Artificial intelligence is changing the way that iGaming companies are run and the current revolution in technology will continue to reshape the industry in the months and years to come.
Amid this technological change, BetConstruct AI’s Chief AI Officer Mushegh Khachatryan tells SBC News how the company is utilising AI and how it has the potential to help operators cut costs and generate revenue.
How is BetConstruct AI using artificial intelligence to help operators create personalised experiences for their customers?
Personalisation is much more than recommending games. We aim to understand each player: what they like and ignore, how and when they play, how price- or bonus-sensitive they are, and how their behaviour is changing.
That intelligence can shape the entire customer journey: the casino lobby, game recommendations, promotions, messaging and even when not to communicate.
Our goal is to move from one casino experience for one million players to one million tailored experiences.
What is the commercial uplift that you see by introducing personalised experiences for players?
Results depend on the operator, market and product maturity, so there is no universal figure. Across our deployments, however, recommendation systems have delivered uplift ranging from high single digits to significantly higher levels. More mature implementations can improve turnover by around 10–15% in the areas where personalisation is applied.
The impact also compounds: better discovery, retention, CRM conversion and bonus efficiency together create a significant commercial effect.
We see AI not as one feature delivering one KPI improvement, but as an intelligence layer improving many decisions across the business.
Are the commercial gains the result of longer session times or higher bet frequency, or both?
Both, but the main improvement comes from reducing friction. When players quickly find relevant content, they spend less time searching and more time engaging.
That can increase session depth, game discovery, bet frequency and retention. The objective is not simply to maximise playing time; it is to improve relevance. When the experience is more relevant, customers engage more naturally and commercial KPIs follow.
AI Agents have been incredibly popular in 2026. How do the AI Agents that BetConstruct have developed help operators manage campaigns and their platforms through simple chat commands?
Until recently, AI in iGaming mainly operated in the background through recommendation, churn and fraud models. We are now connecting those models, data and operational tools through agents.
Instead of opening multiple dashboards and requesting reports, an operator could ask:
“What happened to casino revenue yesterday?”
The agent can explain what changed. The operator can then ask:
“Which player segments caused the decline?”
And finally:
“Create a campaign for the segment with the highest churn risk.”
We are moving from dashboards that display information to AI systems that understand, analyse and eventually help execute tasks. Our Operational Copilot is being built around this idea: the interface is conversational, while the complexity remains behind it.
Which areas of an iGaming business do AI agents perform the most effectively, and which ones still strictly require human oversight?
AI is strongest where there is substantial data, repetition and measurable outcomes. CRM, analytics, player segmentation, campaign preparation, customer support, content discovery and operational monitoring are natural applications. An agent can analyse millions of data points faster than a human and identify patterns that might otherwise be missed.
However, humans must remain responsible for significant financial decisions, responsible gambling interventions, regulatory decisions and unusual customer situations. Our aim is not to remove people from operations, but to reduce repetitive work so they can focus on judgement, creativity and responsibility.
How is BetConstruct’s AI detecting risky behaviour and bonus abuse in real time before operators’ systems are exposed?
AI can identify emerging risk before a rule is broken. Traditional systems might block an account after a defined number of events, while machine learning analyses hundreds of behavioural signals simultaneously to detect unusual activity earlier.
We examine deposits, withdrawals, betting behaviour, bonus usage, game selection, account activity and changes from a player’s normal pattern. The system looks for both known fraud patterns and anomalies.
Rather than waiting to conclude that a player has abused the system, we want to flag statistically unusual behaviour for review. We apply the same approach to negative-NGR prediction, hidden VIP detection, churn and other behavioural models. This turns AI from a reporting tool into an early-warning system.
How do you keep on top of the rapid development of AI models and ensure that BetConstruct’s solutions keep up with those developments so your products are industry leading?
We don’t try to predict which model will win. We build our technology so we don’t have to.
Our architecture is model-agnostic. We continuously test new models against real iGaming use cases, and when something is better, we can adopt it quickly. Because the real competitive advantage is not the model itself. Models will be available to everyone.
The advantage is your data, your domain knowledge and how well you turn those models into products that create real business value.
So we develop and adopt what actually makes the product better.