GR8 Tech focuses on creating AI-driven solutions that
are engaging, personalised for each player, and easy to manage for operators. Our goal is to provide a user-
focused experience where players receive content and offers tailored to their preferences, while operators benefit from automated tools that reduce complexity.
GR8 Tech Creating AI-driven Solutions The gaming industry is acutely aware of the value proposition of AI-driven
personalisation, but implementation of personalisation at scale isn't an easy undertaking and there are many existing priorities that can take precedence. GR8 Tech CEO Evgen Belousov details the nuances involved.
EVGEN BELOUSOV Chief Executive Officer GR8 Tech
What can operators do to identify where AI and personalisation are most needed to ultimately add value for themselves and consumers?
Operators should partner with a provider that prioritises understanding their specific needs rather than just pushing products. A good provider will help assess key areas where AI can add the most value, such as personalised recommendations, customer segmentation, and retention strategies. By working with GR8 Tech, operators can easily integrate AI solutions that align with their goals, simplifying the process and maximising impact.
Te AI-driven solutions most popular among clients are the ones that boost player engagement and drive business results. Our range of tools— from personalised recommendations to CRM optimisation—helps operators focus on areas that make the biggest impact. For example, our sports recommendation models tailor betting suggestions based on player preferences, which keeps players engaged and boosts cross- selling.
On the CRM side, we use player data to customise promotions, improve retention, and predict churn, giving operators the insights they need to enhance the player experience and increase revenue. And that’s just scratching the surface.
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What are the technical hurdles facing operators looking to embrace AI- driven personalisation?
Tere are quite a few technical challenges when it comes to adopting AI- driven personalisation, but several key hurdles stand out. One of them is ensuring data integration and quality. AI systems depend on extensive player data, including behavioural patterns and interaction history, but poor-quality or inconsistent data can hinder accurate recommendations.
Also, coordinating multiple AI models that handle different personalisation aspects, like retention prediction and trending events, adds complexity. Synchronising these models requires continuous fine- tuning and monitoring.
AI must process data quickly to deliver timely recommendations, requiring robust computing infrastructure and optimised algorithms for handling rapidly changing data. Scaling AI solutions across regions is also tricky, as it takes adapting to diverse cultural preferences, training models on region-specific data, and ensuring consistent performance across geos. Another challenge is balancing personalisation with security, particularly in fraud detection. AI systems must identify fraudulent behaviour without falsely flagging legitimate user actions, as this could erode player trust.
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