Tugi Tark whitepaper examines economics of AI iGaming support

Tugi Tark has released a detailed 2026 whitepaper titled The economics of AI-powered iGaming customer support, presenting a structured argument that artificial intelligence is reshaping the financial and operational dynamics of player support services within the iGaming sector. The report adopts a data-driven and analytical tone, focusing on how automation technologies can influence cost structures, efficiency metrics and ultimately player retention outcomes.

The company positions its findings within a broader industry shift, where operators are increasingly exploring scalable and cost-efficient alternatives to traditional human-led customer service models. While the whitepaper highlights potential benefits, it also frames its conclusions as grounded in available datasets and observed operational deployments.

Cost comparison between AI and human-led support

A central claim in the whitepaper concerns the comparative cost efficiency of AI-driven support systems versus human agents. According to the report, AI-handled customer service tickets are priced at approximately EUR 0.15 per interaction. This figure is described as based on verified pricing models observed across deployments.

In contrast, the whitepaper references labour cost benchmarks for human-operated support centres in Eastern Europe, particularly in Romania and Bulgaria. These are estimated to range between EUR 1.73 and EUR 1.88 per ticket when fully loaded employer costs are considered. These costs include salaries, benefits, infrastructure and training.

The report introduces a blended cost model that assumes a 70 percent AI containment rate. Under this scenario, the estimated average cost per ticket falls to approximately EUR 0.67. This figure is presented as representing a reduction of roughly 64 percent when compared to a fully human-led baseline at EUR 1.88 per ticket.

While these figures are presented as indicative rather than universal, they are intended to illustrate how automation can influence unit economics when implemented at scale.

Data sources and analytical framework

Tugi Tark states that its conclusions are based on a combination of publicly available data and proprietary operational insights. The report references Eurostat 2024 labour cost datasets as a benchmark for human workforce expenses. In addition, it incorporates published research on AI chatbot performance metrics and independent studies examining player behaviour in iGaming environments.

The company also draws on internal deployment data gathered from its own implementations. This includes metrics related to ticket handling efficiency, response times and user interaction patterns. The combination of these sources is presented as forming a comprehensive analytical framework, although the company does not disclose specific client identities or operational details.

Projected reductions in support expenditure

Beyond per-ticket cost comparisons, the whitepaper expands its analysis to overall support expenditure. Tugi Tark estimates that operators adopting AI-powered systems could achieve reductions in total customer support costs ranging from 55 percent to 75 percent. These projections are framed as dependent on implementation scale, operational complexity and the degree of automation achieved.

A further point raised in the report relates to scalability. AI systems are described as capable of handling sudden increases in customer queries without requiring additional recruitment or extended training periods. This capability is particularly relevant during high-traffic events such as major sporting tournaments, where customer engagement levels tend to rise sharply.

The whitepaper suggests that this flexibility may allow operators to maintain service levels during peak periods without incurring proportional increases in operational costs.

Executive perspective on industry transformation

Harpo Lilja, founder and chief executive officer of Tugi Tark, provides a strategic perspective within the report. He states: “In 2026, the ‘wait-and-see’ approach to AI is costing operators millions in unnecessary overhead. We aren’t just talking about chatbots; we’re talking about a fundamental shift in the unit economics of player retention.”

This statement reflects the company’s position that AI adoption is no longer an experimental initiative but a structural change in how customer support functions are designed and delivered. The emphasis on retention economics suggests that the company views support services not only as a cost centre but also as a driver of long-term revenue stability.

Customer support as a retention driver

The whitepaper devotes significant attention to the relationship between customer support performance and player retention. It highlights that payment-related issues account for approximately 52 percent of customer support tickets in iGaming environments. These issues often require timely resolution to maintain user trust and satisfaction.

The report argues that slower response times can contribute to increased churn rates. In this context, AI-driven systems are presented as offering faster initial responses, with average first response times estimated at around seven seconds. By comparison, human agents are reported to average approximately 60 seconds for initial engagement.

Tugi Tark suggests that even modest improvements in churn rates can have measurable financial impacts. The whitepaper provides an illustrative scenario in which a 0.5 percentage point reduction in churn could result in the retention of 500 additional players per month for a mid-sized operator. Based on an assumed player lifetime value of EUR 400, this could correspond to approximately EUR 200,000 in additional annual revenue.

These projections are presented as hypothetical examples designed to demonstrate potential outcomes rather than guaranteed results.

Operational use cases for AI deployment

The report outlines several operational areas where AI systems can be integrated into iGaming customer support workflows. These include responsible gambling escalation processes, where automated systems can identify risk indicators and route cases for further review.

Another area is identity verification and compliance procedures, particularly Know Your Customer and Anti-Money Laundering workflows. AI tools are described as capable of assisting with document verification and data analysis, potentially reducing processing times.

The whitepaper also addresses data protection considerations, referencing alignment with General Data Protection Regulation requirements. It suggests that AI systems can be configured to maintain data sovereignty and ensure compliance with regulatory frameworks, although implementation details may vary depending on jurisdiction and system architecture.

Limitations and considerations

While the whitepaper presents a positive outlook on AI adoption, it implicitly acknowledges that outcomes may vary depending on implementation quality and operational context. Factors such as system training, integration with existing platforms and regulatory compliance requirements can influence performance.

Additionally, human oversight remains relevant in complex or sensitive cases, particularly those involving regulatory compliance or player welfare. The report does not suggest a complete replacement of human agents but rather a hybrid model where AI handles high-volume, routine interactions while human staff address more complex issues.

Broader implications for the iGaming sector

The findings presented by Tugi Tark reflect a broader trend within the digital services industry, where automation technologies are increasingly used to optimise operational efficiency. In the context of iGaming, where customer engagement is continuous and often time-sensitive, the ability to provide rapid and reliable support can influence both user experience and commercial outcomes.

The economic argument presented in the whitepaper aligns with ongoing efforts by operators to balance cost control with service quality. As regulatory scrutiny and competition intensify, the adoption of technologies that can support both objectives may become more widespread.

Conclusion

Tugi Tark’s 2026 whitepaper presents a structured analysis of how AI-powered customer support systems can influence the economic and operational landscape of the iGaming industry. By comparing per-ticket costs, response times and retention outcomes, the report highlights potential efficiencies associated with automation.

At the same time, the analysis underscores the importance of implementation strategy and regulatory alignment. AI is positioned not as a standalone solution but as part of a broader operational framework that includes human oversight and compliance safeguards.

The report ultimately frames AI adoption as a strategic decision with both financial and customer experience implications. While the projections outlined are based on specific assumptions, they contribute to an ongoing discussion about how technology can reshape service delivery models in the iGaming sector. As operators continue to evaluate these approaches, the balance between efficiency, compliance and user trust is likely to remain central to future developments.

FAQs

What is the main focus of the Tugi Tark whitepaper?
The whitepaper examines how AI-powered systems can reduce costs and improve efficiency in iGaming customer support operations.

How much does an AI-handled support ticket cost according to the report?
The report states that AI-handled tickets are estimated at approximately EUR 0.15 per interaction.

What are the estimated costs of human-led support tickets?
Human-operated tickets are estimated to cost between EUR 1.73 and EUR 1.88 per ticket based on labour data.

What is meant by AI containment rate?
AI containment rate refers to the percentage of customer queries fully resolved by AI without human intervention.

How does AI impact response times in customer support?
The report indicates AI systems can respond in around seven seconds compared to about 60 seconds for human agents.

What percentage of support tickets are related to payments?
The whitepaper states that approximately 52 percent of tickets are linked to payment-related issues.

Can AI completely replace human customer support agents?
The report suggests a hybrid model where AI handles routine queries and humans address complex cases.

What is the potential impact of reduced churn rates?
A small reduction in churn could lead to retaining more players and increasing annual revenue.

How does AI support regulatory compliance?
AI can assist with KYC, AML processes and GDPR-aligned data handling depending on system design.

What industries can benefit from similar AI applications?
While focused on iGaming, similar AI support models can be applied in other digital service industries.