INDUSTRY INSIDER: MARK MCGUINNESS


beyond the superficial ‘productivity’ stage into true systemic integration. Success is found in the engineering of the workflow, not just the code.


REGULATORY SCRUTINY AND THE UKGC


The UK Gambling Commission (UKGC) has already signalled its stance with increasing gravity. In its 2024–2027 Corporate Strategy, the regulator made it clear that while it welcomes innovation, any use of AI must be subject to appropriate human intervention, governance, and assurance.


The Commission is moving beyond mere observation and into the realm of prescriptive expectation. They are looking for ‘explainability’ in every algorithm. If a player is flagged or a bet is refused, the operator must be able to demonstrate the logic behind that decision. A ‘black box’ excuse will not hold up in a regulatory review. The UKGC is specifically concerned with how AI interacts with the LCCP (Licence Conditions and Codes of Practice). They expect AI to be a shield for the vulnerable, not just a sword for the marketing department.


This means your AI must be trained on high quality, unbiased data to avoid discriminatory practices or the accidental targeting of at-risk individuals. If you cannot explain the “why” behind the AI, you are failing your licence.


OPERATIONAL REALITY


AI systems in iGaming are already handling 92 per cent of unusual transaction patterns for fraud detection according to Gitnux data for 2026. They are also managing 65 per cent of player queries through automated chatbots. Most impressively, these systems can now predict problem gambling signs 48 hours earlier than manual intervention. These are not just productive tasks. They are core regulatory and operational functions that require a different level of management.


If the human staff do not understand how the underlying system reaches its conclusion, the business risks significant compliance failure. We must treat AI adoption as an engineering project, not a marketing one.


We need to move away from the ‘black box’ mentality and embrace a culture of transparency that mirrors the best practices of modern software development.


THE IMPLEMENTATION HIERARCHY


To navigate this, we must establish a hierarchy of implementation. It begins with Policy. You must define the ethical and operational boundaries of AI within your firm before you buy the licenses.


Then comes the Business Case. AI for the sake of AI is a cost centre. You must identify where it solves a systemic bottleneck, such as KYC verification or real time RTP monitoring. Following


this, you must build the Governance and SOPs. There must be clear protocols for when a human must override an AI decision. Finally, you must invest in Upskilling. Your staff must move from being ‘doers’ to being ‘editors’ and ‘auditors’ of AI output.


This transition is perhaps the most difficult part of the process because it requires a shift in mindset as much as a shift in skill.


LEGACY AND TRUST


I have seen our industry evolve from smoke filled betting shops to state-of-the-art server rooms. The introduction of AI is simply the next chapter of that lineage. We are currently at the stage where many are enamoured by the ‘magic’ of the output without respecting the mechanics of the input.


But let us be clear: the winners of this era will not be those who use AI to write more emails. They will be the ones who integrate it as a governed, transparent, and human led system. The future of iGaming is undoubtedly automated, but it must be an automation that is understood by the people running the show. If we lose the thread of human accountability, we lose the trust of our players and our regulators. We should look at the technical reality of the current landscape. Large language models are becoming more accessible, yet the data they consume remains the most valuable asset. If your internal data is messy, your AI output will be flawed.


This is the ‘garbage in, garbage out’ principle that has governed computing for decades. In the context of iGaming, ‘garbage out’ could mean a million-pound regulatory fine or a devastating breach of AML protocols. Therefore, the first step in any AI strategy is actually a data strategy. You must clean your house before you invite the robot in to help you manage it. This is where the engineering discipline becomes invaluable.


WHAT COMES NEXT? The iGaming Roundtable discussions highlighted that we are currently in a ‘Wild West’ phase of AI experimentation. Many small to medium enterprises are rushing to adopt


About the author


Mark McGuinness is an ‘architect of high-impact iGaming marketing.’ He is currently fractional CMO at Devilfish.com and brings over 24 years of elite digital marketing leadership to the role, advising top-tier iGaming operators across diverse regulated landscapes. He translates deep analytical power, honed from his scientific background, into breakthrough strategies for affiliate marketing, Web3, social poker, and casino gaming. McGuinness champions the game-changing integration of neuroscience and behavioural economics to skyrocket customer engagement and conversion.


third party tools without a full understanding of the security implications.


Where is your data going? Who owns the prompts? What happens if the service provider changes their terms? These are the questions of a seasoned operator. We need to approach AI with the same rigour we apply to our gaming math and our financial audits.


It is a matter of professional integrity and long-term viability. Those who succeed will be those who view these systems through the lens of process and workflow.


As we look towards 2030, the integration of AI will become invisible. It will be the wallpaper of the industry. But between now and then, there is a lot of hard work to be done in the ‘engine room’ of our businesses.


We need to stop talking about AI as if it is a magic wand and start talking about it as if it is a new, complex, and high stakes operating system. Only then can we truly harness its power to create a safer, more efficient, and more profitable industry for everyone involved.


MAINTAINING TRUST IN A DIGITAL WORLD The legacy of our third-generation predecessors was built on trust and a deep understanding of the game and the maths that governed it. Our legacy will be defined by how well we maintain that trust in a digital world governed by algorithms.


The core of our industry is human psychology, risk, and entertainment. AI can enhance the delivery of these things, but it cannot replicate the nuance of a relationship or the intuition of a seasoned floor manager. What AI will do is strip away the drudgery, allowing us to be more human, not less. But this only happens if we are the masters of the machine. If we allow the machine to run without a map, we are simply waiting for a crash. Let us build the map first. Let us set the policy, train the people, and then, and only then, let us turn on the power. Success is not found in the software itself, but in the engineering of the workflow that surrounds it. We need to quit looking for the shortcut and start looking at the blueprint.


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