Gambling is one of the oldest professions in the world, and like the other one, it is often pushing new technologies to give it an advantage in what is a seriously cut throat and fast moving industry. Keeping one step ahead of regulators, fraudsters and ethical outrage is a difficult path.

iGaming is a relatively young industry, and as such benefits from starting life on a digital infrastructure and operating in real time when trying to make the most of AI. It is making all the usual internal cost and time efficiencies that come from AI, but will really reap the benefits as the consolidation and personalization of gambling, entertainment and media continues.

The $349 billion global iGaming industry emerged towards the end of the last century, and relies entirely on digital infrastructure, and real time data. It is extremely competitive and has to respond rapidly to constantly changing regional regulations, ethical barriers and public perceptions. If ever an industry was ripe for AI, then iGaming is it.

iGaming software company SOFTSWISS has been reporting on the global industry for the last five years, and its latest report, ‘2027 iGaming Trends’ found clear signs that AI is beginning to have a real impact on the industry, and unsurprisingly has AI adoption rates of nearly 90%.

Alexandra Kavelich, Deputy CMO, SOFTSWISS explains:

iGaming is often viewed as a specialist entertainment sector, but the technology behind it addresses many of the same challenges facing every digital business, like processing transactions in real time, protecting consumers, detecting fraud, personalising products and operating across multiple regulated markets. The difference is the speed and intensity at which these pressures converge.

iGaming ranks among the top three fastest-growing digital industries, outperforming traditional gaming and streaming combined, and it is now worth nearly as much as the global film industry.

The report spoke to more than 500 iGaming professionals, over 65 industry experts, and used market data from WorldGaming, Amazon Web Services (AWS), Pentasia, BGaming and FinteqHub. The use of AI is shifting from basic test pilots into core workforce infrastructure and autonomous systems according to the report. But it also discovered that unmanaged AI tools are inadvertently pushing players toward black-market iGaming alternatives, a constant issue for iGaming companies.

Like Healthcare and Financial Services, the sector is highly regulated, but whereas those industries have been relatively cautious about AI adoption, iGaming has approached AI from the opposite side, using it to deal with compliance issues, as regulatory oversight moves towards automated, data led, market surveillance.

Robin Harrison, Global Content Director B2B, WorldGaming (formerly Clarion) comments:

The reality is that AI improves core processes. Companies are seeing an increase of between 10 and 30% in compliance costs, as it becomes a ‘by the minute’ process rather than reporting back to regulatory authorities. Taking the manual elements out is where AI has a potentially revolutionary effect.

This is also true for fraud prevention and anti-money laundering operations, which are major operating costs for iGaming companies. Fraud prevention efficiency has improved by up to 30%, and investigation costs have reduced by 80%, according to the report. AI-powered systems cross-reference identity documents, trace suspicious transaction patterns, and flag underage or fraudulent users far faster than previously.

Although the report finds that AI adoption is widespread, the gap is widening between iGaming organizations using AI and those who are still experimenting. Where it is working, AWS cited a fivefold reduction in production time and $3 million in annual cost savings from deployed AI use cases.

Shayan Sanyal, Global Games Industry Business Development Leader, AWS, notes: 

More than 85% of global betting and gaming companies are adopting AI, and we are increasingly seeing companies move from experimentation to production. Those companies that have the data structures, the AI governance, and the compliance in place, are the ones moving faster. That gap is increasing between those that are moving to production and those that stay in experimentation, and it is widening quarter by quarter.

In common with other industries, successful iGaming AI implementations have solid data structure, and governance. Responsible AI is becoming part of the technology architecture itself, and survey respondents said there is a need to build trust, observability and consumer protection into AI-driven personalisation from the outset, rather than adding safeguards afterwards. Denis Romanovskiy, Chief AI Officer, SOFTSWISS comments:

Companies can see a return very quickly when they invest into AI infrastructure, AI gateways, and MCP hubs, the things that connect data to AI in a secure, safe manner, with governance. This is where the company can see a return very quickly. Also the companies doing well are also investing in product and software research and development.”

The survey finds that while the industry uses AI extensively for backend logic, like fraud, or risk scoring, respondents were conservative about customer facing gen AI operations because customers seem to have a low tolerance for robotic interactions, preferring human engagement.

Respondents to the survey said that ethical safeguards for AI have to be non-negotiable. The same models used to optimize player lifetime value, predict churn, and to push personalized real time bonuses are also the tools that identify problem gambling and trigger interventions.

Even with sophisticated behavioral models tracking exactly how a player moves through a platform, iGaming operators have learned that AI misses emotional contexts, and external pressures, which can all have a big impact on customer behaviours. Respondents said the best results come when AI highlights anomalies or provides real-time insights, but human judgment handles the final, empathetic decision. AWS’ Sanyal says:

Not considering player protection and personalization simultaneously is a wasted opportunity. The building blocks are there, they're available today. Our customers that are doing this right are treating AI as a trust and engineering decision. They instrument their models from day one to do both. It's the same models, and the same data set you train to do personalization as well as protect the player.

The research reports that personalization is no longer treated as an optional feature, but as a critical baseline for operational efficiency and player retention. Respondents said that personalization has moved from sending lots of emails, to trying to understand players using AI driven player management tools.

Olga Resiga, Chief Business Development Officer, SOFTSWISS, concludes:

The boundaries between media, entertainment, sports, gaming, and iGaming have blurred. The same person watches, plays, follows a team, places a bet, chats with friends, often at once and on the same screen. Watching, engaging and wagering are all collapsing into a single experience layer. That creates an amazing opportunity to personalize before they are even placing a bet.