Everyone’s shouting “AI!” but nobody’s fixing the broken back-end that’s eating your ROI.
Every InsurTech deck screams AI-powered. But under the hood? Most are duct-taping LLMs to workflows built in Excel.
We’ve entered the age of AI theater—flashy demos, mediocre results. If you want to build real value in insurance, stop chasing buzzwords and start fixing your ops.
The Automation Fallacy
- Claims APIs that don’t talk to your FNOL systems? Check.
- RPA scripts breaking every time a carrier updates a PDF? Check.
- Manual exception queues with no feedback loop to improve ML models? Triple check.
That’s not AI—it’s operational spaghetti with a sprinkle of Python.
Fix Your Foundation First
InsurTech winners like Tractable and Shift Technology succeed because they start with clean, interoperable data and build microservices, not monoliths. And they build tools that make human adjusters faster, not obsolete.
Others like Sprout.ai and CCC Intelligent Solutions show what’s possible when AI is layered onto workflows—versus attempting to overhaul them entirely.
Companies such as Snapsheet are demonstrating how virtual claims automation can function at scale, especially for auto and home insurers looking to enhance digital engagement.
Bold Penguin has also become an industry staple, proving that smart quoting and submission tools can reduce underwriter load and turnaround time significantly.
Human + Machine, Not Human vs. Machine
Instead of trying to replace adjusters, smart InsurTech is about supercharging them:
- NLP tools for summarizing long claims forms in seconds
- Anomaly detection that flags subtle fraud patterns
- Generative AI that suggests policy language alternatives
Don’t Forget Compliance
One of the biggest misses in current InsurTech AI tools? They’re not built for regulated environments. Any ML model used in pricing or claims decisions must be explainable, auditable, and compliant with state-level regulations.
This is where legacy systems like Guidewire and Duck Creek Technologies retain a foothold—by building around deeply entrenched compliance modules. New entrants must either plug into that world or reinvent it with clarity and confidence.
The Role of Scalable, Compliant Tech Stacks
This is where Microsoft’s cloud ecosystem quietly excels. Platforms like Azure AI, Power Automate, and Microsoft Synapse Analytics are providing insurers with scalable, security-forward environments to build real-world AI into claims, underwriting, and compliance workflows.
At Advancio, we’ve seen firsthand how deploying Azure Form Recognizer and OpenAI’s models within Azure Cognitive Services can reduce document handling time by over 60%, with full auditability and data residency compliance. Whether it’s automating FNOL with Power Platform or triaging complex claims using Azure Machine Learning, the focus is always the same: stability, explainability, and interoperability.
Our engineers—trained in Microsoft’s best practices and AI tools like GitHub Copilot and Azure DevOps Pipelines—focus on creating systems that don’t just demo well, but operate reliably in live, regulated environments.
The Path Forward
If you’re an insurer or MGA, start here:
- Identify your manual bottlenecks (claims triage, policy issuance, audit prep)
- Map where automation can assist—not replace—your teams
- Build with interoperability in mind: think APIs, not one-offs
Emerging Areas of Opportunity
- Document Intelligence: Tools like Hyperscience and Automation Anywhere are creating OCR and IDP platforms tailor-made for insurance.
- Claims as a Service (CaaS): Platforms like Verisk and Mitchell continue to evolve cloud-first claims ecosystems.
- Voice AI & FNOL Automation: Companies like Hi Marley are using conversational AI to humanize automation in customer interactions.
Done right, you’ll spend less time on workarounds and more on what matters: protecting policyholders and building sustainable growth.
Looking to explore where automation meets real-world insurance outcomes? Dive into our InsurTech Workflow Solutions to see what’s possible.
