The passing of the European Union’s AI Act signals a significant new phase in the regulation of artificial intelligence, one that gambling industry executives cannot afford to ignore. With regulators in several jurisdictions already examining how AI transparency obligations intersect with gambling-specific rules, firms must move swiftly to anticipate what may soon become mandatory reporting and disclosure requirements. From customer protection tools to marketing practices and operational decision-making, the use of AI is now firmly under the spotlight.
The AI Act introduces a graduated system of risk-based obligations, imposing stricter requirements on uses of AI deemed ‘high-risk’ to fundamental rights. In gambling, this categorisation is not yet formally established, but customer interaction models, automated risk assessments, personalised marketing, and algorithmic decision-making about responsible gambling interventions are all likely candidates for heightened scrutiny. Even before formal designations, the principle is clear: companies must be able to explain not only that AI is used but how it operates and what measures are in place to ensure it is fair, safe, and non-discriminatory.
Transparency, in this context, is not a superficial exercise. It involves offering meaningful, intelligible information to both regulators and, in many cases, end-users. For gambling operators, this raises several complex challenges. Models built through deep learning, for example, often produce results that are difficult even for their creators to interpret. Black box models, while powerful, are therefore increasingly problematic from a compliance perspective. Firms relying on opaque AI systems for customer risk profiling or engagement personalisation must now reconsider whether those systems can be adapted to meet explainability thresholds or whether alternative, more interpretable models are required.
This transparency obligation does not only apply at the point of regulatory inspection. Proactive reporting, auditing, and ongoing monitoring are likely to become standard expectations. In many respects, the gambling sector is already familiar with this rhythm through regulatory reporting on safer gambling initiatives and anti-money laundering (AML) measures. However, AI reporting will introduce a new layer of complexity: it is not merely about outcomes, but about processes, models, data quality, and governance frameworks. Being able to evidence the ethical deployment of AI, not just its efficacy, will become a defining characteristic of compliant operations.
Marketing practices will also come under pressure. Personalised advertising, predictive promotions, and dynamic customer segmentation increasingly rely on AI tools. Under the AI Act’s transparency requirements, companies will need to ensure that individuals are informed whenever they are subject to marketing content influenced by AI-driven profiling. In some cases, this may extend to allowing users to opt out of such profiling altogether. The sector must prepare for a shift where ‘personalisation’ is no longer an unqualified benefit but a process that demands transparency, consent, and accountability.
Operationally, the use of AI in areas such as fraud detection, game design optimisation, and dynamic risk management must similarly be assessed for compliance risk. Even if these systems are internally facing, their deployment can influence customer outcomes and regulatory expectations. Governance structures must therefore be adapted to ensure there is board-level oversight of AI use across all domains. Clear internal policies, independent audits, and dedicated AI ethics committees may soon become common features of responsible gambling businesses.
Crucially, the need to act now cannot be overstated. Regulators are already signalling that they expect businesses to show preparedness, not simply compliance after the fact. By investing in AI audits, updating data governance policies, and training staff on emerging transparency obligations, companies can position themselves ahead of the curve. Those that treat AI transparency as a regulatory add-on will find themselves exposed not only to enforcement risk but to reputational harm among increasingly AI-literate customers.
In reflection, the challenge is substantial but not insurmountable. As with all regulatory evolution, early engagement, clear internal ownership, and a willingness to adapt are key. Transparency, properly understood, is not a threat to innovation but a condition for its sustainable use. Gambling executives have a rare opportunity to shape the sector’s relationship with AI before external pressures dictate the terms. It is an opportunity they would be wise to seize.