In Las Vegas, a hotel-casino never sleeps. Every spin of a slot machine, every hand at a blackjack table, every drink order, and every hotel check-in generate data. For most people, those actions equate to an exciting atmosphere of lights and choices that fuel the fun of their vacation or brighten their evenings during a conference weekend. For Jennifer Lendler (McIntire ’86), those kinds of transactions represented something else entirely.
“It was this amazing time to look at an operation like a hotel-casino, with all those inputs,” she recalls. “That’s an ecosystem of a business. And there was so much data behind that. It was my playground.”
That instinct to see systems where others see chaos has defined Lendler’s career. Today, as Founder of Alea Advisors, she’s helping private equity firms and business leaders do something similar with artificial intelligence: cut through noise, focus on what matters, and drive measurable results.
“The disconnect is between the AI conversation and its true application in finance,” Lendler says.
Her message? The barrier to AI isn’t the technology itself. It’s people.
Inside the Patent: Applying Operations Thinking to Real-World Systems
Lendler’s credibility as a builder predates AI. During her time in the casino industry, she developed a patented optimization algorithm that treated the casino floor like a factory.
The model analyzed product mix, from table games to slot machines, alongside labor requirements and customer demand to optimize revenue and profit in real time. It was a complex balancing act that had not been attempted before.
“It’s an optimization algorithm that looks at all of that and says, on any given day, this is the way we should have a product mix,” she explains.
The idea was so novel that the U.S. Patent Office struggled to evaluate it, extending the patent’s life, once granted, well beyond the normal 20 years. For Lendler, the experience reinforced a core belief that meaningful innovation often takes time to be understood.
A Career Built by Turning Complex Data into Business Success
Though Lendler describes her career as “twisty-turny,” the throughline is unmistakable. A love of math, nurtured at McIntire, combined with an early fascination with invention fostered by her father, set her on a path toward solving business problems with data.
After starting in investment banking and earning a graduate degree in Operations Research and Statistics, Lendler made an unconventional and completely unexpected move into casino operations. As could be expected in a city like Las Vegas, the environment was intense, a 24-7 grind, but one that offered something invaluable: a real-time laboratory for decision-making at scale.
From there, Lendler moved into consulting, where the goal was always tied to outcomes. “How are we going to make more money? How are we going to improve our customer satisfaction?” she says. “It was always driven by financial outcomes.”
That focus led her to launch Alea Advisors, motivated in part by her father’s advice to own her intellectual property and patents by starting her own company. “I got my patent, picked up clients along the way, learned how to be an entrepreneur, and figured out what my value proposition was. It was a time of a great amount of learning, self-doubt, and confidence-building.”
A client led her into private equity, which gave her a front-row seat to volatility during the 2008 financial crisis. “We saw it all moment by moment,” she says.
Those experiences set her up for later roles at Aramark and Comcast, which also reflected another shift in her professional life. After years of traveling between Philadelphia and New York and missing time with her young son, Lendler chose to prioritize proximity to family without sacrificing impact.
At Aramark, she built a customer insights function from scratch. At Comcast, she led enterprise business intelligence, helping translate massive data sets into usable internal products.
Across every role, one lesson repeated itself: Organizations tend to resist change even when the data tells them it’s necessary.
“It’s oftentimes not the tech,” she says. “It’s the internal workings of a firm that stymies adoption.”
Using AI Agents to Drive Efficiency in Private Equity Workflows
That insight now sits at the center of Lendler’s work in AI. While the conversation around AI grows louder, she sees a gap between excitement and execution, especially in finance.
Through Alea Advisors, Lendler focuses on middle-market private equity firms, their portfolio companies as well as other small to medium-sized businesses, which often lack in-house AI expertise but that have highly repeatable processes across their functions.
Her approach is twofold.
First, as an adviser, she works with firms to identify specific workflows where AI can deliver measurable economic impact within a defined timeframe. So in a field like private equity, where exit horizons matter, that speed is critical.
Second, she focuses on the product. Lendler builds agentic AI tools that automate and accelerate core tasks. These include analyzing confidential information memoranda, drafting indications of interest aligned to investment criteria, reviewing nondisclosure agreements, translating documents to expand global deal flow, and supporting quarterly reporting to limited partners.
The impact can be dramatic. “Our agents enable an analyst to complete work that typically took six hours to about two minutes,” she says of one use case. “And it’s highly precise.”
Importantly, these tools are designed to be safe and enterprise-ready, helping firms adopt AI without compromising security.
She makes it obvious that the goal is not human replacement, but elevating people’s abilities.
“This isn’t taking work away. It removes the drudgery so people can do the interesting, higher-value work,” Lendler says.
Yet even with clear benefits, adoption often stalls. Many firms remain cautious, overwhelmed by headlines or hesitant to disrupt established workflows.
Her advice is direct and practical: “Stop analyzing it, and just go do it.”
News You Can Use: Practical Ways to Cut Through AI Noise and Start Using It Today
For leaders trying to make sense of AI, Lendler emphasizes practicality over perfection.
Start by acknowledging uncertainty. “If people feel scared or worried, it’s not unusual. We all are feeling that way,” she says. Disruption is uncomfortable, but it is also an opportunity to learn.
Next, experiment. “AI is being wildly democratized,” Lendler says. Tools are accessible, and many are safe to explore with the right precautions. Even small experiments can unlock new ways of thinking and working.
Focus on what matters now. Rather than getting lost in predictions about the future, seek out grounded perspectives, and apply AI to a specific business process that saves time or improves insight today.
Finally, maintain balance. The constant stream of AI news can be overwhelming. Lendler advises professionals to “meter the amount of time you spend thinking about it” and stay connected to the work and activities that bring meaning.
Above all, action beats analysis. Starting small builds confidence and momentum.
Why AI Needs a Seat at the Leadership Table
For Lendler, the path forward for organizations is not complicated. It simply requires a shift in mindset.
Private equity firms routinely rely on operating partners for areas like supply chain or finance. AI, she argues, should be no different.
“If you have an operating partner for supply chain, why not an operating partner for AI?” she says.
The hesitation often comes down to a lack of visibility. “You don’t know what you don’t know.”
Ultimately, her work is about closing that gap to help organizations move from being frozen in uncertainty to taking action. Because in a world increasingly shaped by AI, the greatest risk isn’t moving too fast; it’s not moving at all.
