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Most AI projects don't fail because of the model. They fail because organisations don't trust the data.In this special live edition of the London Fintech Podcast, recorded from Money20/20 Europe in Amsterdam, Tony Clark sits down with Remco den Heijer, Vice President APJ & EMEA Channels at Alteryx, to explore why data readiness has become the defining challenge in enterprise AI adoption.As organisations move from AI experimentation to real-world deployment, the conversation is shifting away from models and prompts towards trust, governance, and operational execution. Remco explains why AI success depends not on having the latest model, but on having data that is visible, understandable, repeatable, and auditable.Drawing on experience working with some of the world's largest enterprises, Remco shares how organisations are modernising legacy processes, replacing spreadsheet-driven workflows, and creating the foundations required for AI to deliver measurable business outcomes.The discussion explores agentic AI, enterprise automation, regulatory expectations, and the infrastructure needed to support AI at scale. They also examine how businesses are using governed workflows to bridge the gap between raw data and trusted decision-making.Beyond technology, the conversation covers leadership, ecosystem partnerships, global perspectives on AI adoption, and why organisations that treat data as a strategic asset are emerging as the winners in the AI era.Whether you're a data leader, fintech operator, AI practitioner, or executive responsible for transformation, this episode offers practical insight into what it really takes to become AI-ready.📌 Topics covered:• Why most AI projects fail despite advances in AI models• What "AI-ready data" actually means• The VURA framework: Visible, Understandable, Repeatable, Auditable• Data governance, trust, and the EU AI Act• Agentic AI and governed workflows• How Alteryx powers enterprise-scale automation• The role of data infrastructure in AI adoption• Why businesses run on workflows, not prompts• AI readiness across Europe, Asia, and North America• Lessons from investing in startups and scaling technology businesses🔗 Learn more:Tony Clark: https://www.linkedin.com/in/tclark100/Remco den Heijer: https://nl.linkedin.com/in/remcodenheijerAlteryx: https://www.alteryx.com/platformNextWave Consulting: https://www.nxwave.com/NextWave Alteryx Knowledge Hub: https://resources.nxwave.com/hub/nxw-alteryx-hubFree Alteryx License: https://www.alteryx.com/trial/workflow-automation?prid=0033n00002qVAafAAG&crp=0033n00002qVAafAAG&apid=0012R00002DwbwTQARAlteryx Training Courses: https://www.nxwave.com/alteryx-trainingGo Beyond the Podcast: https://resources.nxwave.com/hub/london-fintech-podcast
By Tony Clark4.7
99 ratings
Most AI projects don't fail because of the model. They fail because organisations don't trust the data.In this special live edition of the London Fintech Podcast, recorded from Money20/20 Europe in Amsterdam, Tony Clark sits down with Remco den Heijer, Vice President APJ & EMEA Channels at Alteryx, to explore why data readiness has become the defining challenge in enterprise AI adoption.As organisations move from AI experimentation to real-world deployment, the conversation is shifting away from models and prompts towards trust, governance, and operational execution. Remco explains why AI success depends not on having the latest model, but on having data that is visible, understandable, repeatable, and auditable.Drawing on experience working with some of the world's largest enterprises, Remco shares how organisations are modernising legacy processes, replacing spreadsheet-driven workflows, and creating the foundations required for AI to deliver measurable business outcomes.The discussion explores agentic AI, enterprise automation, regulatory expectations, and the infrastructure needed to support AI at scale. They also examine how businesses are using governed workflows to bridge the gap between raw data and trusted decision-making.Beyond technology, the conversation covers leadership, ecosystem partnerships, global perspectives on AI adoption, and why organisations that treat data as a strategic asset are emerging as the winners in the AI era.Whether you're a data leader, fintech operator, AI practitioner, or executive responsible for transformation, this episode offers practical insight into what it really takes to become AI-ready.📌 Topics covered:• Why most AI projects fail despite advances in AI models• What "AI-ready data" actually means• The VURA framework: Visible, Understandable, Repeatable, Auditable• Data governance, trust, and the EU AI Act• Agentic AI and governed workflows• How Alteryx powers enterprise-scale automation• The role of data infrastructure in AI adoption• Why businesses run on workflows, not prompts• AI readiness across Europe, Asia, and North America• Lessons from investing in startups and scaling technology businesses🔗 Learn more:Tony Clark: https://www.linkedin.com/in/tclark100/Remco den Heijer: https://nl.linkedin.com/in/remcodenheijerAlteryx: https://www.alteryx.com/platformNextWave Consulting: https://www.nxwave.com/NextWave Alteryx Knowledge Hub: https://resources.nxwave.com/hub/nxw-alteryx-hubFree Alteryx License: https://www.alteryx.com/trial/workflow-automation?prid=0033n00002qVAafAAG&crp=0033n00002qVAafAAG&apid=0012R00002DwbwTQARAlteryx Training Courses: https://www.nxwave.com/alteryx-trainingGo Beyond the Podcast: https://resources.nxwave.com/hub/london-fintech-podcast

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