When XBRL meets AI: Turning compliance into competitive advantage: A conversation with Janis Steinmann, John Turner, and Phil Wilding

In this episode of Finance in Flow, host Janis Steinmann explores how artificial intelligence is transforming the office of the CFO. Joined by John Turner, CEO of XBRL International, and Phil Wilding, AI entrepreneur at HG Capital, the discussion dives into how structured financial data and AI are converging to create conversational analysis tools. Together, they unpack the challenges of making financial workflows AI-ready, the importance of semantic layers and data governance, and why “trust but verify” is the new mantra for AI in finance. From the digital plumbing of XBRL to the future of continuous reporting, this episode reveals how CFOs can turn data into a true competitive advantage.About the guests:John Turner is the CEO of XBRL International. John is responsible for enhancing the standards and supporting the adoption of XII globally. Throughout his career, he has been focused on improving business reporting and analytics. He has been a leading member of the XBRL community since 2001, when it was founded. John holds a degree in IT and government and an LLB in Law from the University of Queensland, Australia.Phil Wilding is an AI Entrepreneur at Hg. Phil is an AI entrepreneur and technology leader currently advising companies on how to adopt an AI-native posture and successfully bring AI projects into production. He serves as CPTO at Localised.com and the Co-Founder of Future Moto, building a network of electric motorbike parks and leading a race team that took 1st, 2nd, and 3rd place in its first National Electric Flat Track Championship season. Phil has spent his career building and scaling online businesses that merge technology, data, and user experience to drive growth and innovation.  Key Quotes“Stop treating your digital disclosures like homework. Start treating them like your company’s voice in a conversation with every AI on the planet — because that conversation has already started.”– John Turner“Clean numbers alone don’t tell the story — they lack the context that human analysts hold. For data to be truly AI-ready, you need a well-defined semantic layer.” – Phil Wilding “AI doesn’t magically fix bad data — it just amplifies it at scale. So who’s ultimately responsible for data quality? The CFO, the auditor, or the regulator?” – Janis Steinmann Time Stamps00:00:36 – Guest Introduction: John Turner, CEO of XBRL International00:02:36 – Guest Introduction: Phil Wilding, AI Entrepreneur at Hg00:04:11 – What Is XBRL?00:05:57 – Why Financial Data Is Challenging for AI00:08:31 – Making Structured Data AI-Ready00:11:57 – The Limits of Large Language Models00:14:55 – Building the Semantic Layer00:18:07 – Conversational Financial Analysis in Practice00:21:40 – Trust but Verify: Ensuring Accuracy00:25:58 – Cross-Company Insights and AI Potential00:27:57 – Governance and Data Quality00:31:03 – Risks of Poor Data and Black Box AI00:35:06 – Who Owns Data Quality?00:39:10 – Quick Fire Questions with Phil Wilding00:42:24 – Quick Fire Questions with John Turner00:45:49 – The Future of Financial Reporting00:48:12 – Key Takeaways & Closing ThoughtsLinksConnect with John on LinkedInConnect with Phil on LinkedInLearn more about Lucanet Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.