AI
Should we fear Generative AI?
Nik McDonald, Senior Account Director at Fujitsu, says absolutely not but that it does come with some risks and drawbacks that organisations should be aware of.
What makes AI such a hot topic across the industry right now?
Operators and suppliers have come to understand that artificial intelligence can have a seismic impact on their businesses, whether that be streamlining internal processes or improving the solutions, tools, services and experiences they provide to their customers. But as the understanding of AI has deepened, so too has the awareness that the impact AI has can be both positive and negative. This has ultimately left some organisations nervous and unsure how to approach it, let alone integrate it into their workflows, services and products. And this is why it’s become a hot topic, with stakeholders across the sector keen to learn more about it.
Is there a certain type of AI that’s best suited to this industry? If so, what makes this type of AI such a good fit?
There are several types of AI including Narrow AI, General AI, Super AI, Reactive Machines, Limited Memory, Theory of Mind and Self Aware. The category most are interested in is Narrow AI and in particular, Generative AI – this is AI that can create new data including texts, images and videos by learning the structure and patterns of its training data to generate new ideas with similar characteristics. It can be trained to understand human language, programming language, art, chemistry, biology, law and countless other complex subjects and is often powered by Large AI models, often referred to as foundation models. This means Generative AI can perform a wide range of tasks including summarisation, classification and answering queries. This scope is what makes it ideally suited to businesses in this industry, regardless of whether they have a B2B or B2C focus.
Can you give a real-world example of Generative AI?
ChatGPT is the most famous example. It’s essentially a chatbot that runs on the foundation of large language models, trained on vast amounts of data to produce texts that humans understand. Users ask a question and ChatGPT breaks down the query into smaller components to analyse their meaning and determine what the user is really asking it to do. It then returns the words and sentences it thinks best answer the query based on the data it’s been trained on. It’s pretty cool, but it does have some drawbacks and risks to be aware of.
Could you explain some of these drawbacks and risks?
The accuracy of results is a big concern, as is inconsistent outputs, bias, lack of explainability and even threats to privacy, security and intellectual property. People often forget that ChatGPT is a public service and that as well as sharing information, it consumes it. This means users must approach with caution if using it in the workplace or to ask questions about proprietary and sensitive information and data. Users also need to cross-check the answers that are provided to their queries given the inaccuracies and biases it can have.
Does this mean Generative AI should be feared?
Not at all. Organisations should embrace the power of Generative AI and the clear benefits it can bring to their operations. We are already seeing companies use it, whether that be a slot studio harnessing its creativity to come up with new game concepts, designs, animations and even mechanics, to compliance platforms that use it to spot patterns in player behaviour. This sector has always been at the cutting edge, and I would include operators and suppliers to push the boundaries of AI but just to be mindful of some of the risks it presents.
How has Fujitsu approached Generative AI?
We have been busy developing a chatbot that’s similar to ChatGPT but that organisations can use with confidence. Instead of using publicly available data, it sits on top of the company’s data warehouse and allows teams and employees to ask questions and queries and have answers generated based on the proprietary data the foundation models have been fed on. Data can be siloed within the warehouse and with different levels of permission granted to different employees and teams. With our PrivateGPT, companies can really benefit from the power of Generative AI but with confidence that data is safe, secure and private, that responses are accurate and unbiased, and that the right level of permission is granted to individual employees.
Can you give an example of how organisations can use your PrivateGPT?
Our PrivateGPT has lots of use cases including being able to ask any question, chat with company data, find new answers and insights, foster deeper collaboration, jointly generate insight and evaluate results and develop decision support systems. Specifically, it might be a legal and compliance team wanting to ask a question about a previous market entry and a specific legal requirement, or it might even be to offer a consumer-facing tool where bettors can see how a team or player had performed across historic bet outcomes. This is what makes Generative AI so exciting and why it will continue to be a hot topic for some time to come.
AI
EveryMatrix launches Bonus Guardian to stamp out bonus abuse with AI precision
Reading Time: < 1 minute
EveryMatrix has launched Bonus Guardian, a next-generation AI-powered tool designed to help iGaming operators identify and prevent bonus abuse – one of the industry’s most damaging and rapidly-evolving fraud types.
Developed as part of EveryMatrix’s BonusEngine and EngageSuite stack, Bonus Guardian allows operators to maximise ROI on marketing spend by detecting fraudulent player behaviour before it impacts margins.
The solution uses AI and machine learning to continuously analyse player activity, adapt to new abuse tactics, and apply role-based responses such as bonus exclusion and withdrawal holds.
This ensures legitimate players continue to enjoy a seamless experience without restrictions and limitations, while abusers are stopped in their tracks.
Bonus abuse accounts for more than 63% of all detected fraud according to recent industry data. Fraudsters are increasingly using AI, automation, and synthetic identities to exploit promotional offers, while traditional, rule-based systems have struggled to keep pace.
Operators must also maintain friction-free onboarding and engaging rewards to stay competitive.
Bonus Guardian addresses this directly, offering a context-aware solution that can be integrated with operators’ systems, such as payment processing and player account. Unlike generic anti-fraud platforms, it is designed specifically for bonus abuse scenarios.
It continuously learns from real-time player data, reducing manual workload and false positives, helping operators:
- Prevent revenue loss by flagging and stopping bonus abuse early
- Improve segmentation accuracy and player lifetime value
- Reduce operational friction with intelligent, role-based fraud controls
- Futureproof operations against evolving fraud mechanisms such as deepfakes, AI-generated accounts, and coordinated abuse rings
Stian Enger, Head of Casino, EveryMatrix, said: “Everyone in iGaming knows about the battle between fraudsters and anti-fraud prevention tools. Each side wants to get ahead of the other, but with Bonus Guardian, we strongly believe we have a definite edge.
“Bonus Guardian is not just another fraud filter. It is a living shield that adapts to everything that is thrown at it thanks to the power of AI.”
The post EveryMatrix launches Bonus Guardian to stamp out bonus abuse with AI precision appeared first on European Gaming Industry News.
AI
Movers and Shakers – From Data to Decisions: What It Really Takes to Make AI Work in iGaming
Reading Time: 3 minutes
“Movers and Shakers” is a dynamic monthly column dedicated to exploring the latest trends, developments, and influential voices in the iGaming industry. Powered by GameOn and supported by HIPTHER, this op-ed series delves into the key players, emerging technologies, and regulatory changes shaping the future of online gaming. Each month, industry experts offer their insights and perspectives, providing readers with in-depth analysis and thought-provoking commentary on what’s driving the iGaming world forward. Whether you’re a seasoned professional or new to the scene, “Movers and Shakers” is your go-to source for staying ahead in the rapidly evolving iGaming landscape.
By Claudia Heiling, Co-Founder & COO, Golden Whale
For years, iGaming has considered itself a data-driven industry. We’ve all spent time refining segmentation, optimising CRM journeys, mapping behavioural signals, and building increasingly complex player models. And with machine learning now widely available, whether bought, built, or borrowed, it would be reasonable to assume that the industry is already fully realising the benefits of AI.
But speak to most operators, product teams, or data leads and you’ll hear a different story.
There are models running somewhere – and usually several. There are predictions being generated. There are dashboards, reports, and insights circulating. Yet the business impact often feels inconsistent. Some initiatives deliver a clear uplift; others stall or never make it past a proof-of-concept stage. Projects that shine in testing environments don’t always translate into live, reliable operations.
The issue is rarely the model. And it’s rarely the data team. The gap is operational.
It’s one thing to build machine learning models. It’s another to make them function as part of the daily working rhythm of an iGaming business.
The operators and providers seeing the strongest and most reliable gains are the ones who treat AI not as an experiment, but as a capability: something that must be designed, deployed, monitored, re-trained, and continuously improved. This is closer to how we already treat core game operations, promotional systems, risk tooling, or CRM orchestration. It’s iterative, structured and ongoing.
In practice, that means building the frameworks around the models, not just the models themselves. Continuous data flows. Automated re-training. Real-time deployment pipelines. Feedback loops that allow systems to learn not just once, but constantly. When we work with iGaming clients who have embraced this operational mindset and leverage our ready-to-deploy MLOps system built for iGaming, the impact becomes both compounding and predictable.
The other shift happening is cultural. There has been a lingering expectation in some corners of the industry that AI will replace manual decision-making entirely and that it will “take over” processes like CRM optimisation, fraud detection, or product adjustment.
That’s neither realistic nor particularly desirable.
iGaming is too contextual, too human, too dependent on craftmanship and intuition.
The real value of AI is in augmentation: giving teams better visibility, faster feedback, and stronger evidence on which to base decisions.
In organisations where this mindset has taken hold, you see a different dynamic.
CRM teams run more experiments, more often, because they aren’t spending time rebuilding segments from scratch. Analysts spend less time on manual spreadsheet simulation and more on strategic exploration. Live-ops managers can respond to player behaviour as it changes, not after the weekly report comes in.
AI becomes the layer that enhances judgement, rather than replaces it.
And when AI is integrated technically and culturally, the commercial outcomes are hard to ignore. In setups where continuous learning pipelines are properly established and aligned with live operations, we’ve seen engagement and retention metrics improve dramatically and sustainably, with activity and revenues rising by 100–200%, while bonus and incentive costs drop by 20%+, driving growth and both securing and expanding market share. Operational teams benefit too, with workflows becoming smoother and less manual because the system is handling the constant data processing and iteration.
The improvements don’t come from having more complex algorithms. They come from having a structure that allows those algorithms to perform reliably, adapt to change, and keep learning over time.
This is where the conversation about AI in iGaming is quietly changing.
It’s no longer dominated by model performance or dataset scale, rather it is focused on repeatability, reliability and learning speed.
The distinction matters because it separates having AI, from running AI.
And the operators and providers who get this right aren’t just improving performance in the short term. They are building organisational momentum, a capability that compounds over time and is very difficult to replicate quickly.
In a sector defined by tight margins, competition and rapidly shifting player expectations, that advantage is significant.
So, if there is a “next step” in the industry’s AI journey, it’s not a more complex algorithm. It’s not a bigger data pool. And it’s not a new suite of predictive dashboards.
It’s the ability to learn continuously, responsibly and at scale.
Because in iGaming, as in intelligence, data alone doesn’t win. What wins is the ability to turn learning into action again and again.
The post Movers and Shakers – From Data to Decisions: What It Really Takes to Make AI Work in iGaming appeared first on European Gaming Industry News.
AI
Xtremepush’s CRM Services Integrated into EveryMatrix Platform
Reading Time: 2 minutes
EveryMatrix global customers now equipped with seamless access to award-winning loyalty and gamification offering
Xtremepush, the leading provider of CRM and loyalty marketing powered by AI, has announced its latest tier one partnership, having agreed a deal to provide acclaimed igaming provider EveryMatrix with its award-winning CRM and loyalty marketing services.
EveryMatrix, leveraging Xtremepush’s varied product suite, will now be able to offer its customers real-time, hyper-personalised CRM and gamification capabilities via its proprietary platform, helping them to drive engagement, increase loyalty, and maximise the lifetime value of all player types in a seamless manner.
Xtremepush leads the market in its unified, holistic approach to data collection, with its Single Customer View built to extract data from all sources in true real-time, providing an individual view of players to deliver a higher standard of omni-channel personalisation and messaging. Coupled with a gamification engine and AI-powered automation and data insights, operators will be able to leverage these revenue-driving tools via their existing integration with EveryMatrix.
Tommy Kearns, CEO and co-founder at Xtremepush, said of the partnership: “EveryMatrix has built a well-earned reputation for being a provider of best-in-class sports betting and gaming solutions for its operator partners, and we’re pleased to bolster their software and services with our first-rate CRM and loyalty solutions.
“Regulated markets are hugely competitive and Xtremepush has proven its worth in optimising and scaling customer’s loyalty engines and processes in these environments to realise greater engagement and ensure maximum lifetime value of players. We’re very confident that we’ll showcase this once again with EveryMatrix, via its clients, and to make them another customer for life.”
Kevin Furlong, Chief Product Officer, EveryMatrix, said: “Alongside our advanced turnkey platform technologies we have always partnered with best-in-class third-party suppliers such as Xtremepush providing added value to our customers.
“Combining our market-leading gaming infrastructure with Xtremepush’s powerful CRM technology will enable our customers to better understand their players, offer them even more personalised experiences and boost loyalty levels to name just a few benefits.”
Following a successful launch phase with EveryMatrix, Xtremepush will make additional services available to the supplier, including its Agentic AI, which will supercharge marketing processes with intent and iteration, allowing related teams to focus on broader strategy and value-driven projects.
The post Xtremepush’s CRM Services Integrated into EveryMatrix Platform appeared first on European Gaming Industry News.
-
Latest News7 days agoBoomerang Partners has been included in 3 prestigious industry Awards, which will be presented in January 2026
-
Latest News6 days agoKazakhstan Authorities Dismantle Large-Scale Illegal Payment Scheme Linked to Online Casinos
-
Fernando Di Carlo CEO of Yellow Elephant Studios7 days agoSCCG Announces Strategic Partnership with Yellow Elephant Studios to Expand Multi-Channel Gaming Content Worldwide
-
Alyona Suvorova6 days ago
Law enforcement officers from Kazakhstan eliminated the organized financial criminal group organized by Vadim Gordievsky, Larisa Ivchenko, and Alyona Suvorova from Ukraine
-
Latest News6 days agoLoopMe research: Increasing GenAI adoption paves the way for an explosion in mobile gaming ad potential
-
Boomerang Partners7 days agoBoomerang Partners has been included in 3 prestigious industry Awards, which will be presented in January 2026
-
Latest News6 days agoThe Top South African No-Deposit for 2025
-
Latest News7 days agoN1 Partners Takes Action at Affiliate World Asia 2025 with a New Award and Key Event Collaborations



