Artificial intelligence (AI) is redefining the iGaming industry. It is no longer just a back-end tool for data analysis; it has become a cornerstone of innovation, powering hyper-personalised user experiences, automating complex operations, and even creating new gaming content. Early adopters among online betting and gaming operators are already reporting tangible benefits: more engaging products, improved customer retention, streamlined workflows, and stronger risk controls. For example, operators using AI-driven personalisation have seen player engagement surge by 10–15%, and casinos deploying AI-driven promotions have boosted retention rates by up to 20%. At the same time, this “AI arms race” brings new challenges. AI can just as easily amplify problems – from producing misleading marketing content to autonomously nudging at-risk players – raising ethical, regulatory, and reputational risks. Regulators in major markets (UK, EU, US states, Malta) are responding with heightened scrutiny and nascent governance frameworks to ensure AI is used transparently and responsibly, especially where it impacts consumers. Crucially, the competitive gap is widening between those investing in advanced AI capabilities and those who are not. In an industry built on data, AI adoption will not be optional – it will define competitiveness in the coming years. The following report provides a comprehensive analysis of how generative and agentic AI are transforming iGaming product development, marketing, customer experience, compliance, and operations. It highlights real-world use cases from 2023–2026, examines emerging risks (and mitigation strategies), surveys regulatory responses, and maps out strategic scenarios and predictions through 2028. Key findings and strategic implications are summarised below.

Key Findings and Strategic Implications:

• Generative AI is enabling new levels of product innovation: AI can now generate gaming content and features in ways impossible just a year or two ago. For instance, generative models can produce graphics, narratives, and even entire slot games in minutes, ushering in an era of rapid game development and personalised content. This accelerates product cycles and allows operators to tailor experiences to micro-segments of players at scale.
• Agentic AI is automating complex operations: Beyond analytics, AI “agents” are taking on decision-making roles in trading, customer service, and fraud management. Sophisticated AI-driven trading engines now adjust odds and manage risk in real time across thousands of markets, far faster than human traders. Meanwhile, AI chatbots handle 24/7 customer queries in multiple languages, with 65%+ of major operators having embedded chatbots by 2022. These autonomous or semi-autonomous systems drive efficiency and scalability, but also demand new oversight to prevent mistakes or abuse.
• Hyper-personalisation is becoming a competitive differentiator: The integration of large-language models (LLMs) and machine learning into iGaming platforms allows for Netflix-style personalisation of offers, games, and communications. Accenture research finds 80% of players seek personalised experiences, and AI-led personalisation can raise engagement by 10–15%. Companies leveraging AI to deliver tailored game lobbies, dynamic odds, and individualised promotions are seeing higher customer satisfaction and loyalty. In a data-rich sector, personalisation at scale has shifted from a marketing buzzword to an expected standard.
• Regulatory and ethical hurdles are rising fast: The deployment of AI is outpacing the existing rules in many jurisdictions. Key gambling regulators are now racing to set guardrails on AI use in areas like player protection, fairness, and data usage. The UK Gambling Commission’s 2024 strategy, for example, adopts a “low-risk” appetite for AI, demanding transparency, human oversight and compliance with licensing objectives for any AI-driven tools. In the EU, the forthcoming AI Act will classify many gambling AIs (e.g. risk scoring systems, ID verification, behavioural profiling) as high-risk, imposing strict requirements on auditability, bias testing, and human control. Operators that proactively build AI governance (e.g. bias audits, AI use registers, human-in-the-loop processes) will mitigate compliance and legal risks, whereas those that do not face potential regulatory sanctions, legal liability, and reputational damage.
• New risks around content and conduct have emerged: Generative AI can just as easily produce problematic outputs as beneficial ones. For marketing and acquisition, this means a risk of AI-generated content that breaches advertising standards or responsible gambling codes (e.g. exaggerated claims or inappropriate targeting). Deepfakes and synthetic media present a frightening scenario – regulators warn that AI could be misused to bypass KYC/AML checks or create fake identities. AI chatbots, if unchecked, might give misguided advice or implicit encouragement to gamblers, potentially crossing “inducement” lines. Additionally, opaque AI algorithms might inadvertently prey on vulnerable players, which the EU AI Act outright prohibits as an exploitative practice.
• Competitive dynamics are accelerating AI investment and M&A: Leading iGaming operators and suppliers are pouring resources into AI to gain an edge. Many are choosing a dual strategy of in-house development and acquisitions/partnerships. These moves underscore a talent and IP arms race: operators with advanced AI capabilities can optimise customer value and risk management in ways slower competitors cannot. Weaker or smaller players may find themselves reliant on third-party AI solutions or at risk of consolidation. We anticipate more tech partnerships and M&A as firms vie for AI expertise and scalable platforms.
• Strategic Outlook – AI as both disruptor and differentiator: By 2026, AI will be deeply embedded in the iGaming value chain – from game design and odds compilation to customer targeting and compliance monitoring. In the near term, this confers first-mover advantages to those who deploy AI thoughtfully: better product offerings, lower costs, superior player safety, and enhanced ability to navigate regulatory expectations.

However, in the long term, the ubiquity of AI could level certain playing fields (e.g. commoditising basic personalisation or risk detection) while raising the bar on compliance and data governance. Operators must therefore treat AI not as a magic bullet but as part of a broader digital transformation: success will depend on integrating AI with human expertise, rigorous governance, and a customer-centric strategy. Crucially, winning the “AI arms race” in iGaming does not mean using AI to exploit customers or cut corners – it means leveraging AI to deliver sustainable, transparent and player-safe innovation faster than the competition.

We begin this report by defining the rise of generative and agentic AI in context, then examine impacts on product innovation, player acquisition/retention, and operational automation. We explore the regulatory and ethical dimensions in detail, compare how major industry players are adapting, and present forward-looking scenarios for how AI could shape the industry’s trajectory through 2028. A final section provides clear definitions of key AI terms and concepts, and an index of all cited sources is included for reference.