How Chris Cheatham Built Risk Genius and Milo to Make AI Work for Insurance Agents and Small Business Clients
Hosts of The Insurance Dudes Podcast — 1,000+ episodes helping insurance agents build elite agencies
The agents who will thrive in the next decade of insurance aren't the ones who resist technology, they're the ones who understand it well enough to use it as leverage and keep doing the things that technology can't do. Chris Cheatham has spent his career building exactly the kind of technology that creates this leverage, and his perspective on where AI fits and where it doesn't is among the most nuanced available from someone who's actually built it.
Craig and Jason sat down with Chris, a former lawyer, co-founder of Risk Genius, and driving force behind the Milo insurtech platform, to explore how he thinks about the intersection of legal complexity, machine learning, and the future of insurance processes for agents and clients alike.
The Legal Career That Made the Technology Obvious
Chris Cheatham's background as a lawyer gave him a front-row seat to one of the most persistent inefficiencies in the insurance industry: the gap between what insurance policies actually say and what clients and agents understand them to mean. Insurance contracts are extraordinarily complex documents. The language is precise but not accessible. The provisions that matter most in a claim scenario are often buried under layers of qualifications and exclusions that require genuine expertise to navigate.
This complexity creates real harm. Clients discover coverage gaps at the worst possible moment, when they're trying to make a claim. Agents spend enormous amounts of time on policy review that could be applied to client service and business development. Carriers face operational inefficiencies from manual document processing that creates bottlenecks and errors.
As a lawyer who dealt with complex documents daily, Chris recognized that this was a pattern recognition problem at scale. The documents were complex but structured. The questions being asked about them, "does this policy cover this situation?", were answerable through systematic analysis rather than genuinely creative legal reasoning. This was, in other words, exactly the type of problem that machine learning was becoming very good at solving.
Building Risk Genius: The Founding Story
Risk Genius was built on the conviction that machine learning could read insurance policies, all of them, simultaneously, consistently, and surface the information that agents and clients needed in a format they could actually use. The technical challenge was significant: training a model to understand insurance policy language required enormous amounts of labeled data and careful attention to the specific ways that insurance policies are structured and the specific questions that practitioners need them to answer.
The founding experience of Risk Genius taught Chris things about entrepreneurship that his legal career hadn't prepared him for. Building a technology company requires a different kind of problem-solving than building a legal practice, faster iteration, higher tolerance for uncertainty, and the willingness to launch an imperfect product and improve it in production rather than waiting until it's fully polished.
The insurance industry's response to AI in the early years of Risk Genius was mixed. Traditional carriers and agencies were often skeptical about tools that displaced established workflows, even when those workflows were inefficient. The champions of the technology were typically the people closest to the pain, the underwriters spending hours on manual document review, the agents frustrated by their inability to give clients quick, confident answers about complex coverage questions.
Milo and the Small Business Insurance Opportunity
The Milo spin-out represents Chris's application of the Risk Genius foundation to a specific market segment with particularly acute needs: small business insurance. Small businesses are systematically underserved by the insurance industry because their needs are too complex for fully generic products but their premiums are too small to justify the intensive manual attention that complex risk requires.
Milo's approach is to use AI automation to bring the efficiency of standardized products to the personalized accuracy that small business insurance requires. The platform handles the document-heavy, process-intensive parts of the underwriting and quoting workflow, allowing agents to serve more small business clients at a higher quality level without the time investment that currently makes small business insurance economically challenging for many agencies.
For the agents who figure out how to use tools like Milo effectively, the opportunity is significant. The small business market is large, underserved, and populated by clients who tend to be more engaged and appreciative of genuine advisory relationships than commoditized personal lines clients. The agent who can serve small businesses efficiently has access to a client segment that will refer prolifically, cross-sell multiple lines, and stay through market volatility because they value the relationship.
What AI in Insurance Actually Means for Agents
Chris's perspective on AI in insurance is deliberately non-alarmist. The concern that AI will replace insurance agents misunderstands what agents actually do and what AI is actually good at. AI is exceptional at pattern recognition at scale, consistent application of defined rules, and processing large volumes of structured data quickly. These capabilities are genuinely valuable in insurance.
What AI is not good at is the relational work that sits at the center of the best insurance relationships: understanding a client's unique situation in its full context, building trust over time, navigating the emotionally complex moments that arise when coverage is needed and claims are being processed, and advocating for a client when the carrier's initial response isn't right.
The agents who understand this division will use AI to handle everything in the first category and protect their time for everything in the second. The agents who fear AI will resist the tools that could make them dramatically more effective and eventually find themselves competing at a disadvantage with the agents who've embraced the efficiency gains.
What This Means for Your Agency
Audit your technology stack this month. Identify the three activities that consume the most of your team's time and ask for each one: is this a pattern recognition activity or a genuine relational activity? If it's pattern recognition, quoting comparison, policy review for standard coverage questions, follow-up sequence management, there's likely a technology solution that can handle it with less human time.
On the small business opportunity: if you're not currently serving small business clients, spend one hour this week researching the small business landscape in your geographic area. What industries are prominent? What are their most common insurance needs? The answers to these questions point toward the specific expertise you'd need to develop to serve this market well.
Connect with the insurtech community even if you're not a technology professional. Following companies like Milo and understanding what they're building gives you advance notice of the tools that will change your competitive environment before they arrive. The agents who are surprised by technology tend to fall behind the agents who saw it coming.
The Bottom Line
Chris Cheatham's career is a case study in applying a genuine outside perspective to an industry's most persistent problems. Legal training gave him a precise understanding of what insurance documents are and aren't doing. Technology gave him the tools to fix it. The result is a set of capabilities that will change how insurance is processed, and the agents who understand this change early will build meaningful advantages around it.
About Chris Cheatham: Chris is a former lawyer, co-founder of Risk Genius, and the driving force behind Milo, an insurtech platform that uses AI to make small business insurance more efficient and accessible for agents and clients alike.
Catch the full conversation:
Level up your agency:
Listen to The Insurance Dudes Podcast
Get more strategies like this on our podcast. Available on all platforms.
Related Episodes
What Educational Consultant Melissa Dillon Teaches Insurance Agents About Redefining Failure
From Network Marketing to 10 Medicare Policies a Week: Julian Chambers' Young Agent Success Formula
From Legal Frustration to Insurtech Innovation: Why Chris Cheatham Left Law to Revolutionize Insurance with AI
Ramis Hakim's Final Expense Playbook: Ultra-Specialization, Strong Culture, and Systems That Scale
Adam Pisani's 19-Year Insurance Playbook: Why 'Fire in the Belly' Is Still the Most Important Business Asset