AI can accomplish many extraordinary things. Its abilities are being explored in numerous areas, including responsive gambling technology.
Here’s a striking statistic: according to a Swedish gambling study, there’s now responsive, AI-powered gambling technology that has 97% accuracy in detecting problem gamblers. In 2024, it saved platform operators €6 million.
This is significant given that traditional gambling tools are reactive, not predictive. AI of the sort mentioned above can detect player behavioral patterns before they escalate and cause the player serious harm.
This technology signals a pivotal change. AI can be leveraged not just for business value but as a proactive tool to address social issues like problem gambling.
To fully understand the scope and impact of this technology, let’s examine it in greater detail. This exploration will highlight the companies leading these innovations and discuss the broader implications for other industries as well.
Source: Freepik
Preventative AI in Action: Directly Addressing Problem Gambling
Modern responsible gambling platforms rely on machine learning methods that examine player behavior. For instance, there’s a gradient-boosted decision tree called XGBoost that is well-suited for identifying problem gamblers because it rapidly analyzes dozens of player tendencies. These include:
- deposit cadence,
- bet-size volatility,
- and the frequency and length of gaming sessions.
All of these combine to produce interpretable risk scores for each player. Operators wanting to get into this niche often train their models using data from past behaviors that have led to outcomes like self-exclusion or payment defaults.
When these AI models are deployed, they tend to notice clear and repeating behavioral markers indicating escalating risk in a player’s actions. The AI can track loss-chasing patterns, such as when a player is down big and starts making even larger bets to recoup their losses.
The AI might flag longer gambling sessions, especially if a player who used to log in for brief periods is now spending hours in a digital casino. Multiple-day or late-night sessions are also often considered problematic. Other features the AI looks for include more frequent deposits, bet volatility, and pauses and bursts that might indicate a player’s mounting emotional frustration.
With this type of AI, real-time monitoring engines are combined with transactional data feeds. They score each player’s account, and an intervention is triggered when the technology deems it prudent.
In the Swedish study mentioned earlier, the AI being used reported 97% accuracy using just 30 days of behavioral data. There’s also the SOFTSWISS Risk Scoring Tool that detects when players deposit €500 or more after midnight.
Another AI model can analyze text and identify potentially problematic gambling indicators by scanning customer emails. There’s also GameScanner technology, which currently monitors 9+ million players monthly across 39 countries.
In Canada, updated guidance from the Alcohol and Gaming Commission of Ontario (AGCO) Standards 2.10 and 2.11 is being used. It requires real-time behavioral monitoring for signs like repeated gambler deposits and prolonged sessions.
If players look for operators that infuse their platforms with preventative AI technology, it potentially benefits them. When the AI detects risk, it initiates interventions such as personalized alerts, reminders to take breaks, and suggestions for setting limits. The inclusion of such tech allows them to make safe choices with CanadaCasino platforms that align with more hands-on monitoring standards.
The Companies Making Responsible Gambling AI a Reality
Specialist vendors are quickly moving into the preventive, AI-based responsible gambling space. Let’s look at a couple of them.
Mindway AI
Mindway AI, based in Denmark, is one of the most visible players in this space, combining artificial intelligence with neuroscientific research. Its two flagship products, GameScanner and Gamalyze, focus respectively on behavioral monitoring and cognitive assessment.
The available data from GameScanner’s continual monitoring indicates that it can successfully detect at least 87% of the problem cases human specialists would flag. Mindway AI shows no signs of slowing down, either.
The company now has partnerships with Australia’s Crown Resorts, Sweden’s ATG, and Belgium’s PepperMill Casino, which recently onboarded GameScanner to strengthen player protection in both online and land-based operations. The Gamalyze product, which uses an interactive card-style game for decision-making pattern assessment, has been adopted by the Hellenic Gaming Commission.
In markets where regulators are focused on harm-prevention measures, the impact of these tools is impossible to ignore. Mindway AI has partnered with land-based analytics firms and mental-health providers. Platform integrations with companies like Finnplay and Bejoynd are now common as well.
SOFTSWISS
SOFTSWISS is another iGaming technology provider. Its Managed Services Anti-Fraud team has an AI-powered Risk Scoring Tool that identifies problematic gaming behaviors in real time. Clients report that in the first half of 2024, it saved them about €6 million and reduced year-over-year high-risk incidents by 33%.
The reported savings are mostly attributable to fraud prevention and earlier responsible gambling interventions. However, faster resolution of player complaints has also become a key focus of the Risk Scoring Tool. The tool won the EiGE Awards 2025 Excellence in Responsible Gaming Support.
These products typically operate under a SaaS model. Companies offering these tools have developed a value proposition that blends regulatory risk management with reduced fraud-related losses.
Industry sentiment regarding this type of AI use is also noteworthy. SOFTSWISS’s 2026 iGaming Trends report found that the use of preventative AI in the gaming sector is now seen by platforms as rating 8.41 out of a possible 10 on the scale of presumed importance. In addition, 56% of surveyed companies stated that AI integration is among their top three business priorities.
What Impact Does This Technology Have?
All of this leads to a key question, though: Is AI-based responsible gambling technology actually changing player behavior? Several large-scale studies suggest that it is.
Studies have shown that 65% of players reduced their gambling activities on days when they received AI-triggered warning messages. Of these players, 60% were still betting less 7 days later. Personalized messaging based on high losses, increased deposits, and extended session duration all seem to be impactful.
This type of personalization is scalable with help from AI. Players no longer get generic warning messages. Instead, they get highly personalized ones pointing to specific problem behaviors.
It seems advisable to tailor the message’s tone to the player. A low-risk player might need no more than an occasional gentle reminder. Higher-risk ones, by contrast, naturally need stronger prompts or direct offers of counseling or self-exclusion if they’re on a dangerous trajectory.
Regulatory requirements are fueling the growth of preventive AI gambling measures. In Ontario, the AGCO has required real-time behavioral monitoring since June 2025. Operators are required to track repeated deposits, excessive sessions, and any instances of apparent loss-chasing.
In the UK, there are mandated risk checks that trigger when a player wagers £5,000 per month or £25,000 per year. Brazil now requires AI monitoring for a gambling platform to get certified. Ghana has mandated biometric player identification, while the Gamalyze tool is prominently featured on the Hellenic Gaming Commission’s website.
Any gambling platform wanting to avoid regulatory penalties and license risks, regardless of the territory in which it operates, must be mindful of a shifting perspective on player health and wellness.
Where Ethics and Technology Meet
It’s evident that the same models protecting vulnerable players could be used to identify and target individuals with potential gambling problems. This raises uncomfortable questions about what an unscrupulous company might choose to do with them.
There’s also the question of privacy. Building accurate risk profiles requires close tracking of player behavior. The collection and retention of this data must comply with frameworks like the EU’s General Data Protection Regulation (GDPR) and California’s Consumer Privacy Act (CCPA).
In response to these concerns, some regulators have been pushing for “explainable AI.” This involves operators proactively using interventional technology only when the system flags a player who appears to be struggling with problematic behavior.
Anyone in the tech field or who is considering launching a startup should pay attention to this technology’s capabilities and limitations, as well as its implications for privacy and data. AI can be used as a powerful predictive tool, but the consensus is that it also shouldn’t directly violate anyone’s personal choices. Other industries, including e-commerce, fintech, and social media, should be watching and taking notes.
Learning how best to use this technology can be a difficult line to walk, but that seems to be what’s required, even as more AI models hit the market and are implemented by platforms and official government entities.
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