‘From Research to Reality: How AI Becomes Products, Platforms and Business Value’ - with Andrea Rosales

SEASON FIVE: In this week’s episode of Talent First, I chat to Andrea Rosales, data scientist and AI researcher and innovator, about what it really takes to adopt AI inside organisations beyond the hype.We talk about how companies are evaluating large language models and AI tools for enterprise use, and what decision makers should be looking for when the market is moving this quickly.Andrea shares her perspective on how AI, data science and traditional engineering are coming together, and what that means for how teams are built and structured, We also get into how ideas move from research into real products, the role of universities and industry collaboration, and why that gap between innovation and execution still matters.Our conversation explores governance and accountability, who owns AI once it is in production, and what this means for organisations operating in more regulated environments.We finish on the bigger picture. The AI Productivity Paradox, why more technology does not always mean more efficiency, and how companies can balance innovation with caution without falling behind.A practical and thoughtful conversation on how AI is being implemented and what leaders need to be thinking about now.About Our Guest: Andrea Rosales is an AI Research and Innovation Lead with over 15 years of experience delivering data and AI solutions across both industry and academia. She holds a PhD in Computer Science from the University of St Andrews, where her research focused on how AI systems learn and adapt in complex, real-world environments. Her work has evolved from domain adaptation and continual learning to more recent research on large language model reasoning and reliability, with a strong emphasis on building AI systems that are explainable and robust.She was recognised as a UK Global Talent for her contributions to AI in industry and academia. Currently, she is an Associate Director of Data Science at Blend, where she works with organisations to design and deliver end-to-end AI solutions, with a focus on responsible AI adoption and “data for good”, ensuring that AI systems create meaningful and positive impact.