AI Document Automation: Why Curiosity Still Outpaces Adoption in iGaming
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Artificial intelligence continues to dominate conversations across the gaming industry, with document automation frequently positioned as one of its most promising use cases. From faster KYC checks to streamlined affordability reviews and reduced manual workloads, the potential benefits are clear.
Yet discussions at the Payments, Fraud and Compliance Gaming Leaders' Summit revealed a very different reality.
While interest in AI-powered document verification is widespread, genuine implementation remains rare. Operators are intrigued by the technology, but many are still evaluating, observing and waiting rather than actively deploying solutions.
Perhaps the most significant takeaway from the roundtable was the gap between enthusiasm and adoption.
Despite choosing AI document automation as the discussion topic, very few participants had integrated AI into their verification workflows in any meaningful way. Instead, most organisations described themselves as being in an evaluation phase, monitoring the market, assessing vendors and waiting for greater regulatory certainty before committing to implementation.
Even larger operators with dedicated AI or data science teams admitted that much of their work currently focuses on research, proof-of-concept planning and vendor assessments rather than live production deployments.
Given the strategic importance many organisations place on AI, the lack of experimentation—even within controlled or low-risk environments—was one of the session's most surprising findings.
Starting Small Instead of WaitingOne of the key messages emerging from the discussion was that operators do not need to wait for a large-scale transformation before exploring AI.
During the session, we shared examples of how Solas Compliance is already using AI and machine learning to improve document review and compliance workflows, alongside practical examples of accessible tools that can automate repetitive verification tasks.
The opportunity is not necessarily to replace human reviewers overnight.
Instead, AI can begin by extracting information from documents, identifying inconsistencies and reducing manual administration, allowing compliance teams to focus their expertise where it delivers the greatest value.
For many operators, the greatest risk may no longer be adopting AI too early, but waiting too long while competitors build knowledge and experience through incremental experimentation.
Trust Remains the Biggest BarrierThe discussion quickly moved beyond technology and into trust.
Participants repeatedly highlighted that AI will only gain wider adoption if operators can demonstrate that automated decisions are transparent, explainable and capable of standing up to regulatory scrutiny.
Questions raised throughout the session included:
- How can AI-driven decisions be audited?
- How can operators demonstrate consistency and avoid bias?
- What level of human oversight should remain within the process?
- Can regulators be confident in automated verification outcomes?
Many participants viewed human-in-the-loop models as the most practical approach, allowing AI to complete initial document reviews while experienced compliance professionals retain responsibility for complex or higher-risk cases.
Practical Challenges Still Need SolvingAlongside regulatory concerns, operators identified several practical barriers that continue to slow adoption.
Legacy technology remains a significant obstacle, with many onboarding and compliance platforms lacking the APIs or flexibility needed to integrate modern AI tools efficiently.
Data privacy also featured prominently. Questions around GDPR, model training data and the handling of sensitive identity documents continue to create uncertainty for operators evaluating AI-powered verification.
For businesses operating across multiple jurisdictions, document variation presents an additional challenge. Supporting passports, national identity cards and local documentation across numerous countries requires significantly more sophistication than many vendor demonstrations initially suggest.
Smaller operators also highlighted a lack of clarity within the vendor landscape. Many recognised they would likely purchase rather than build AI capabilities, yet admitted they were unsure which providers offered genuinely proven solutions or how competing platforms should be evaluated.
Finally, commercial considerations remain difficult to ignore. Without robust evidence demonstrating measurable efficiency gains, improved accuracy or reduced operational costs, building a compelling business case for investment remains challenging.
Looking AheadThe roundtable provided an honest snapshot of where the industry currently stands.
AI document automation is no longer viewed as a futuristic concept. Most operators recognise its potential to improve efficiency, strengthen compliance processes and accelerate customer onboarding.
However, the industry has not yet crossed the line from interest to widespread implementation.
Regulatory uncertainty, integration challenges, vendor complexity and the high stakes associated with compliance decisions continue to encourage caution.
The organisations most likely to gain an advantage will not necessarily be those investing the most, but those prepared to begin learning. Starting with focused, low-risk use cases allows operators to build internal expertise, understand where AI delivers value and develop confidence before scaling more ambitious programmes.
For technology providers, the opportunity is equally clear. Solutions that are transparent, easily integrated and capable of demonstrating regulatory robustness will be best positioned to help operators bridge the gap between curiosity and confident adoption.
Author: Neil Dillon, Solas Compliance