Players are no longer relying solely on Google to find betting platforms, instead asking AI tools which operators are trustworthy, fast-paying or worth trying. Rather than browsing links, they are receiving direct recommendations, a shift that is already measurable.
According to Bain & Company, around half of internet users under the age of 45 now use AI tools as often as traditional search engines, and Ofcom reports that ChatGPT usage in the UK increased nearly fivefold during 2025.
The implications are significant. AI systems do not present ten blue links, instead they typically recommend a small number of operators. Being included in that shortlist creates visibility at the exact moment a player is making a decision. Being excluded means disappearing from that process entirely.
Research conducted by iGaming marketing specialists Receptional illustrates how uneven that visibility currently is. Their analysis of 50 iGaming operators across ChatGPT, Claude and Perplexity found:
Only 6 operators appeared consistently in AI recommendations
This creates a clear divide between the operators AI recognises and those it does not.
Traditional search engines rank pages based on keywords, links and technical optimisation, which means that even lower quality sites can still receive traffic.
AI works differently. It selects operators based on perceived credibility and presents them as answers. So, instead of asking which site ranks highest, AI will evaluate which operator appears most trustworthy.
This means visibility depends less on keyword targeting and more on whether AI systems can verify credibility using public information.
Receptional’s research found that AI systems consistently favour operators with stronger markers of trust, regardless of size or market share. For example, SBK achieved an AI visibility score of 92 percent, whereas William Hill scored 68 percent.
Despite William Hill’s scale and heritage, SBK appeared more consistently in recommendations because vague claims can’t be recognised by AI without supporting evidence. This shifts the importance from what operators say about themselves to what can be independently verified.
Receptional’s research shows that AI tools form opinions about operators based on the information they can find across the public web. Some factors appear to carry more weight than others:
Regulatory transparency
Player reputation
Operational performance
Independent validation
AI pulls these signals together to form a picture of which operators it can trust enough to recommend.
Improving AI visibility is not purely a technical task. It requires alignment across brand, compliance, operations and communications.
Operators that perform strongly tend to demonstrate credibility through transparent regulatory disclosure, strong player satisfaction, clear performance metrics, and independent validation through media and reviews.
Performance marketing still remains important for acquisition. However, credibility increasingly determines whether operators are recommended in the first place.
AI-driven discovery is no longer a future trend, it’s already influencing how players evaluate operators. Receptional’s research shows that only a small number of operators currently appear consistently in AI recommendations, while most remain largely absent.
Operators that establish strong credibility signals early are now more likely to secure consistent visibility; those that do not risk becoming harder to find, regardless of their size or history.
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