Yannick Even

Scroll through LinkedIn and you’ll see two camps: • The Optimists painting Agentic AI as the savior of underwriting, claims, and customer experience overnight. • The Skeptics warning of runaway costs, regulatory chaos, and existential risks. Different words, same mentality. Both extremes miss the point. The truth? Agentic AI is neither a silver bullet nor a ticking time bomb. The real opportunity lies in orchestration of solving the last mile decision making where human judgment, legacy tech, and regulatory nuance collide. That’s the hard part, and it’s where most narratives stop short. At Genpact we talk about process DNA, the hidden complexity of how work really flows. Agentic AI will only succeed if it learns to navigate that DNA, not bulldoze over it. Insurance is built on trust, risk sense, and context. Automation alone won’t get you there, but an AI that can orchestrate across fractured systems, adapt to regulation, and augment human judgment? That’s where the value is. This isn’t hype or fear. It’s realism. And it’s more powerful than either extreme because it acknowledges insurance as it actually operates. Reminds me of Peter Drucker’s warning: “The greatest danger in times of turbulence is NOT the turbulence, it is to act with yesterday’s logic.” #AgenticAI #FutureOfInsurance #ProcessDNA #LastMileAI #DigitalTransformation #InsuranceInnovation

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It's time for the 2025 actuarial entry level recruitment season. The theme this year is artificial intelligence. Now, fortunately for aspiring actuaries, the market for interns and entry-level actuaries has not diminished significantly with the rise of artificial intelligence in the same way it has for many other technical fields. However, this process of applying for and accepting jobs is going to be affected by AI. The primary reason is that companies are seeing AI and agentic AI tools flood their applications, making it harder and harder to screen and identify the best candidates for the position. 1) They're gonna be using AI to review resumes, so make sure you use a standardized format with easy to read text and key pieces of information. 2) Make an effort to get to in-person conferences. Shaking hands with actuarial hiring managers and HR managers is a good way to help yourself stand out from the large pool of applicants that are pursuing similar positions to you. If you're in the Midwest, the Actuarial Development Institute is hosting a free career fair in Milwaukee, Wisconsin with 20+ Actuarial Employers. Comment for details!

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Feeling Stuck? While everyone talks about #AI transformation, fewer than 20% of companies are actually scaling generative AI meaningfully. Most remain trapped in endless experimentation—countless pilots that never deliver real business impact. The problem isn't technology. It's strategy. Too many organizations treat AI as another IT deployment instead of what it really is: a fundamental shift in how we compete and create value. Two strategic imperatives separate winners from laggards. First, AI transformation must be driven from the top with executive ownership, clear vision, and integration into core performance metrics. Teams need explicit direction to make changes of this magnitude. Second, focus beats fragmentation. Instead of chasing hundreds of use cases, concentrate on four to five critical domains where AI can reshape entire systems of work. Think complete customer lifecycles, not isolated tasks. These become your competitive battlegrounds. The companies pulling ahead aren't the ones with the flashiest demos or biggest budgets. They're making disciplined strategic choices and executing with operational rigor. Kudos to Chuck Whitten, Sarah Elk, Florian Mueller, and Richard Fleming with Bain & Company for sharing their insights. https://lnkd.in/e36Q_cwG

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Massive investment, minimal return - Enterprises invested $30–40 billion in GenAI, but 95% report zero measurable ROI. Only 5% of pilots deliver value, showing a stark “GenAI Divide” between winners and laggards High adoption, low transformation - Over 80% of organizations piloted tools like ChatGPT/Copilot, with ~40% deploying them. But these mainly boost individual productivity, not enterprise P&L. Pilots stall at scale - While consumer tools like ChatGPT see 83% pilot-to-production success, custom enterprise tools see only 5% reach production.

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AI isn’t all hype—or all risk. It’s both. Some headlines tell us that AI is the answer to humanity’s most pressing problems. Others warn us it could amplify misinformation, fuel delusions, or even put trust at risk. 👉 The truth—like in most meaningful transformations—sits somewhere in between. 💡 We need to resist the temptation of chasing the hype cycle. 💡 We also need to avoid the opposite trap: cynicism that blinds us to progress. Instead, leaders must build a balanced lens—curious about breakthroughs, critical about risks, and intentional about how technology is deployed. At its core, AI isn’t about hype or fear—it’s about choice. The choice of how we design and and apply it. The choice of using it to elevate human potential rather than replace it

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*Insurance cycles detection using neural networks* by hamza hanbali – published in the July 2025 issue of the Annals of Actuarial Science. Link to full text in the comments. Abstract: This paper utilizes neural networks (NNs) for cycle detection in the insurance industry. The efficacy of NNs is compared on simulated data to the standard methods used in the underwriting cycles literature. The results show that NN models perform well in detecting cycles even in the presence of outliers and structural breaks. The methodology is applied to a granular data set of prices per risk profile from the Brazilian insurance industry. #actuarialscience #research #insurance #cycles #neuralnetworks

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