AI-Driven Marketer podcast
Browse the complete archive of practical conversations and experiments for marketers building with AI.
Episode archive
Page 14 of 18
A practical look at combining a CRM journey builder with OpenAI to turn podcast source material into consistent newsletter drafts and automated campaigns that can be reviewed and improved.
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Audra Carpenter and I discuss connecting AI to marketing automation, using existing podcast content, clearer prompts, and review checkpoints to create repeatable workflows.
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Noz Urbina and I unpack generative AI's creative power, hallucinations, context, knowledge graphs, and the process that helps marketers use new tools responsibly.
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Dan explains the move from solo consulting and podcasting toward an AI agency built around practical content systems, client bottlenecks, and original points of view.
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Lee-Ann Scott shares a podcast-in-a-box workflow that uses custom GPTs, automated outreach, AI clipping, and fewer handoffs while protecting time for strategic thinking.
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The future of AI marketing is uncertain, but the next step is clear: master transferable fundamentals, test real workflows, and learn early enough to lead the people around you.
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An AI strategy connects a business objective to a measured workflow, a responsible owner, and adoption support so experiments can become useful operating systems.
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Harrison Painter shares a practical view of AI adoption, from the role of a non-technical chief AI officer to the human creativity and emotional intelligence teams still need.
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The ChatGPT desktop app made it easier to speak a rough request, transcribe it, and get useful help without writing a long prompt first.
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Mark Fidelman and Dan Sanchez discuss the gap between AI hype and adoption, practical marketing workflows, and why human judgment and trust matter as synthetic media improves.
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A working taxonomy gives AI marketing structure. Categorize the work, test each area against business goals, and revise the map as the technology evolves and new capabilities emerge.
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Gen Furukawa and I discuss learning from practitioners, repurposing original content, using data analysis, and building a practical AI stack for small marketing teams.
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