You have probably heard that AI is changing every industry. Gaming platforms are one of the places where that is actually true and not just hype.
Not in a vague, futuristic way. Right now, today, the platforms where people play poker and casino games are running AI systems that do specific, measurable things. Some of it helps players. Some of it works against cheaters. Some of it is about pushing you to play more.
Here is what is actually happening, with real examples.
GGPoker Is Using AI to Catch Cheaters in Real Time
Online poker has a serious cheating problem. Bots, collusion, real-time assistance tools. These are not rare edge cases. A September 2024 Bloomberg investigation revealed an organised industry selling advanced poker bots and player profiles to private clubs. One set of bots on America’s Cardroom reportedly accumulated nearly $10 million in profits before being caught.
GGPoker responded by investing heavily in AI detection. Their system monitors betting speeds, fold rates, and decision patterns across millions of hands. It compares what a player does against databases of known cheating behaviours. If something looks like a bot, the system flags it.
Between 2023 and 2024, GGPoker blocked tens of thousands of accounts and confiscated millions of dollars from suspected cheating players. That is not a small operation. That is a scaled AI enforcement system running constantly in the background of every game.
In 2025, GGPoker also partnered with GTO Wizard to build a Fair Play Check system. It compares hand histories against solver outputs to detect whether someone was using real-time assistance during play. The collaboration led directly to 31 confirmed account bans. PokerStars and WPT Global signed up to the same initiative.
The arms race here is real. AI is being used to cheat. AI is being used to detect cheating. The platforms are not winning every battle but they are fighting it systematically in a way that was impossible before machine learning.
Casino Lobbies Are No Longer Static. AI Rebuilds Them for Each Player
When you open an online casino, you see a lobby full of games. That lobby is not the same for everyone anymore.
Boost Casino, part of the Entain group, partnered with ZingBrain AI in early 2026 to replace their static, manually curated lobby with an AI-driven recommendation engine. The system analyzes every interaction. Games searched, session length, device used, time of day, how long you played each title. It then rebuilds the lobby around what you are most likely to want.
The results from A/B testing were clear. Turnover per player went up. Gross gaming revenue per player went up. The number of unique games each player tried also went up. After the test, the recommendation modules became the primary way players discovered new titles on the platform.
This is the Netflix model applied to gambling. Netflix does not show you the same homepage as your parents. The algorithm knows what you watch and surfaces what it thinks you will watch next. Casino lobbies are now doing the same thing with slot games, live tables, and card games.
The practical question this raises is how these systems are built and managed. When a casino has 10,000 games from over 100 providers, organising that library so the AI can work with it properly is a serious operational challenge. The guide on how to Choose a Casino Games Aggregator gets into how operators evaluate the technology that sits underneath their game lobby, which is exactly where AI personalisation connects to platform infrastructure decisions.
PokerStars Is Watching for Problem Gambling Patterns
Not all AI use in gaming platforms is about extracting more money from players. Some of it is about identifying when someone is in trouble.
PokerStars has invested what it describes as millions in responsible gambling AI. The system monitors player behaviour for patterns that suggest problem gambling. Chasing losses, sharp increases in session length, betting amounts that jump suddenly, logins at unusual hours combined with erratic play.
When the system flags someone, it can trigger automatic interventions. A cooldown message. A prompt to use responsible gambling tools. In serious cases, temporary account restrictions.
This is not pure altruism. Regulators in the UK, Germany, and several other markets now require operators to have systems that monitor for problem gambling indicators. The AI makes compliance possible at scale. A human team could not monitor every session of every player on a platform with millions of users. The algorithm can.
The global AI gambling market is projected to hit $10 billion by 2027 according to Transparent Market Research. A significant chunk of that investment is going into exactly this kind of behavioural monitoring, both for responsible gambling compliance and for fraud detection.
Fraud Detection: The Layer Most Players Never See
Beyond poker-specific cheating, gaming platforms deal with the same fraud problems as any large financial platform. Bonus abuse. Multi-accounting. Payment fraud. Identity spoofing.
AI fraud detection systems monitor transaction patterns, IP addresses, device fingerprints, and payment method histories simultaneously. A player who creates five accounts using slight variations of the same name, different email addresses but the same device, claiming welcome bonuses each time is not going to fool a machine learning model trained on millions of similar patterns.
The fraud detection market across all industries was valued at between $33 billion and $50 billion in 2024. Three quarters of organisations now use AI for fraud detection because manual review cannot keep up with the volume and sophistication of modern fraud attempts. Gaming platforms are not exceptional here. They are just one part of a broader shift toward automated fraud prevention.
CrossClassify is one example of a platform specifically built for iGaming fraud. It handles behaviour monitoring, link analysis between accounts, bonus abuse detection, and multi-accounting identification. Platforms integrate it through an API so the detection runs in the background without disrupting the player experience.
Game Recommendations Are Getting Scarily Accurate
The Boost Casino and ZingBrain example is not a one-off. It is part of a wider industry movement.
Casino.org’s state of the iGaming industry report for 2025 described AI personalisation as the defining technology shift of the year. One quote from Casino.org’s casino editor summed it up directly: personalised slot recommendations and tailored bonuses based on your play are not on the horizon anymore. They are here.
The 2025 SOFTSWISS trends report highlighted AI use across personalisation, complex decision automation, responsible gambling, cybersecurity, and analytics as the five main areas of AI investment in iGaming. Personalisation was listed first because it has the most direct revenue impact.
Industry data from operators using deep personalisation shows staking increases of over 5% from the existing user base. That sounds small but on a platform doing hundreds of millions in monthly transactions, 5% is enormous. The AI does not have to be magic. It just has to be slightly better at surfacing the right game to the right person at the right moment than a static manually curated list would be.
The Part That Should Make You Think
Roar Tech Mental exists to question technology, not just celebrate it. So here is the honest version of what this all means.
The AI systems that catch cheaters and detect problem gambling are genuinely useful. They solve real problems at a scale that was impossible before. GGPoker catching tens of thousands of cheating accounts protects honest players. PokerStars flagging problem gambling patterns before they escalate can prevent real harm.
The personalisation systems are more complicated. The same technology that shows you games you are likely to enjoy also shows you games you are statistically more likely to spend more time and money on. The lobby that feels custom-built for you is optimised for operator revenue, not player wellbeing. Those two things sometimes overlap and sometimes do not.
According to the UK Gambling Commission’s research on online gambling behaviour, personalised marketing and algorithmic content surfacing are among the factors cited by problem gamblers as contributing to their gambling behaviour. The same AI that makes the lobby feel more relevant also makes it harder to stop.
None of that makes the technology bad. It makes it complicated. AI in online gaming is not one thing. It is a set of tools that can be used to protect players or to push them harder, and often the same platform uses both at the same time.
Understanding how it works is the first step to thinking clearly about it. Now you know what is actually running underneath the games.
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