As artificial intelligence sparks an efficiency revolution across various industries, the gambling sector appears to be faltering in this wave. A recent report jointly released by the International Gaming Institute at the University of Nevada, Las Vegas, and KPMG reveals a rather embarrassing set of data: the global gambling industry's AI maturity index composite score is only 45 out of 100, significantly lower than the overall economic average. This report, titled "AI Application Status in the Gambling Industry 2026," based on an in-depth survey of 83 gambling companies and 113 regulatory bodies, outlines a scenario where the industry and regulators each go their own way, with misaligned perceptions. Kasra Gaharayan, the lead editor of the report and director of IGI research, states at the beginning that the core questions the research team hopes to answer are: how companies are actually deploying AI, where the biggest challenges lie, how to ensure responsible implementation, and which new technologies will drive future innovations. Perhaps the most glaring finding in the survey is not the lag in AI application itself, but the 27-point chasm between strategic ambition and governance readiness, and the collective misjudgment by regulators about the actual use of AI in the industry.
Current State of AI Applications in the Industry: Technology Safety First, Cost Savings Yet to Be Realized
From the application scenarios, the logic behind AI deployment in gambling companies is starkly different from consumer-facing industries like retail and media. The report shows that the current AI applications in the industry are concentrated in two main areas: technology safety and product development innovation, accounting for about 50% combined; while risk compliance applications only account for 14%, ranking last. Researchers interpret this as: gambling operators, being closer to regulated financial institutions, prioritize technology, safety, and product integrity over direct player interaction. This not only reflects the pressure of regulatory scrutiny but also the high-risk nature of AI-driven personalization in a behavior-sensitive environment—rather than using algorithms to precisely push betting suggestions and spark compliance disputes, it's better to first fortify the defenses against cyber threats and fraud.
However, the cost-benefit ledger has yet to present convincing figures. When asked to what extent AI has contributed to cost savings, the average score among surveyed companies was only 2.43 out of 5. Among them, 10.8% stated they had not saved any costs at all, while 48.2% reported only minimal savings. Expectations for the investment return period are also divided: 26% of companies expect to see results within one to two years, 20% hope to break even within six to twelve months, another 20% have seen substantial results, and 19% believe it is still too early. From a staffing perspective, 42% of companies indicate they have no plans to hire for AI-related positions, while 53% believe that AI will lead to restructuring rather than a net increase or decrease in workforce. This set of data sends a clear signal: AI in the gambling industry is still in the early stages of transitioning from "proof of concept" to "large-scale deployment," and the promise of cost reduction and efficiency gains has yet to be realized, but the industry has begun to stockpile ammunition for long-term transformation.
Strategic and Governance Fatal Fault Line: The 27-Point Gap's Underlying Concerns
The most startling discovery in the report is the huge discrepancy between corporate AI strategy and AI governance. In the maturity index's four pillars, the strategy dimension scores 55 points, while the governance dimension scores only 30 points, a difference of 27 points. The report's authors sharply comment that the industry "sets the direction much faster than it builds the guardrails." Companies' self-assessed greatest AI risks are cybersecurity vulnerabilities and data privacy failures, while issues related to core responsibilities of the gambling industry, such as "AI amplifying problem gambling risks" and "producing unfair outcomes for players," are ranked at the very bottom.
The lack of organizational readiness is equally concerning. Only 22.9% of companies have dedicated positions for AI governance, responsible AI, ethics, or compliance. Researchers point out that this exposes a clear disconnect: data privacy and governance are at the top of the industry's list of AI risks, yet the governance framework and dedicated positions needed to address these risks are still underdeveloped in most companies. In other words, while companies have strategically placed AI on their core agenda, they are far behind in terms of who will oversee the algorithms, who will ensure models do not produce discriminatory results, and who will be accountable for AI decisions.
Regulatory Misalignment: Thinking Companies Are Focusing on Customer Acquisition, When They Are Actually Focusing on Safety
The regulators' responses also reveal concerning signals. Of the 113 regulatory bodies involved in the survey, only 68 completed an AI literacy test consisting of 14 questions, with an average score of 8.6 out of 14. More intriguingly, the research team found a "very weak correlation" between the regulatory personnel's AI training experience and their level of AI literacy—having undergone training does not necessarily mean they truly understand AI. Regulators are most confident in "identifying ethical risks in AI deployment" and "judging whether current regulations need to be revised due to AI," but their confidence is lowest in "assessing how licensees use AI in operations" and "understanding how AI systems are applied in gambling scenarios." Researchers characterize this as a "clear contradiction": regulators know that AI governance challenges are urgent, yet admit they are unprepared.
This misalignment is even more starkly reflected in another set of data. Regulators generally believe that the focus of gambling companies' AI applications is "customer-facing functions," with this option receiving more than 20 percentage points more votes than the second most popular option. However, the actual responses from companies are the exact opposite—technology safety and product innovation are the most frequent application scenarios, while customer-facing functions rank low. Regulators overestimate the companies' impulse to use AI for customer acquisition, yet underestimate their investment in compliance and safety. The report's authors comment on this: "There is a clear gap between regulators' perception of industry practices and companies' actual deployments," which raises the question—on what basis do regulatory bodies advocate for specialized AI regulation of the gambling industry and hold a skeptical attitude towards industry self-regulation?
When asked whether their institutions are currently planning AI guidelines or review processes, only 52% of regulators answered "yes," while 47% stated they had no such plans. Regarding the most effective path to improving AI regulation, the most common agreement was on "strengthening collaboration between states and countries"—suggesting that the fragmented regulatory landscape itself has become a stumbling block for AI governance. PASA's official website continues to track global gambling industry technology governance dynamics, noting that the report reveals a cognitive gap between the industry and regulators, essentially a stalemate about "who takes the first step": companies are waiting for a clear regulatory framework to avoid compliance risks, while regulators are waiting for more mature industry practices to inform rule design. In an era where AI capabilities iterate by the month, the cost of this mutual waiting may well be much heavier than a mere 45-point maturity report.
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This article is from "PASA-Global iGaming Leaders," a gambling industry news channel:https://t.me/pasa_news
Original in-depth gambling channel:https://t.me/gamblingdeep
Free data reports: @pasa_research
PASA Matrix: @pasa002_bot
PASA official website: https://www.pasa.news
