, triage, and subrogation can be automated to reduce cycle times and leakage.
- Underwriting: Data gathering, prefill, and risk summarization can shrink quote turnaround from days to minutes.
- Distribution: Agents get AI copilots for quoting, email follow-ups, and cross-sell prompts.
- Operations: Policy admin tasks (endorsements, bordereaux, compliance checks) get streamlined.
Agentic AI, in plain English
Think of an agentic system as a digital teammate that can read instructions, take multi-step actions, and report back. It doesn't just answer questions; it executes a process across tools and data sources, within guardrails you set. Good governance still matters-risk, bias, and auditability don't go away.
NIST's AI Risk Management Framework is a solid reference for controls and oversight.
UAE market snapshot: $3.56B projection
- Drivers: Fintech integrations, embedded insurance at point of sale, and digital-first distribution.
- Likely beneficiaries: Health, motor, and travel lines with high transaction volume and data flow.
- What to prepare: Local compliance readiness, Arabic/English data handling, and bancassurance partnerships.
How to act now (90-day plan)
- Pick 1-2 workflows with high volume and repetitive steps (e.g., FNOL intake, quote prep, endorsements).
- Run a contained pilot with clear success metrics: cycle time, touch reduction, accuracy, and loss ratio impact.
- Set guardrails: PII handling, access controls, human-in-the-loop thresholds, and error escalation paths.
- Score vendors on security (SOC2/ISO), integrations (APIs, RPA fit), data residency, and audit logs.
- Show the math: Time saved per task x volume x fully loaded cost. Reinvest the savings in scaling the wins.
Capability building for teams
Your advantage won't come from tools alone-it comes from people who can orchestrate them. Train adjusters, underwriters, and ops staff to write effective prompts, QA outputs, and standardize workflows.
Explore AI courses by insurance job function to upskill quickly.
Red flags to monitor
- Data leakage: Keep customer data within encrypted, governed environments.
- Hallucinations: Require reference citations for decisions; route low-confidence outputs to a human.
- Integration drag: Hidden costs appear when stitching legacy core systems to new tools-budget time for APIs and testing.
- Vendor lock-in: Favor exportable artifacts (prompts, workflows, datasets) and clear termination clauses.
What to watch next quarter
- Case studies from Mulligan and Stitch on measurable claim and quote improvements.
- Regulatory guidance on AI use in underwriting and claims decisioning.
- More embedded partnerships in travel, auto, and SME financing channels.
- Model upgrades that reduce hallucinations and improve reasoning on policy documents.
Keep it simple: pick one process, automate it end-to-end, measure it, then repeat. Small wins compound-and that's how real transformation happens in insurance.
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