Dr. Andreas Koeberl – Why AI has changed iGaming forever

Dr. Andreas Koeberl is the CEO of BetGames, a leading supplier of iGaming content, and co-founder of Autonomous Minds, a startup building Enterprise AI solutions. With a background in software engineering and marketing, Andy specialises in competing within competitive, high-tech industries.

Dr. Andreas Koeberl, CEO of BetGames, explores the exponential growth of AI in iGaming, how studios are harnessing its power for efficient product development, and what the future looks like for machine learning technology in the sector.

We are living in a new age of technology. Artificial intelligence (AI) has infiltrated every commercial and creative sector, and those that fail to adapt risk being left behind. In no industry does that ring truer than iGaming, where relentless iteration and differentiation are pivotal in remaining ahead of the curve in this hyper-competitive sector.

AI’s Meteoric Rise

The sophistication of AI has skyrocketed in the last decade, with every new technology upgrade offering greater potential than the previous. As the technology readiness improves, it becomes more adept and applicable to broader business needs. This has resulted in the topic gaining widespread attention and breaching the mainstream – it is no longer an underground trend discussed on forums by engineers or applied by data engineering teams. Instead, we are seeing a growing number of companies and C-suite executives committing huge resources to successfully integrating AI processes. It is now generally accepted that companies must learn to incorporate AI if they are to remain at the forefront of industry progression.

The rise of AI in iGaming is fuelled by intense market pressure. It is an incredibly saturated industry, with new start-ups created almost daily, and failure to adopt evolving technologies will see you surrender market share. It has never been more important to innovate, prototype, fail, learn, and iterate at real speed, allowing more time to double down and invest in successful ideas. This is one of the main drivers of AI integration. It is vital to free up engineers’ valuable time – assisted by AI, they can now produce code in hours that would have previously taken days. The capacity of Generative AI tools to produce code, artwork, and game characters makes it an invaluable tool that maximises operational efficiency. There has been much talk about technology taking over from humans – in reality, people should be less concerned about being replaced by AI and more about being replaced by someone who effectively leverages AI to speed up and elevate the quality of their work.

Streamlining Product Development

Creating a new game is comparable to producing a new TV show; you never know if it will strike the right chord with your target audience. While an idea might feel like a winner internally, you essentially remain blind until you test and validate it. AI has unlocked a new realm of possibilities when it comes to prototyping. Now, you can turn a written concept on a page into a fully functioning game prototype within a day, carving out more time for testing. Providing someone with a working demo to gauge their sentiment is far more effective than explaining the concept via a PowerPoint slide. Within 60 seconds of trialling a prototype, you can ascertain if the idea has merit or if you need to kill it and move on to the next.

Aside from prototyping, AI can also be utilised in a variety of ways to analyse player behaviour to steer future product development. Machine learning algorithms can measure key performance metrics, predict CLVs, segment players, and assign bonuses in real-time, as well as compile data about patterns in strategy, all of which provide unparalleled insight into how a player engages with content. Performance data is one side of the coin. The other side is measuring usability, which is a direct consequence of UX and QA developments. Some tools use heat map data to provide insight into where exactly a player is tapping on the game, how long it takes them to execute the desired action, and which design of the same game appeals to which player segment. This highlights whether the design is strong enough from a user experience perspective, and what to improve based on the data fed into the AI models. Together, these AI-driven insights create a powerful feedback loop that informs smarter design decisions, ultimately enhancing player satisfaction and overall game performance.

The Future of AI

An interesting paradox is that we are seeing engineering roles being more affected by AI than roles like secretaries or personal assistants. Traditionally, a software engineer would have been considered a niche, highly skilled role, but the reality is that AI is better equipped to take on these tasks. In contrast, professionals specialising in people-facing roles requiring relationship management and the juggling of multiple chaotic tasks continue to be highly sought after. Good luck trying to replace a CEO’s personal assistant with AI!

In the next five years or so, we will likely see businesses consolidating their product teams as a direct result of constantly improving AI technology. Development teams will scale down as machine learning programs are entrusted with coding, and we will reach a point where a small number of engineers will be tasked with orchestrating several AI-driven projects. It isn’t easy to comprehend the full potential of AI. As it stands, we are heading towards a future where roles are adapted to get the best out of AI rather than replacing humans with technology altogether. Whatever the future looks like, those who commit to embracing this technology will position themselves to reap the rewards.