Main Street AI

"Main Street AI" is an immersive content series probing the intricate intersection of humanity and artificial intelligence in the world of business and high-stakes industries. Journey with us into stories of challenge and triumph of innovators navigating their unique industry mazes, and of the transformative power of AI seamlessly merging into these narratives. Think of it as "Masters of Scale" but customized for visionaries, pioneers, and enthusiasts in the ever-evolving AI-for-business space.

Main Street AI is a technology podcast hosted by Multimodal, with 97 episodes on record and a Required Pod Score of 80. PitchCentric scores this show on Booking Probability, Listen Score, and live audience signals refreshed every 24 hours.

Multimodal hosts Main Street AI, a technology show with 97 episodes published.

Our AI reads these to draft pitches. Use them as grounding for a pitch that cites a real guest and a specific topic.

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  Main Street AI

  Budgeting for Agentic AI in 2027: What to Ask Every Vendor

  Aug 17, 202627 min

  Ishita Jaiswal, Head of Growth at Multimodal, interviews Ankur Patel, CEO & Founder of Multimodal. Subscribe to the Main Street AI Newsletter: https://multimodal.beehiiv.com/subscribe?utm_source=podcast&utm_medium=description&utm_campaign=podcast Multimodal builds agentic workflows for credit unions and community banks, covering member experience and lending operations. Ankur argues that a 2027 budget has to fund three things at once, an account on one of the big three models for every single person, a hard look at whether your incumbent vendors are opening their software up or walling it off, and a few net new agentic partners, with every vendor pushed to show simulated usage numbers before anyone signs. Guest: Ankur Patel, CEO & Founder, Multimodal Host: Ishita Jaiswal, Head of Growth, Multimodal 0:00 Introduction: Meet Ishita 0:57 The two categories of agentic AI 2:39 Where credit unions start on personal productivity 3:15 Leadership, stewards, and uneven adoption 6:06 Member experience and lending operations 8:12 Why growth beats cost efficiency 9:19 Three pieces of budgeting advice for 2027 13:20 Walled gardens and the SaaS apocalypse 16:19 Usage pricing, tokens, and simulated numbers 20:04 What Multimodal built for credit unions 23:43 The ROI bar and the tuition expense 25:56 Closing

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  Main Street AI

  What Actually Gets AI Buy-In at a Credit Union

  Aug 11, 202637 min

  Ankur Patel interviews Youssi Farag, CFO at WEOKIE Federal Credit Union. Subscribe to the Main Street AI Newsletter: https://multimodal.beehiiv.com/subscribe?utm_source=podcast&utm_medium=description&utm_campaign=podcast WEOKIE Federal Credit Union is a $1.5B institution where Youssi's seat covers finance and accounting, compliance, and commercial lending all at once. Her argument is that AI only sticks when you start from a real problem, put IT, compliance, legal, and the frontline in the same room, and hold vendors to a date instead of accepting "it's on the roadmap." Guest: Youssi Farag, CFO, WEOKIE Federal Credit Union Host: Ankur Patel, CEO & Founder, Multimodal 0:00 Introduction: Meet Youssi 0:44 What Youssi owns at WEOKIE 1:51 Community bank speed vs credit union scale 4:43 How technology decisions actually get made 6:24 Where AI landed first: fraud, risk, and reporting 8:59 Buy, build, or partner 11:39 Budgeting for AI 13:44 Budget discipline with mid-year pivots 16:31 AI in consumer vs commercial lending 19:33 How far along WEOKIE is 21:39 Member-facing AI and measuring what changed 23:35 Vendor green flags and red flags 26:17 Structuring an experiment you can pivot out of 28:51 Reward seeking vs risk mitigation 31:28 Leading vs fast following 33:29 Getting the team bought in 34:45 What success looks like in three years 36:12 Closing

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  Main Street AI

  Why 30 Years of Hard-Won Skills Count for Zero

  Aug 4, 202649 min

  Ankur Patel interviews Kirk Drake, Founder and CEO of CU 2.0. Subscribe to the Main Street AI Newsletter: https://multimodal.beehiiv.com/subscribe?utm_source=podcast&utm_medium=description&utm_campaign=podcast Kirk wrote the AI strategy book for banks and credit unions in 2020, before most of the industry had heard of ChatGPT, then rebuilt CU 2.0 around AI first practices and moved two-thirds of his team onto that work. He argues that 30 years of hard-won PowerPoint, spreadsheet and Word skills now count for zero, that the "we can't put our data near these models" fear is mostly an excuse, and that the AI strategy every credit union is chasing is really just learning how to move faster. Guest: Kirk Drake, Founder and CEO, CU 2.0 Host: Ankur Patel, CEO & Founder, Multimodal 0:00 Introduction: Meet Kirk 1:08 The 2015 talk that started it 6:31 Fintechs vs credit unions 11:49 Why the legacy stack won't port 13:15 30 years of skills at zero 15:09 Why you can't show them the future 18:22 You can't out-exercise your appetite 19:59 Two-thirds of the company on AI work 22:10 Building the impossible in 48 hours 26:09 Opt-in volunteers, not mandates 28:11 Don't hire a VP of AI 31:38 A faster way to learn 36:27 Greenfield prototyping in a day 38:46 If net interest margin drops to 1% 41:50 Skills catalog and workflows 45:10 When IT ships 50x faster 46:28 Closing

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  Main Street AI

  Adopting AI without losing the human connection

  Jul 28, 202645 min

  Ankur Patel interviews LeAnn Case, Chief Strategy Officer at St. Cloud Financial Credit Union. Subscribe to the Main Street AI Newsletter: https://multimodal.beehiiv.com/subscribe?utm_source=podcast&utm_medium=description&utm_campaign=podcast St. Cloud Financial is a $450M central-Minnesota credit union doing things most institutions its size won't touch — cannabis banking, digital asset custody, and a nationwide foundation. LeAnn's argument: adopt AI to strip out the friction (a cannabis business review takes 15 hours to file) and buy back time for members, without sacrificing the human connection that's the whole point of the place. Guest: LeAnn Case, Chief Strategy Officer, St. Cloud Financial Credit Union Host: Ankur Patel, CEO & Founder, Multimodal 0:00 Introduction: Meet LeAnn 1:10 From marketing to strategy 6:36 What is St. Cloud Financial 7:24 A vision built on human connection 8:33 The convenience-vs-connection tension 11:08 Prioritizing AI use cases 13:00 34 fintech pitches, one budget 15:24 Member engagement and support 19:09 The iPhone pace expectation 20:42 Vendors who become partners 23:00 AI is not plug-and-play 25:09 Staff expectations and guardrails 28:01 Leading versus following 30:56 Evidence-backed AI and audit trails 33:00 Competing with the fintechs 37:54 Change management: start with the why 42:26 Signals and risks ahead 44:15 Closing

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  Main Street AI

  The Work Credit Unions Skip Before AI

  Jul 21, 202641 min

  Ankur Patel interviews Adrian Rodriguez, former SVP of Data & Innovation at American Heritage Credit Union, now an independent Data & AI advisor. Subscribe to the Main Street AI Newsletter: https://multimodal.beehiiv.com/subscribe?utm_source=podcast&utm_medium=description&utm_campaign=podcast Adrian built a data and innovation function from the ground up at a credit union that didn't have one, and now advises institutions navigating the same journey for AI. His argument: most credit unions skip the unglamorous foundation work — clean, governed, clearly-defined data — that decides whether AI delivers reproducible answers or just propagates the mess underneath it. Guest: Adrian Rodriguez, former SVP of Data & Innovation, American Heritage Credit Union (now an independent Data & AI advisor) Host: Ankur Patel, CEO & Founder, Multimodal 0:00 Introduction: Meet Adrian 1:06 Technical and operational debt as an anchor 2:38 The agentic AI inflection point 4:11 Standing up a data function from scratch 6:40 Build, hire, or partner 8:09 Why six-month timelines force partnering 12:14 Getting your data house in order first 15:49 The data flywheel 21:46 The next dashboard evolution 27:33 Top-down AI leadership 28:48 What's next: the data and AI journey 30:42 Finding an owner for governance 34:22 Leaders vs laggards 35:50 The cost of AI 39:43 Staying model agnostic 40:32 Closing

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