Why is AI crucial for the growth of iGaming? 

The massive amount of data, the high volume of games produced, the dynamic nature of the industry, and increasing player expectations have led over 75% of iGaming companies to acknowledge the necessity of implementing AI in their operations. This is essential to keep pace with the rapid evolution of the iGaming market. 

Much has already been written about AI in iGaming – how it can personalize offers and player communication, test large volumes of games, ensure license compliance, and enhance customer support. However, significantly less is said about how to implement AI in a structured and proven way. The reason is simple: AI is still discussed more than it is actually deployed. 

AI implementation in iGaming is a complex, multi-stage process that requires a strategic approach. Below is a tested framework designed to ensure an effective and efficient rollout. 

AI Implementation in iGaming: Step-by-Step Framework 

Drawing on our 15+ years of industry experience and proprietary AI solutions, we have divided the process into five key milestones, essential for leveraging AI to streamline processes and boost business performance. 

Step 0: Define ownership 

One of the most overlooked aspects is clarifying whether the organization has the internal capabilities to manage the entire AI implementation independently or whether external expertise will be required – both on the organizational and technical side. 

Step 1: Needs assessment and goal setting 

Every AI initiative should begin with a precise definition of business problems and objectives. At this stage, fostering open dialogue between technical and operational teams is critical. AI in iGaming can address numerous challenges, but prioritization requires deep understanding. Listening to team feedback helps identify repetitive tasks that consume resources and hinder strategic work. Early involvement creates internal advocates who will support adoption during implementation. Once priorities are clear, the next step is analyzing the financial viability of automation. 

Step 2: ROI analysis 

This is often skipped but is fundamental to success. Every automation project should deliver a measurable return on investment (ROI). Implementing AI purely for image or trend-following purposes is counterproductive – it risks unsettling teams and generating disappointment with the technology. 

At this stage, it is also advisable to conduct market research to determine whether existing solutions meet the identified needs or whether a custom-built system is necessary. 

Key ROI considerations: 

• Direct costs: software licenses, infrastructure, implementation. 

• Indirect costs: training, maintenance, team involvement in the change process, subscription fees for SaaS solutions. 

• Benefits: increased revenue (e.g., higher player retention), reduced costs (e.g., lower customer support headcount), improved player experience, and the release of team capacity for strategic tasks. 

Combining Steps 1 and 2 enables the creation of a priority list aligned with team needs, business goals, and profitability. 

Step 3: Choosing the right AI solution 

At this stage, you need to decide whether to use an existing tool or create a custom AI solution. There are two main paths: ready-made SaaS tools, which allow faster implementation, lower initial costs, and do not require building a team; or custom solutions, which give more control and better fit your needs but have higher costs and take longer to implement. 

When choosing a solution, you should consider data availability, legal and security requirements, integration with existing systems such as CRM, gaming platforms, or payment systems, and scalability  –  whether the solution can handle a growing number of players. 

Step 4: Collecting and preparing data 

Data is the fuel for AI, and without good-quality data, implementing AI in iGaming is impossible. Key information includes game history and results, real-time player behavior, transactions and deposits, support interactions, and content data like meta descriptions or game reviews. 

The biggest challenges are cleaning the data (removing duplicates and missing information), anonymization, ensuring GDPR compliance, and creating a central data repository that allows efficient use. 

Step 5: Building, training, and integrating the AI Model 

If the organization chooses a custom solution, this stage is crucial. The process includes several important steps. First, build and train the model, which involves choosing the right algorithms, such as machine learning or deep learning, and training on historical data. 

Next is testing and validation  –  checking if the model meets goals, like recommendation accuracy or response time. Then, integrate it with production systems, including CRM, payment systems, or the player’s front-end. At the same time, ensure security by encrypting data and performing security audits. 

The last, but equally important step, is monitoring and optimization, because AI requires continuous supervision and improvement. 

Summary of AI Model Training and Integration Process 

1. Build and train the model 

2. Test and validate 

3. Integrate with production systems 

4. Ensure security 

5. Monitor and optimize 

Ensuring successful AI deployment 

Success depends on a phased approach – starting with a pilot in a single area (e.g., an AI chatbot) and gradually expanding to other processes. Cross-functional collaboration is essential: IT, product, compliance, and marketing teams must work in sync to ensure consistency and efficiency. Continuous measurement and optimization are equally critical – regularly reviewing KPIs, testing new solutions, and implementing improvements will help maximize AI’s potential. 

If internal resources are insufficient to manage the process, partnering with an experienced provider is recommended. Companies like createIT, with hands-on experience in both leveraging and developing AI-driven products, can significantly accelerate implementation and reduce risk. 

Implementing AI in iGaming requires strategy, high-quality data, and skilled teams. While the process is complex, the benefits – ranging from process automation to hyper-personalization – are transformative. The key lies in thoughtful planning, ROI-driven decision-making, and ongoing optimization. 

If your organization is considering AI adoption, start by analyzing business needs and selecting the right approach – off-the-shelf solutions or custom development. Then, prepare your data, deploy the solution, and continuously optimize. 

AI is the future of iGaming. The time to build that future is now.