How savvy AI implementation can help gaming operators and providers hit the jackpot

Artificial intelligence (AI) is revolutionizing industries across the board, and gaming is no different. According to AlixPartners’ recently released “Practical AI for CEOs” playbook, corporations invested more than $150 billion in AI applications and projects in the past year. From a gaming perspective, operators and providers are committed to investing in AI use cases for the casino gaming and sports betting sectors, exploring uncharted territory as additional practical applications come to fruition. 

Every industry player we have spoken to in the last year is actively spending to augment AI capabilities and accelerate their roadmap, whether through organic investment, asset acquisition, or both. With that said, some say the pace of implementation leaves room for improvement. According to the 2024 AlixPartners Disruption Index, our annual survey and report on disruptive trends and their impact, executives worry that they are falling behind on the adoption curve. 75% of tech execs say AI is important to their industry, but 38% say advancements in technology are happening at a rate at which their company cannot keep up. As a result, only 17% say their companies are among the industry pace setters when it comes to generative AI usage.

Although there are many emerging use cases with differing degrees of maturity, we believe gaming operators should focus their AI efforts across three major functions:

Level one: Automating processes and boosting efficiency 

Across R&D and operations, gaming companies should already be leveraging AI to automate straightforward, repetitive tasks. According to the 2024 AlixPartners Tech Sector Growth and Performance Report, when asked which AI use cases are top priorities, tech executives ranked software development and customer service as two of the three highest, while using AI to automate processes and workflows is the top-rated priority for operational improvement. Current opportunities to reduce costs and increase ROI through AI implementation include:  

• Content development: Games production is one of the most expensive and inefficient processes in the industry, as a handful of games generate most revenue with a long tail failing to provide adequate return on investment. AI advances can aid in the development of graphics and sound, along with coding, refactoring, and quality assurance for both casino gaming and betting —and video games as well. Across software use cases, GenAI can improve developer efficiency by up to 25-30% when coding and testing, according to our proprietary research.  
• Land-based operations: AI can help predict when gaming hardware needs maintenance in field operations, optimize the mix and location of games on the casino floor based on players’ predictive preferences, and even improve surveillance and security operations by recognizing player voices and faces. 
• Odds setting: When it comes to sports betting, AI can increase the prediction accuracy of event outcomes, elevating the efficacy of the odds-setting process while mitigating operator risk to losses. The data captured by computer vision and wearables, such as advanced player tracking metrics like player acceleration and fatigue levels, also have the potential to improve the predictability of match outcomes. 
• Customer support: Integrating AI with chatbots and voice analytics can aid with automated issue identification and demand planning and scheduling.  

Level two: Minimizing risk and fraud while improving compliance 

The gaming industry is highly scrutinized from top to bottom. Licensing and regulatory authorities at national and local levels oversee compliance, investigate potential violations, and constantly monitor for signs of nefarious activity.

AI can greatly enhance regulatory compliance efforts, minimizing operator risk and consumer fraud while boosting the industry’s standards. Through AI implementation, gaming companies can prevent many of these historic problems from arising in the first place through:  

• Compliance automation: AI is a boon to risk management actions. It can automate player account and age verification without human intervention—as GeoComply does through its partnership with IDVerse, utilizing the latter’s technology to ensure the authenticity of player identification documents.
• Anti-fraud initiatives: AI can help detect potential match-fixing abnormalities and other fraudulent activities, such as money laundering or collusion, by identifying leading indicators in player behavior.
• Responsible gaming: AI can read and prevent problematic gaming patterns from individuals that may need to be monitored or prevented from playing for their own safety. 

Level three: Augmenting the player experience 

Utilizing player data allows gaming companies to more effectively tailor products, promotions, and other communication touchpoints to customers. This level of personalization boosts the player experience—those that excel in this area can leap ahead of the competition. Major opportunities where companies can leverage AI to boost efforts include: 

• AI product recommendations: Unlike traditional systems, AI-based recommendations take each user’s preferences and previous interactions into account when generating suggestions. Personalized next-best-game and next-bet recommendations utilize deep-learning-based sequential recommenders to improve performance versus traditional engines. 
• AI-based pricing: AI can deliver greater accuracy compared to alternatives, optimizing pricing to specific customer segments to improve margins according to their elasticity. AlixPartners clients have experienced 4%+ revenue boosts and 13%+ gross margin improvements through AI-based pricing advances. 
• UX hyper-personalization: We have previously discussed the need for gaming operators to personalize the in-game experience within iGaming and online sports betting, borrowing from the social media industry to provide players with their most relevant content at the top of each app. AI advances make it possible to personalize each UI and UX for a tailored experience. 
• Personalized communications: A hybrid approach that combines GenAI with machine learning (ML) allows gaming companies to micro-segment customers based on unique bettor insights and create new levels of hyper-personalized campaigns. Marketing and sales teams can then target each segment with highly specific, action-driven messaging around retention and loyalty, gaming promotions, bonuses, free bets, and more. DraftKings, a leading U.S. betting operator, is deploying GenAI-enabled marketing techniques to tailor messages, maximize response rates, and lower acquisition costs.  

At AlixPartners, we also utilized this approach to create personalized micro-segments for a major equipment provider’s customer base. We then used GenAI to create and test a variety of subject lines and messages for each segment, training our AI model and iterating with the most effective options. As a result, our client drove click-through rates that were 40-50% higher than alternatives and achieved a 40% revenue lift for the final marketing campaign compared to non-AI control campaigns.  

Risks and challenges to consider 

There are risks and challenges associated with the nascent use of AI that need clear governance, particularly in gaming and sports betting. These include: 

• Tech challenges: Operators and providers often rely on legacy systems and engines that are not AI-ready and need refactoring for AI integration. We expect this to continue driving significant spend and investment in tech stack modernization. 
• Ethical challenges: Gaming operators must comply with strict responsible gaming practices to prevent the risk of abuse from AI technology. Risks here include fair-play manipulation and loss of control of these powerful AI tools.  
• Legal, privacy, and compliance challenges: The amount of sensitive player data operators can collect and manage via AI are subject to potential data breaches and loss, which would come with severe financial and reputational consequences. Additionally, the potential misuse of AI solutions can expose operators to licensing compliance, ESG, and privacy risks.  

Looking ahead to the next level 

Creating and testing new game concepts and betting opportunities is the most advanced but least proven level of AI application for the industry. With time, operators and providers that effectively implement AI here will expedite the game ideation and design process, enable faster prototyping and demoing, and accelerate decision-making around which games to greenlight. They can also use AI to validate which games and attributes resonate most with players by building synthetic player personas to test and garner feedback. 

Already, we are seeing sports betting companies leverage GenAI and real-time data to create new content in the form of more engaging betting markets and increased “in-play” betting options. For example, when live sports came to a halt during the pandemic, sports technology company Sportradar used GenAI to design simulated-reality betting products. These drew on previous statistical outputs to simulate matches reflecting historical team form and normal match play. 

As we discuss in our playbook, it’s crucial to start with a clear AI strategy, and then work out which AI use cases are most relevant for your business from a value-creation perspective. The savviest amongst providers and operators will see a pay-off as large as any Vegas jackpot.