37 PUBLIC GAMING INTERNATIONAL • JULY/AUGUST 2025 The AI Mirage: Why Smarter Doesn’t Always Mean Easier in the Lottery Industry Another AI story. Another industry article. Another promise that machines will revolutionize the way we work. But here’s the thing: artificial intelligence isn’t making life easier. It’s making it different. That subtle distinction might be the most important takeaway for anyone in the lottery business trying to make sense of the AI gold rush. For years, our industry has navigated a slow but steady evolution from gut-based decisions to data-backed strategies. What began as instinctdriven marketing matured into business intelligence. Customer segments were mapped and tested in a structured, measurable way. Then came the flood of machine learning with its promise of hyper-personalized experiences and real-time optimization. That was only achievable if you could afford the data scientists and infrastructure to make it work. Now, many lotteries are leaping over that middle step and diving straight into AI. On paper, it sounds efficient. You get faster analysis, automated insights, and predictive models. But in practice, it is a much messier knot to untangle. AI doesn’t remove complexity, it simply redistributes it. The data is bigger. The models are smarter. But the challenges are more opaque. At Intralot, we’ve seen both sides. We've invested in a proprietary AI tool called Nous.ai, trained exclusively on lottery-specific data. Generalpurpose models, while convenient, often miss the nuances. Using Nous. ai, we condensed a thousand-person segmentation study, and work that would’ve traditionally taken weeks was completed in just hours. We validated it against real participant behavior almost instantly. That’s the magic. Real-time insights at scale. But the cost was a significant upfront investment in time, talent, and infrastructure. It’s undoubtedly a long game. What AI gives in volume, it often lacks in clarity. We now face the paradox of choice. Instead of choosing between three products, we are choosing between hundreds. The real question becomes whether our organizations can keep up. Most legacy structures were not built for this kind of velocity. Creative teams, operations, and compliance are all suddenly expected to operate in a test-and-learn culture. That is the kind of environment AI thrives in. Making this shift is difficult for an industry rooted in risk mitigation. There is also the broader ecosystem to consider. The same algorithms that can personalize content and optimize spend can also be misused. Bad actors are already exploring ways to exploit AI in gaming. This is why responsible gaming must evolve just as fast. Thankfully, AI is well-suited to that challenge. It can monitor player patterns, identify outliers, and flag early signs of problem behavior. This is one of the most promising frontiers for ethical AI application. So, where does that leave us? Somewhere between cautious optimism and strategic skepticism. AI is not a shortcut. It is not a plugand-play miracle. It is a fundamental shift in how we collect, interpret, and act on information. This requires rethinking everything from tech stacks to team structures to how we define success. It’s tempting to imagine a future where AI runs seamlessly in the background. We might think it can crunch data while we sip coffee on the beach, but that is a fantasy. The more realistic picture is AI as a powerful partner. It demands a lot from us even as it delivers. AI might not hand us easy answers, but it’s giving us a whole new way to play the game. n By Adam Barry, Chief of Staff, INTRALOT, Inc. INTRALOT CMYK Matt Guide Orange: CMYK 0/70/100/0 Grey: CMYK 70/50/65/50
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