by Harnham & Rockborne
This podcast will cover a range of topics such as finding data talent, and AI training. We will also discuss more advanced subjects like assessing the value of your data team, identifying biases in AI and addressing pay gaps in data and analytics. See more on our website: https://www.harnham.com/data-and-ai-podcast/
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Publishing Since
6/6/2023
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May 22, 2026
"It's not 'don't do,' it's 'how to.'" James Robson, Founder of Datum Longevitus and former Data Protection Officer for the Labour Party reveals how organisations can use data protection to speed up AI rollouts rather than slow them down. In this Data & AI Podcast conversation with Waseem Ali, they talk about: Why DPOs need to be involved at the start of projects, and how to bring the wider business with you What organisations get wrong when rolling out Copilot and other LLM tools The ethics of automated decision-making and what transparency actually requires Why "human in the loop" still matters in AI-driven decision-making How poor AI configuration creates unnecessary data and IP risk Waseem and James also explore real examples shaping the future of AI governance, including the Labour Party's data environment, the Housing Helper homelessness chatbot used by local councils, and the facial recognition platform PIM Eyes. The episode closes with James's view on what's next: trusted data intermediaries that let organisations share data compliantly, and could reshape the AI tools built on top of it. Plenty to take away for anyone working out where AI compliance ends and AI innovation begins.Subscribe to the Data & AI Podcast for more conversations on data, AI, and the future of work. If you found this useful, share it with someone navigating their own AI compliance work, or visit harnham.com to find out how we support data and AI hiring across the UK and US.
January 9, 2026
In this episode of Harnham’s Data & AI Podcast, Harnham CEO Dave Farmer speaks with Rockborne CEO Waseem Ali about one of the biggest challenges facing organisations today: closing the data and AI skills gap while building a culture that uses data in everyday decision making. Waseem explains why the gap is often misunderstood. Many companies focus on technical hiring or new tools, but the real issue is confidence and capability across the wider business. People need to understand how data helps them make better decisions, not just how a platform works. That shift takes leadership focus, clear communication and continuous learning, not one-off training sessions. The conversation breaks down: How organisations can combine upskilling, coaching and literacy programmes to build capability at scale. Why celebrating early wins and visible examples creates momentum and buy-in. How leaders can balance hiring specialist talent with developing the people they already have. What happens when centralised teams try to hold everything, and why federated decision-making often speeds up impact. Real lessons from clients who improved decision-making and adoption by focusing on communication, context and consistent leadership support. Waseem also looks ahead at how AI is changing expectations of data teams. Coding remains important, but problem framing, critical thinking and asking better questions are becoming central skills as automation improves. He closes with practical steps leaders can take today: get clear on the decisions that matter, train executives first, remove friction around data access and spend time listening to the business before rolling out solutions.Subscribe for more conversations with data and AI leaders, and explore the full series at harnham.com.
October 2, 2025
This week on Harnham’s Data & AI Podcast, Senior Growth Manager Jayme Oshaben is joined by Ashish Bansal, founder of StarSpark.AI and former Google leader, for a grounded look at where generative AI is really heading. Ashish reflects on the breakthroughs that brought us here: from seq2seq models to Transformers and self-supervised learning, and why cost, scale and reliability still determine which ideas make it into production. He explains the common stumbling block teams face with GenAI: it’s easy to get to a promising proof of concept, but closing the gap to a production-ready system demands stronger engineering, cleaner data, and a clear product mindset. The conversation looks ahead to what’s next: Smarter, in-product support that avoids the “please hold” loop. AI and robotics shifting from virtual experiments to physical tasks. Education reimagined with affordable tutors that encourage curiosity. Why GenAI is probabilistic, not deterministic, and why that matters. On skills, Ashish is direct: embrace new tools, but go beyond them. The advantage now lies in pairing technical depth with communication, product sense, and a growth mindset.As founder of StarSpark, the first AI math teacher designed for K–12 mastery, Ashish shares how education can be transformed. StarSpark uniquely combines alignment with state standards, adaptive grade-level progression, and 100% solving accuracy with personalized, proactive teaching that no other platform delivers. Whether you’re testing your first agent, scaling a platform, or planning your next role, this episode offers a clear-eyed view on turning GenAI from demo into lasting value.
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Chris Gibbins
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This podcast will cover a range of topics such as finding data talent, and AI training. We will also discuss more advanced subjects like assessing the value of your data team, identifying biases in AI and addressing pay gaps in data and analytics.
See more on our website: https://www.harnham.com/data-and-ai-podcast/
This podcast updates bi-weekly.
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