The Future of iGaming: Lean Teams, Data, and AI
In the fast-evolving landscape of digital entertainment and e-commerce, the line between technology and commercial strategy has completely blurred. To get a frontline perspective on where the market is heading, we recently sat down with Murat Boşnak, a veteran Senior Product Leader and engineer with a 17-year career combining a core software engineering foundation with over a decade of product leadership. At ComeOn, Murat scaled from a hands-on Product Owner to Head of Product and Director of Program Management, directing the end-to-end development of proprietary sportsbooks and casinos while driving complex multi-brand platform migrations across strict regulated global markets. Below, we explore the macro trends transforming the industry based on his real-world experience: the strategic shift between buying software and building in-house, the evolution of personalization in heavily regulated markets, and how generative AI is radically changing the structure of modern tech teams.
The Battle for Data Ownership: Buy vs. Build
As international markets open up across the globe, a booming ecosystem of niche B2B providers has emerged, offering specialized solutions for everything from KYC compliance to open banking (PSD2). In Murat’s view, the strategic choice between buying a turnkey solution and building in-house depends almost entirely on company maturity, scale, and a desire to own the data pipeline from start to finish.
Drawing from his observations across teams of various sizes, Murat highlights a distinct industry spectrum:
- The Small Operator Reality: For a small operator—such as a lean, 10-person setup managing compliance, co-founders, and gaming operations—buying the entire platform from a third party is often a operational necessity to get to market quickly.
- The Enterprise Shift: At the other end of the spectrum, Murat points out that larger players naturally lean toward building in-house components. At a midsized operator, for example, the team initially integrated third-party providers but systematically took over modules one by one, culminating in building their own sportsbook.
- The ROI of Data Control: The core philosophy behind building in-house, according to Murat, is absolute data ownership. When an organization owns its data end-to-end, it can make highly educated, rapid choices regarding the user experience (UX) and calculate a clearer return on investment (ROI).
Personalization: Moving Beyond the "Bonus Culture"
For years, player retention in online entertainment relied heavily on financial incentives like bonuses. However, Murat points out that this approach is hitting a hard ceiling. As strict regulatory frameworks tighten in geographies like Sweden, Finland and Denmark, operators are increasingly restricted, often limited to offering a single sign-up incentive.
Because most competitors offer an identical selection of third-party games, Murat believes that personalization is now the single best and most effective mechanism for operators to differentiate themselves.
Looking at mainstream entertainment giants like Spotify and Netflix, the goal is clear: maximize user attention and keep them consuming the product on your platform. Murat highlights that if you cannot rely on a continuous stream of bonuses, your core product must step up to drive retention by:
- Customizing the exact games, content, and layout a user sees on the website.
- Tailoring how the platform communicates with the individual user in real-time.
When asked where the low-hanging fruit lies in personalization, Murat emphasizes that there is no shortcut; it varies entirely by company size. The absolute prerequisite is data maturity: you must start with clean data ownership, and build your personalization layer on top of that foundation.
The Democratization of Tech: AI and the Rise of the Micro-Team
Perhaps the most disruptive shift currently occurring is the changing profile of the tech professional. The industry is seeing a clear convergence where engineers are expected to hold a deep product perspective. Murat strongly agrees with this trend, noting that modern AI development tools mean "everyone can do everything" technically—but it comes with a major caveat regarding true expertise.
As someone who actively uses AI development environments and autonomous coding agents to build complex backend logic, Murat shares a grounded perspective on what AI can and cannot do:
- AI Needs Competent "Pilots": Generative AI allows users to build interfaces and write production code in record time, but the output isn’t guaranteed to be scalable or robust. Murat emphasizes that if you don't possess foundational career skills, you won't know how to give proper instructions or evaluate the quality of the AI's work.
- Product Domain Expertise is Vital: The same limitation applies to product management. If a professional doesn't know how to thoroughly define, structure, or evaluate a digital product, AI cannot magically fix it. However, when paired with domain expertise, AI is incredibly powerful—compressing complex user research from weeks into just a few hours.
Final Thoughts
The future of digital product delivery belongs to the agile. Whether it is a large enterprise consolidating architectures to drive operational efficiency, or a lean startup utilizing autonomous agents to challenge legacy software, the playbook has changed. As Murat's experience highlights, winning in highly regulated, hyper-competitive landscapes requires an absolute focus on data control, hyper-personalized user experiences, and the strategic adoption of AI to keep teams lean, fast, and relentlessly focused on shipping product.
Do you want to get concrete examples on how AI agents can be built into your development workflows, or get more insights into personalisation topics? Get in contact and let’s start a conversation!
