Evoke’s chief risk and intelligent automation officer, Harinder Gill, has spoken openly about how the operator is deploying artificial intelligence across the entire player journey.
The interview forms part of the State of AI Adoption in iGaming 2026 report, set to be published by The Playa and NEXT.io on 3 June.
At Evoke, artificial intelligence is helping the company better understand what its players are communicating, fundamentally revolutionising how customer research is conducted.
“Historically, feedback from customers was collected mostly from our UK users, which was often difficult to get any actionable insights from. To address this, we combined the voice of our customer with machine learning, generative AI and automation, to redevelop the entire end-to-end process,” Gill explained.
The system now ingests raw data, transforms it into actionable insights, and delivers results directly to dashboard teams across the company for immediate use.
“Based on the success of this initiative, we plan to roll it across all markets and languages to support our customer facing teams,” Gill added, signalling ambitious plans for wider deployment.
To drive these efforts forward, Evoke has established an Intelligent Automation and AI Centre of Excellence, staffed with more than 40 specialists recruited partly from outside the gaming industry.
“We want our colleagues to see AI as a powerful tool for creating new content, enabling infinite personalisation, and working more efficiently across our global offices,” said Gill.
Gill described AI as having become a core capability and integral part of Evoke’s broader business strategy over the past few years.
“Our AI strategy focuses on building a culture that embraces AI, upskilling forward-looking employees, and using the technology safely in daily work to improve how we operate and serve our customers,” he said.
Evoke has also built a target business architecture designed to scale personalised player experiences, supporting more tailored betting and gaming offerings underpinned by AI-powered safer gambling tools, customer 360 views, and risk monitoring.
In the operator’s trading room, algorithms are already adjusting trading limits in real time, demonstrating how automation and intelligence are extending from analytics into live operational environments.
Gill confirmed that Evoke is primarily using AI to support back-office processes, with human accountability remaining central to all decisions and outcomes at this stage.
While AI-driven analytics are being applied to areas such as churn, VIP identification, and player value, their use in direct decision-making is described as still being in its early stages.
“We are very careful when it comes to AI influencing player-facing decisions, such as bonuses, promotions, or communication frequency,” Gill said. “We start with small, tightly defined use cases, monitor outcomes closely, and expand over time.”
Despite that cautious approach, AI’s measurable impact at Evoke is already visible across operational efficiency, streamlined processes, reduced time to market, and improved productivity.
Personalised offerings and customer interactions have also improved, supporting revenue growth while simultaneously enhancing player safety and Net Promoter Scores across the business.
Each use case within Evoke’s global operations is assessed against clear success criteria, ranging from reducing lead times and identifying harmful behaviours earlier to delivering cost savings and revenue uplift.
“At this stage most of the value comes from back-office processes, particularly those involving high-volume activity,” Gill said, underlining where the technology is currently delivering the strongest returns.
Gill was equally clear that Evoke is deliberately avoiding areas where AI might replace human judgment or interact directly with customers without appropriate oversight being in place.
“Our approach is to augment our workforce rather than replace it,” he said, drawing a firm line around how the technology is being positioned internally across the organisation.
Looking ahead, Gill acknowledged that the pace of AI innovation itself presents a significant strategic challenge for operators seeking to build and own technology independently.
“While we would love to own all our technology in-house, the rate of change and resources required to innovate from the ground up can be very capital intensive,” Gill concluded.
