AI is becoming a more meaningful part of how iGaming businesses build, operate and innovate. But its value comes from how it is applied in practice, whether that means improving internal efficiency, supporting product development or creating better user experiences.
At Flows, that thinking is tied closely to a broader view of connected intelligence, where people, AI and systems work together rather than in isolation.
In conversation with SBC News, Alvaro Elosua, Product Enablement Lead, AI & Onboarding at Flows, shares how the business is approaching AI, what he has been building and where he sees the biggest opportunities for AI to create practical value for users and operators alike.
What do you think the industry still gets wrong about AI?
Most companies are trying to use AI as the engine that does everything and that is exactly why most AI projects fail.
AI is excellent at understanding intent, language and context, but it is not a system of record and it is not a reliable logic engine.
To actually create value, you need the right architecture around it. That is where Flows comes in. Flows sits as the orchestration layer across an operator’s entire stack, connecting AI, real systems, real data and deterministic logic, AI understands the why, Flows executes the how.
The real mistake the industry makes is treating AI as a replacement for systems, instead of as an intelligence layer on top of them. AI is not a system. It is an intelligence layer that needs structured systems around it to create real outcomes.
From your perspective, where can AI make the biggest difference inside a business today?
The biggest impact today is in turning unstructured user interactions into actionable decisions in real-time.
Players do not speak in structured data. They complain, hesitate, get frustrated and ask unclear questions. AI can interpret that intent instantly and classify it into meaningful signals such as bonus issues, withdrawal confusion, risk signals and churn risk.
At Flows, we take that one step further. That understanding becomes an immediate trigger, and critically, this can be deployed and iterated in hours, not months, without rebuilding core systems. Flows then orchestrates what happens next across all connected systems.
A single message from a player can instantly activate a flow by:
- Triggering a bonus.
- Initiating a responsible gaming interaction.
- Escalating to support.
- Adapting the user experience dynamically.
All of this is coordinated through a single orchestration layer rather than fragmented across multiple tools. So instead of reacting too late, operators can act in the exact moment it matters, while their user is still engaged.
As you have studied AI more deeply and started applying it in practice, what have been some of the biggest lessons for you so far?
AI is evolving extremely fast, but value does not come from chasing the latest model, it comes from how you apply it.
What feels difficult today might be trivial in a few weeks, so staying up to date is critical. But even more important is designing systems that are flexible enough to evolve with AI.
The winners will not be the ones using the most advanced models, but the ones who integrate AI into real workflows in a scalable and controlled way.
The real skill is not using AI, it is knowing where and how to use it right.
What has mattered most in shaping Flows’ approach to AI, both in terms of what you build and how you apply it across the business?
Everything we build around AI is focused on one thing: real impact.
We do not see AI as ‘just’ a feature. We see it as a foundational layer that enhances everything else.
That means:
- AI for understanding intent.
- Flows for executing logic and orchestration.
- Systems working together instead of in isolation, with Flows acting as the layer that coordinates how those systems interact.
This approach ensures AI is useful, reliable and scalable across the business.
What have been some of the biggest challenges in developing AI at Flows so far, and how have you worked through them?
A key challenge is balancing flexibility with control.
AI by nature is probabilistic, while operators need deterministic outcomes, especially in areas like bonuses, payments or responsible gaming.
We have addressed this by separating responsibilities:
- AI handles understanding and decision support.
- Flows orchestrates rules, limits and execution across systems.
Another challenge is making AI fast and reliable enough for real-time use. AI responses need to be fast enough to work in real-time user interactions, which requires careful architecture.
Looking ahead, what do you think will be the next big test for AI in iGaming?
The real challenge is not speed or reliability. Those will improve naturally over time. The real challenge is domain knowledge.
iGaming is not a generic use case. It is a highly specialised, regulated, real-time environment where bonuses, payments, player lifecycle and compliance all interact.. Every operator works differently, every setup has its own logic, its own constraints and its own way of handling things like bonuses, payments or player lifecycle.
AI does not naturally understand that context. So the real gap is between how AI thinks and how iGaming actually works in practice.
To make AI truly useful, you need to bridge that gap by understanding:
- How operators behave.
- How systems are connected.
- The real business logic behind decisions.
At Flows, we have been working on training our agents specifically on the iGaming ecosystem, not just generic AI capabilities, but how this industry actually operates.
Because in the end, the value is not in having AI. The value is in having AI that understands your world. And that is where the real competitive advantage will come from.
How do you see AI shaping the next phase of Flows?
AI will become the natural interface for building and interacting with Flows, but Flows remains the orchestration layer that ensures everything runs in a controlled and connected way.
Instead of building workflows manually, users will be able to describe what they want, and AI will not only translate that into executable logic inside Flows, but also help fix, suggest and improve your workflows.
At the same time, AI will enhance how flows operate by:
- Interpreting user behaviour.
- Adapting experiences in real-time.
- Improving decision making across the lifecycle.
Flows remains the execution layer, AI becomes the intelligence layer and together they create a more powerful system.
What is one piece of advice you would give to operators or businesses looking to use AI more effectively?
Start simple, but start now.
Do not try to replace everything with AI. Focus on one area where AI can clearly add value, typically where there is unstructured data or user interaction.
Test, iterate and learn fast.
And most importantly, work with a setup that gives you control. AI without structure leads to inconsistency. AI combined with orchestration creates real impact.
What does Agentic AI actually mean in practice for iGaming operators?
Agentic AI is often misunderstood as replacing entire workflows with AI agents.
In practice, it is about giving AI a clear role within a structured process, not handing over full control.
At Flows, we are deliberately structuring how agents operate within controlled workflows. It understands the user and their intent, then triggers the right structured workflow, within a fully orchestrated environment.
That means operators can use AI to make interactions more intelligent and responsive, without losing visibility or control over what happens next.
So instead of a black box making decisions, you get:
- Intelligence from AI.
- Control through Flows.
- Execution through integrations.
That is what makes AI usable in real-world iGaming environments. It is what turns AI from something interesting into something practical.
How do you ensure AI remains compliant in a regulated industry like iGaming?
Compliance comes from control, not from the AI itself.
AI can suggest or detect, but it should never be the final decision maker in regulated actions.
In Flows, all critical actions like bonuses, responsible gaming interventions and payments are handled through structured logic, rules and limits, orchestrated centrally through Flows.
This ensures AI enhances decision making while the system remains auditable, transparent and compliant.