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From AI Pilots to Production: A Guide to Navigating the New iGaming AI Landscape

By jili tutorial · September 18, 2026

From AI Pilots to Production: A Guide to Navigating the New iGaming AI Landscape

In September 2026, CreateFuture announced two senior appointments that signal a fundamental shift in how betting and gaming operators are approaching artificial intelligence. Eddie Bennett joins as Director of Lottery and iGaming, while Andy Wright becomes Strategic Advisor—both joining the consultancy’s iGaming practice under Industry Director Hass Peymani. These hires are not merely personnel changes; they reflect a maturing understanding that the biggest obstacles to AI success are no longer technical.

This comprehensive guide unpacks the context behind the appointments, examines the real barriers operators face, and offers actionable insights for turning AI pilots into production-ready, regulator-approved systems.

The Changing Landscape of AI in iGaming: From Technical Hurdles to Business and Regulatory Challenges

The prevailing narrative in iGaming AI has long been one of rapid innovation: machine learning models that predict player behaviour, neural networks that optimise trading, and algorithms that detect fraud in real time. Yet behind the headlines, a growing number of operator AI programmes are stalling—and not because the models themselves are underperforming.

CreateFuture’s position, reinforced by the Bennett and Wright appointments, is clear: the binding constraint on operator AI is no longer the model but what sits beneath it. The core failure points now cluster around three areas:

This shift in priorities explains why operators are no longer asking, “How do we build a better AI model?” but rather, “How do we get the model we already funded into production, and how do we prove to regulators it works?”

“Almost every operator we meet has a slide deck of AI pilots and a data estate that cannot support any of them. That is not a failure of ambition, it is the cost of fifteen years of growth by acquisition.”
— Hass Peymani, Industry Director of iGaming, CreateFuture

Key Appointments at CreateFuture: Eddie Bennett and Andy Wright

The two new hires are operator-side veterans who have lived through the very challenges CreateFuture now helps clients solve. Their combined experience spans national lotteries, pool betting, retail, online sportsbook, and large-scale mergers—exactly the kind of complexity that characterises modern iGaming data estates.

Eddie Bennett – Bridging the Commercial Gap

Eddie Bennett brings over 20 years of operator-side experience, having held senior roles at Allwyn, UK Tote Group, BoyleSports, Sky Bet, and Lottoland. This breadth covers national lottery operations, pool betting, retail, and online—a rare combination that reflects the diversity of modern betting and gaming.

His remit at CreateFuture focuses on the commercial half of the AI deployment problem:

The appointment also formalises lottery as a distinct discipline within CreateFuture’s iGaming practice, separate from sportsbook. This is timely: lottery operators are now running the same data consolidation programmes as their sports betting counterparts, but with unique regulatory and business models.

“I have sat on the other side of this table. A model that performs in a test is not the same thing as a model a regulator will let you run. That takes a business case, an operating model and an audit trail. CreateFuture has the engineering and data depth already. My job is to make sure the commercial argument stands up as well as the technology does.”
— Eddie Bennett, Director of Lottery and iGaming, CreateFuture

Andy Wright – Guiding Funded Programmes to Production

Andy Wright brings 27 years of experience as a chief executive and senior operator across betting, gaming, and regulated consumer businesses. His career highlights include leadership roles during two landmark integrations:

At Ladbrokes, Wright took a stalled, already-funded technology programme and drove it into live operation as an automated trading platform running across five markets. This hands-on experience directly addresses the most common failure pattern in operator AI: programmes that receive initial approval but never reach the trading floor.

As Strategic Advisor, Wright will:

“Boards rarely struggle to approve the first investment. They struggle to explain the second when the first never reached the floor. The operators calling now are not asking how to start. They are asking how to finish what they have already funded.”
— Andy Wright, Strategic Advisor, CreateFuture

The Underlying Problem: Data Infrastructure as the Primary Constraint

Why is data infrastructure the single biggest bottleneck? Consider a typical operator estate. Over a decade of acquisitions, market-by-market builds, and platform migrations leaves behind inconsistent player records across brands. A player who uses both a sportsbook and a casino brand within the same group may appear as two different people in two different databases—or worse, have multiple wallets and journey histories that don’t reconcile.

The consequence is stark: a personalisation engine, a trading model, and a compliance team can each return a different answer about the same customer from the same underlying data. This is not just a performance issue—it is a regulatory liability. Regulators increasingly demand a single, consistent view of the player for responsible gambling checks, anti-money laundering monitoring, and fair play audits.

Real-World Example: CreateFuture and evoke

CreateFuture is currently working with evoke on exactly this kind of data consolidation. The goal is a single, consistent view of the player across brands and markets. According to CreateFuture, this foundation is already running production workloads in:

Crucially, each application reads the same player record, wallet, and journey that compliance and finance teams use. This alignment is a requirement for regulatory defensibility in licensed markets.

Why this matters: Without a consolidated data platform, every AI model is built on shaky ground. A model trained on a subset of data may perform well in a test environment but fail in production because the real-world data is inconsistent. Worse, it may produce biased or unfair outcomes that a regulator could challenge.

The Role of AI Academy at SBC Summit Lisbon 2026

CreateFuture is the headline sponsor of the AI Academy at SBC Summit Lisbon 2026, running from 29 September to 1 October at FIL and the MEO Arena. The event is expected to draw 40,000 attendees from more than 150 countries, making it one of the largest iGaming gatherings globally.

Key Speakers and Sessions

The Academy’s focus—moving from pilot to production, building regulatory evidence, and solving data infrastructure—mirrors exactly the challenges that Bennett and Wright are now helping clients address.

About CreateFuture and Its Strategic Position

CreateFuture is an AI transformation and engineering consultancy headquartered in Edinburgh. In 2026, it was acquired by Version 1, forming a combined group of approximately 4,250 staff with revenues exceeding €500 million. The firm itself has around 550 professionals across offices in Edinburgh, Glasgow, Leeds, London, and Sofia.

Its iGaming client roster includes major names:

Strategic partnerships reinforce its credibility:

This combination of operator-side talent, deep engineering capability, and cloud infrastructure expertise positions CreateFuture as a bridge between the technical promise of AI and the commercial/regulatory reality of licensed gaming.

Practical Takeaways for Operators and Investors

The story of Bennett and Wright’s appointments, and the data infrastructure crisis they highlight, offers several lessons for anyone involved in iGaming AI:

1. Audit Your Data Estate Before Building Models

If you cannot produce a consistent player record across all brands and markets, no AI model will be trustworthy—and no regulator will approve it. Invest in data consolidation as a prerequisite, not an afterthought.

2. Build the Business Case and Audit Trail in Parallel

As Eddie Bennett emphasises, a model that performs in a test is not the same as a model a regulator will let you run. Start documenting your data lineage, model training decisions, and fairness testing from day one.

3. Focus on “Finishing What You’ve Funded”

Andy Wright’s observation is a reality check: many operators have already approved AI budgets but never saw the outcomes. Ask your team whether existing programmes are fully deployed, and if not, identify the organisational or infrastructure blockers.

4. Treat Change Management as a Transformation Job

Hass Peymani’s insight is crucial: moving from pilot to production is not a technology purchase—it’s a transformation. That means changing how the business operates on top of the platform, which requires executive sponsorship, cross-functional teams, and clear governance.

5. Leverage Industry Events for Peer Learning

The AI Academy at SBC Summit Lisbon provides a concentrated opportunity to learn from operators, technology providers, and regulators. Sessions like “From Pilot to Production” offer real case studies that can save years of trial and error.

Conclusion

The appointments of Eddie Bennett and Andy Wright at CreateFuture are more than corporate news—they are a signal that the iGaming industry has entered a new phase of AI maturity. The era of flashy pilots without production follow-through is ending. In its place, operators are demanding practical, commercially sound, and regulator-ready AI deployments built on solid data infrastructure.

For boards, executives, and investors, the message is clear: the next competitive advantage will not come from the best algorithm, but from the best foundation.