In his latest contribution to Gaming Americas’ Movers and Shakers, Eberhard Dürrschmid explains why the real AI question is not simply whether to build or buy, but what operators need to own, control and measure.
As artificial intelligence and machine learning become more deeply embedded across iGaming operations, the question of whether to build capabilities internally or work with a specialist provider is becoming increasingly important.
In his latest contribution to Gaming Americas’ Movers and Shakers, Golden Whale CEO Eberhard Dürrschmid argues that the traditional build-versus-buy debate is too narrow.
Rather than focusing solely on who develops the technology, operators should consider a more fundamental question: which parts of their AI strategy must they own and control to protect their business and deliver measurable commercial outcomes?
Own the Outcomes, Not Every Tool
Operators do not necessarily need to own every machine learning model, optimisation layer or piece of supporting infrastructure.
What they do need to control is their data, commercial strategy, player relationships, responsible gaming boundaries and definition of success.
As Eberhard explains, the technology applied to player data may change over time, but the data itself remains a core operator asset. AI and machine learning should therefore be evaluated according to how effectively they improve commercial decisions, rather than simply whether the underlying technology was developed internally.
Clear KPIs and meaningful benchmarking are central to that process. A model performing well in isolation is not enough. Operators need to understand whether it performs better than the available alternatives and whether the resulting uplift justifies the investment.
Combining Internal Control with Specialist AI Expertise
The article also challenges the idea that partnering with an external AI specialist means surrendering strategic control.
A successful optimisation strategy should reflect the operator’s own commercial objectives, risk appetite and operational boundaries. Specialist technology can then provide the modelling capabilities, infrastructure and experience required to navigate complex player-level decisions at scale.
For many operators, this creates a compelling middle ground between building and buying. Internal teams retain ownership of strategy and outcomes, while specialist AI capabilities provide the speed, expertise and optimisation intelligence required to accelerate implementation and performance.
Drawing on Golden Whale’s experience across more than 300 integrations and operators on four continents, Eberhard also highlights the importance of external benchmarking and field experience when assessing the true performance of AI and machine learning models.
Protecting Operator-Specific Intelligence
Ownership becomes particularly important as AI models learn from operator-specific player behaviour.
Golden Whale structures its partnerships around a clear principle: operators retain ownership of their data and the model weights created directly from it. The underlying modelling technology can remain the supplier’s intellectual property, while the intelligence generated from an operator’s player relationships remains protected.
This approach supports greater flexibility and helps operators avoid unnecessary dependency on a single technology provider.
Governance Must Be Built In
As machine learning increasingly influences player journeys, incentives and retention strategies, governance cannot be treated as an afterthought.
Responsible gaming requirements and other operational boundaries need to be embedded as clear guardrails around optimisation. Human oversight, transparency and clearly defined decision boundaries remain essential as AI takes on a greater role in commercial decision-making.
Ultimately, the strongest AI strategies are unlikely to be defined by build or buy alone.
They will be defined by an operator’s ability to understand what it needs to own, where it must retain control, and where specialist AI expertise can deliver faster and more measurable value.
Read Eberhard Dürrschmid’s full contribution to Gaming Americas’ Movers and Shakers to explore why AI ownership is ultimately a question of control, accountability and commercial performance.
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