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AI & Automation
Where AI is actually moving work in life and annuity — underwriting, servicing, distribution — and what adoption takes inside a carrier.
Insights
All insightsThe Role of AI in Securing Insurance Data and Cloud Security
In an expert opinion piece for CXO Today, Zinnia India CTO Pawan Choudhary explores how AI and cloud computing are reshaping cybersecurity in the insurance sector, from real-time threat detection to blockchain-based policy records.
Read moreNovember 19, 2025How AI is Lowering the Barrier for Annuity Sales
In a feature for InsuranceNewsNet, Zinnia CEO George Esposito shares his vision for how AI is transforming annuity distribution, turning wealth advisors into informed retirement experts while building consumer trust through transparency.
Read moreJuly 1, 2025Rewiring Insurance: Zinnia's Vision for Blockchain, AI, and APIs
In a revealing interview with CXO Today, Josh Everett, CEO of Zinnia India, outlined how emerging technologies are fundamentally reshaping insurance infrastructure. Learn about Zinnia's strategic approach to integrating blockchain, artificial intelligence, and API-first architecture.
Read moreJune 3, 2025Inside the AI-Driven Hiring Wave in Insurance
When Zinnia hired an aerospace engineer for insurance technology, it wasn't an anomaly—it was a statement. Learn how Josh Everett and the India team are dismantling traditional hiring barriers and building a workforce based on technological capability rather than industry pedigree.
Read moreMay 21, 2025The Gen AI and Digital Dragons Insurance Revolution
Picture walking into an insurance office in 1983. File cabinets line the walls. A thick haze of cigarette smoke hangs in the air. Now fast forward to 2024. An agent is having coffee at home while her AI assistant analyzes 50 applications simultaneously.
Read moreMarch 6, 2025Beyond Traditional Underwriting
Beyond Traditional Underwriting Imagine reducing your underwriting decision time from weeks to minutes while improving—not compromising—risk assessment accuracy. This isn’t..
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Your AI Strategy Is a Document — The Operating Model Is the Difference
Sean O'Donoghue — Chief Digital, AI & Technology Officer at Security Benefit and Eldridge Wealth Solutions, who came to the retirement business by way of DreamWorks, Madison Square Garden, and Major League Soccer — argues that most insurance AI stalls not on the technology but on the operating model. He draws the line for Paul: a strategy is a document; an operating model is a system where everyone already knows who decides, who builds, how it's governed, and how data flows without needing a meeting. He reframes straight-through processing as table stakes and points to “the conversation around the button” — surfacing the consequences of a transaction just in time — as the next battleground, moves employees from “human in the loop” to “human above the loop,” and insists governance is a framework, not a committee, with the advice boundary built into infrastructure rather than decided by a model in a prompt. Security Benefit and Zinnia are affiliated companies under common ownership by Eldridge. Security Benefit is also a client of Zinnia. The views expressed by podcast guests are their own.
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AI Doesn't Know How to Do Your Job. You Do.
Jane Vevea spent 20 years in life insurance before anyone would have called her a tech person. She started at Prudential in 2006 running a retention call center, wholesaled through the bank channel at PNC, got laid off, and made a sharp left turn into insurtech. That detour took her through White Swan, then Atidot — where she was predicting lapses, surrenders, and upsell opportunities using AI before most carriers had even thought to ask the question — and now to xAI, where she works as a finance domain expert on large language models.
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Who Owns the Workflow? The Organizational Problem AI Actually Exposes
Wei Chen is an Associate Professor at the University of Connecticut School of Business and co-leader of the Digital Frontiers Initiative. His central argument: every serious conversation about AI and the workforce stops at the task level — which tasks AI can automate, which jobs are at risk. But tasks are only the bottom tier. The level that actually determines whether AI transforms an organization is the workflow: the connected chain of tasks that produces a business outcome. And the piece nobody's building is ownership — a named human who's accountable for the whole workflow, with the authority to stop it when something goes wrong.
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"You Can't Just Slap AI On It" — Brian Poppe's Four-Phase Test for Carrier AI Adoption
Brian Poppe — SVP of Life Insurance Solutions at Mutual of Omaha — has been an actuary, the entire innovation department, the Chief Data Officer, and now a P&L owner. In this episode he walks through his four-phase AI adoption framework, gives an honest read on where Mutual of Omaha actually sits (phases two and three), and explains why a memorial-book partnership he loved had to be killed because the timing of the offer was wrong.
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We Develop Products in Reverse Order — Eric Sondergeld on Insurance's Backwards Playbook
Eric Sondergeld — Managing Director at Greenwald Research, an actuary who spent years in market research at LIMRA before moving to custom research across life, annuities, and distribution — opens with the human cost of getting customer experience wrong. When his mother died in 2019, the life carrier bounced his claim between departments, sent a checklist of documents with an envelope too small to hold them, and never once expressed condolences. When his father passed this year, the same carrier had learned to say "I'm sorry" — but mailed a cryptic claim form and, this time, no envelope at all. From that story Eric builds his central argument: the industry develops products in reverse order, starting with the distribution it already has instead of the consumer it's supposed to serve, then stopping before it ever reaches the customer. Along the way he dismantles the idea of "best practices," explains why the industry's real superpower is copy-and-paste, names the third customer nobody designs for (the beneficiary), and gives a research veteran's read on synthetic respondents and AI moderation.
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The Robots Took the Easy Cases — What's Left for Human Underwriters
Frank Chechel — VP and Head of Individual Life Underwriting at Gen Re, and an actuary who fell into underwriting a decade ago building an R&D team — argues underwriting is only just scratching the surface after a hundred years. He and Paul trace how COVID turned accelerated underwriting from experiment into mandate overnight, why wellness programs went quiet and are now roaring back, and how to think about AI in three layers: predictive, generative, and the still-early agentic frontier. Frank is blunt about the limits: a summary that's 95% accurate is a good way to get fired, and the same case put in front of five underwriters yields five answers. The robots are taking the easy cases — which makes the human's job harder, not obsolete.
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"A Garage Full of Mac Minis" — AI, Angel Investing, and the Next Wave of L&A Innovation
James Wong built a massive IMO from scratch, sold it to a Fortune 500, and then launched The Founder's Chair — an insurance-focused angel investing platform that has funded 17 companies and deployed $11M+ in two and a half years. He breaks down what AI is actually doing to startup teams right now and shares his unfiltered read on the LPL-Anthropic deal and why it overnight made the biggest firms every startup's competitor.
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Why Half Our Company Are Engineers: Reinventing the IMO
Patrick Kelly, Co-Founder and CEO of Signal Advisors, breaks down his IMO 4.0 thesis — the idea that modern IMOs should implement best practices through technology, not just teach them. From founding RepPro to building an AI-native IMO in Detroit, Patrick shares what it took to create features like One Click Annual Review, TruePay, and Pay Later Marketing that are changing how advisors run their businesses.
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From the Rangers to Reinventing Annuity Applications
Andrew Barnett, VP of Technology Innovation at FIG, shares how a stint in minor league baseball led him to one of the most forward-thinking tech teams in insurance distribution. He breaks down FIG's work at the IRI hackathon — including an AI agent that calls clients to gather application data — and makes a compelling case for why the industry needs to stop planning to 2028 and start shipping in weeks.
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Ash Sawhney On The Future Of Underwriting And AI
Paul Tyler speaks with Ash Sawhney, President and Chief Revenue Officer of Zinnia, about the transformative changes in the life insurance and annuity sectors. They discuss the evolution of underwriting, the impact of technology and AI, and the entrepreneurial journey within the insurance industry.
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Zinnia Announces Collaboration with Snowflake to Deliver Real-Time Insurance Analytics and AI Solutions
Zinnia partners with Snowflake to deliver cutting-edge analytics and AI solutions that transform how insurers leverage data for real-time decision making with enterprise-grade security and scalability.
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Changing The Cost Structure Of The Life & Annuity Industry With AI: The Opportunities and Challenges
Panel Discussion at Hartford AI Day April 23, 2025 Panelists: Moderator: Paul Tyler, Head of Marketing Innovation at Zinnia Panelist: Dan Gremmell, Chief Data Officer, Zinnia Panelist: Manu Mazumdar, Head of Data Analytics Insurance Technology, Conning Panelist: Imad Eid, SVP Head of Salesforce Technology, Global Atlantic Panelist: Doug Elfers, VP, Data Science, Prudential [ ]
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Royal Neighbors of America® Modernizes Annuities Processing with Zinnia
Royal Neighbors of America launches The Policy Processor (TPP) with Zinnia, becoming the first carrier to process annuities on the AI-powered platform for streamlined case management.
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Zinnia Unveils The Policy Processor 8.0: An AI-Powered Leap Forward in L&A Underwriting
Zinnia announced the launch of The Policy Processor (TPP) 8.0, a cloud-based underwriting platform for life and annuity insurance carriers. The platform serves over 15 major North American carriers, processing more than three million applications annually.
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