How AI Is Rewriting iGaming Regulation

Globally, regulators are taking a closer look at gambling operators and the technology and payment networks behind them, particularly AI and crypto. 

Great Britain’s Gambling Commission raised gambling software from low to medium money-laundering risk on 30 July 2026, and on 9 September the Financial Action Task Force (FATF) published its first detailed examination of online and illegal gambling risks. For platform and content suppliers, this means regulators can now inspect their customers, payment flows, and models.

AI is also becoming a tool for regulators themselves. These tools can automate data analysis, flag anomalies, and help authorities identify suspicious patterns across large volumes of information.

Why It Matters for Suppliers?

The UK Gambling Commission’s 2026 risk assessment raised gambling software to a medium-risk category, citing concerns that licensed operators could supply software to illegal gambling sites through business-to-business (B2B) relationships. It also classified inadequate checks on B2B customers as high risk. In 2026, it also included two new concerns: insufficient monitoring of third-party contracts to prevent software from being resold to unlicensed sites, and B2B partners based in or connected to high-risk jurisdictions.

The FATF’s 9 September announcement points in the same direction. It warns that gambling platforms depend on related services, including software developers, which may be outside the scope of existing regulatory frameworks. It also highlights that ownership structures can be designed to avoid regulatory checks.

What Regulators Are Likely to Ask of Suppliers

AI and blockchain have become the focal point of regulatory attention and, hence, future demands to be prepared for by betting companies and suppliers.

Area	What suppliers may need to do	Current status	Source
Supplier licensing and due diligence	Verify operator clients, assess their legitimacy and monitor sublicensing arrangements.	UKGC identifies inadequate B2B due diligence as a high-risk area. Broader licensing expectations are a forecast.	UKGC 2026 risk assessment
Domain monitoring and geo-blocking	Track approved domains and mirror sites; detect attempts to bypass location restrictions using VPNs, proxies or other tools.	Stronger technical controls are a forecast, not a universal requirement. UKGC has identified risks involving software supplied to illegal operators.	UKGC 2026 risk assessment
Traceability and audit access	Keep game-launch and incident logs, support regulatory audits and enable rapid suspension of software in a specific market or for a specific operator.	Potential future expectations; no single binding rule covering this entire package has been identified.	No specific source confirming the full set of proposed requirements.
Detection of gambling-related harm	Help operators identify risky play, record interventions and support human review of automated risk alerts.	UK-licensed remote operators already have customer-interaction duties. Supplier obligations depend on their role and contracts.	UKGC Licence Condition 3.4.3
Crypto customer checks	Support wallet-owner identification, transaction screening, blockchain analysis and records of crypto-to-fiat conversions.	Forecast for gambling suppliers; specific obligations depend on the business and applicable AML rules.	FATF 2026 gambling-risk update
Crypto transfer information	Ensure covered transfers handled by EU crypto-asset service providers include the required originator and beneficiary information.	Existing EU requirement, subject to the regulation’s scope and exemptions.	EU Regulation 2023/1113
Anonymous crypto accounts	Covered financial institutions and crypto-asset service providers must prepare for restrictions on anonymous accounts and accounts enabling anonymisation through privacy-enhancing coins.	EU rules apply from 10 July 2027. This is not a blanket ban on all anonymous crypto use.	EU Regulation 2024/1624
AI governance	Document AI systems and their purpose, assess risks, check data quality, log decisions and maintain appropriate human oversight.	Requirements depend on the system’s classification and the supplier’s role under the EU AI Act. Not every gambling AI tool is high-risk.	EU AI Act
AI-driven personalisation	Explain how recommendation and personalisation models work, test their effects on wagering behaviour and establish accountability for harmful outcomes.	Regulatory scrutiny is developing; no general industry-wide ban is established by the cited examples.	Massachusetts Gaming Commission letter to operators, October 2026

Your Model Is Now on the Audit List

AI creates two sets of obligations for gambling suppliers: regulators are using data analytics to monitor the market, while operators face growing scrutiny over the AI tools they buy or build.

For example, the UKGC’s approach to AI emphasises governance, assurance and human oversight. 

The second pressure comes from suppliers’ own AI systems. Under the EU AI Act, prohibitions on certain harmful AI practices have applied since February 2025. Transparency duties apply to certain AI interactions, but not every AI product is covered by the same rules. 

Gambling is not automatically a high-risk category; individual systems must be assessed against the Act’s classification criteria. The European Commission’s official summary of the rules and implementation dates explains the distinctions.

In the US, regulators are also asking more direct questions about betting-related AI. On 14 October 2026, the Massachusetts Gaming Commission asked licensed sports wagering operators to disclose how they use AI and machine learning, with responses due by 3 November. Separately, New York Gaming Commission meeting minutes record a proposal to restrict AI-generated personalised promotions and suggested wagers or wager amounts. That is a proposed measure and has not been enacted yet.

For suppliers, the commercial implication is straightforward: operators may ask vendors to explain what their AI models do, what data they use, how they are tested, who is accountable for their outputs and what safeguards prevent harmful wagering behaviour. Suppliers should be prepared to provide evidence, not just describe a product as “AI-powered” or “compliant”.

Meanwhile, there are still many blind spots in the oversight of these technologies. For instance, general-purpose AI assistants can be prompted to recommend unlicensed offshore casinos, with no formal duty to check licences. 

How Regulators Around the World are Using AI

Regulators are not only writing rules for AI; they actively implement AI tools to make supervision more accurate and efficient. Here are some examples: 

– France (ANJ): The regulator adopted a scoring algorithm in May 2026 to identify excessive gambling. The algorithm is available to operators, but its use is optional. However, operators face a huge fine if they fail to identify and support high-risk players. 

– Spain (DGOJ): Spain’s gambling regulator has proposed a common supervised-learning model to detect early signs of problematic gambling. As of October 2026, the model has not yet been confirmed as fully adopted or operational. 

– Great Britain (ASA/CAP and the UKGC): The Advertising Standards Authority and the Committee of Advertising Practice use an AI-based Active Ad Monitoring System to identify gambling advertisements likely to have strong appeal to under-18s. 

The UKGC also uses an automated website-identification tool to find potentially illegal gambling sites and prioritise those with the highest estimated online activity for human review and possible enforcement.

– Malta (MGA): The Malta Gaming Authority uses an AI tool to support criminal-probity screening and the analysis of industry performance returns submitted by licensees. The tool flags information for further examination, while staff review the results, making the final decisions. The use of AI was reported in the MGA’s 2025 annual report. 

When regulators develop their own models, they gain a benchmark against which to assess operators’ systems. If an operator’s tools identify fewer at-risk players than the regulator’s model, its detection methods are easier to question. If regulators make a standard model mandatory, platform vendors will also need to integrate it into their systems.

To Sum Up

AI is becoming an increasingly effective tool for gambling regulators, enabling them to identify potentially problematic gamblers, locate illegal websites, audit operators’ advertising and compliance systems, and much more besides.

AI becomes a more important part of gambling regulation not only as a means of market supervision but also as a technology that requires some oversight. This creates additional responsibility for suppliers to be open and accountable. The competitive advantage will not only be determined by the capabilities of AI but also by human oversight and the ability to explain, test and validate its decisions.