The gap between AI strategy and working software
Most AI projects fail not because the technology doesn't work, but because nobody builds the bridge between the strategy deck and a system real people can use. Ariena Phannaen builds that bridge. As Head of AI Delivery and Design at Sovata AI, she is responsible for turning AI deployments from architecturally sound plans into intuitive, production-ready systems that staff actually adopt.
Her background spans both sides of the line that most practitioners sit on one side of: she designs experiences with the rigour of a product designer and builds them with the pragmatism of a developer. That combination is rare — and it is what separates Sovata's deployments from AI implementations that look good in demonstrations and fail in daily operation.
“An AI system that staff don't trust or don't understand won't be used. The governance and the guardrails matter — but so does the moment a person first touches the interface and decides whether to trust it.”
— Ariena Phannaen, Head of AI Delivery & Design
What human-centred AI delivery looks like in practice
For Ariena, a successful AI deployment has two measures: it does what it was designed to do, and the people who use it feel confident using it. Achieving both simultaneously requires understanding how non-technical staff relate to AI systems — their concerns about accuracy, their instinct to second-guess outputs, and their tolerance for complexity in a tool they're expected to rely on.
Her delivery process starts with the user journey, not the model. Before any technical implementation begins, she maps how different roles in an organisation will interact with the AI: what they'll ask, what they'll expect, what will confuse them, and what will erode their trust. The interface, the prompting architecture, and the governance controls are all designed around those answers.
Areas of expertise
See the delivery process in action
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