Here's the uncomfortable truth the findings in this report reveal: more than half of respondents believe AI is fully integrated across their marketing channels. Yet not a single respondent can launch a campaign in less than a day. Nearly a third still take over a month.
This isn't a success story. It's a warning sign.
The industry has declared victory on AI adoption while the evidence suggests something far less triumphant: operators have digitized their old workflows without fundamentally reimagining them. The sector has fallen into the halfway trap. It has all the complexity of AI, none of the agility it promises.
The Complacency Problem
Perhaps most revealing is what respondents said when asked how important execution speed is to competitiveness. Just 17% called it "critical." More than half dismissed it as merely "somewhat important."
This should alarm anyone paying attention to where iGaming is heading. Speed isn't just operational efficiency; it's survival. Player expectations shift daily. Regulatory environments evolve by the quarter. Competitors emerge from adjacent markets with no legacy infrastructure to slow them down.
The real risk isn't being slow. It's not knowing you're slow while others figure out how to move faster. When 73% of marketers struggle to measure campaign impact and 61% cite resource dependencies as barriers, the problem isn't a lack of AI tools. It's a lack of transformation.
Of respondents view execution speed as "critical" to improving competitiveness
However, more than half of marketers claim it to be only "somewhat important"
Cite resource dependencies as barriers when it comes to execution speed
Three Shifts That Separate Leaders from Followers
From Tools to Capabilities
Most teams have adopted AI tools: email automation platforms, basic personalization engines, and social media schedulers. The research confirms it: 39% use marketing automation, while 31% have personalisation engines. But these are tools, not capabilities.
Real capabilities are systems that enable real-time decisioning across channels, closed-loop optimization that learns without manual intervention, and prediction models that anticipate player behaviour. The question isn't "do we have AI?" It's "can our AI do things we couldn't do before?"
If personalization remains limited to product recommendations and behavioural triggers, organizations are automating the past, not building the future.
From Integration to Independence
Positionless Marketing has captured the industry's attention for good reason. The survey found 91% expect it to deliver greater team independence, and 61% believe it will enable faster execution. Yet only 13% operate this way today.
At its core, Positionless Marketing gives every marketer the power to execute instantly and independently through three essential capabilities: Data Power to discover insights without waiting for engineers. Creative Power to generate assets without waiting for creative teams. And Optimization Power to run self-optimizing campaigns without waiting for analysts.
The vast majority of respondents to our survey believe Positionless Marketing will deliver greater team independence
Which begs the question: Why are only 13% currently operating in a fully Positionless way?
The 69% who wait on creative teams, the 67% who depend on media buyers, the 55% who can't move without analytics... these aren't collaboration points, they're bottlenecks.
Operators like Caesars Entertainment and FDJ United demonstrate what going beyond halfway looks like. Rather than layering AI on top of existing workflows, they've rebuilt the workflows themselves. They are enabling marketers to move from insight to execution in real time while compliance and brand guardrails remain embedded in the system, not bolted on at the end.
The path from the 45% who are "experimenting" to fully operational requires radical honesty about what independence costs: investment in new platforms, training that builds real capability, process redesign that challenges sacred cows, and letting go of control.
From Measurement as Reporting to Measurement as Infrastructure
Of respondents are struggling to measure campaign impact
Are experimenting with Positionless marketing, with 41% moving in that direction
When 73% struggle to measure campaign impact, the instinct is to blame the tools or the data. But most organisations treat measurement as something that happens at the end. A report. A dashboard. A post-mortem.
Leaders are building measurement into the infrastructure from the start. They're instrumenting every touchpoint, creating closed-loop systems where results feed directly into the next decision, and designing experiments that produce learning regardless of outcome.
The New Imperative
The halfway trap is comfortable. Marketing teams have invested in AI, they can check the box, they can point to automation and personalization in their strategy decks. But comfort is the enemy of transformation.
The critical questions for leadership: Are teams using AI to do what they already do faster, or to do things they couldn't do before? Can they launch campaigns in days, not months? Are marketers empowered or dependent?
The gap between AI adoption and AI transformation is where winners and losers will be decided. The data suggest that most of the industry is still stuck in the middle.
The answer lies in eliminating dependencies, not just adding tools. The halfway trap has an exit, but only for those willing to fundamentally rebuild how marketing works.
