AI in Marketing: Unpacked: Daily Summaries Delivered

Let the AI Find the Opportunity. Let the Agent Make the Call.

Most AI gets bought first and pointed at work later. Anna Patrick, Vice President of Sales Enablement and Technology Adoption at Integrity, starts from the other end: which work should an insurance agent never have to do by hand again?Anna explains how Integrity decides what goes into IntegrityCONNECT, why manual entry is the first thing agents stop doing, how AI call summaries protect agents in an audit and coach them afterward, and why client health information stays out of open AI tools. She's just as clear about what never moves: the recommendation and the follow-up stay with the agent, because the agent knows the client best.Take the AI Opportunity Score: Your Next Steps | The AI HatShow notes and full transcript: https://theaihat.com/what-insurance-agents-should-never-do-by-hand/ Find out where your team’s week goes: take the free AI Opportunity Score at TheAIHat.com/ai-opportunity-scoreConnect with Mike, AI Keynote Speaker & Trainer: linkedin.com/in/mikeallton Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

The AI Demo Looked Great. Then Real Users Showed Up.

Someone on your team is already using an AI tool nobody approved. And the next vendor demo you sit through will look great whether or not the product holds up on your data.Stella Liu, Head of AI Applied Science and Lead Data Scientist in ASU's AI Acceleration group, joins Mike Allton to explain why traditional software testing leaves gaps with generative AI. The same prompt can give a different answer every time, so a product that passed a builder's quick check can miss the edge cases real users hit on day one.In this episode:The three things Stella evaluates: performance, quality and safetyWhy a polished demo tells you little about real useThe vendor who never asks about your data, and other red flagsThe first question to put to any AI vendorWhat to add to your procurement checklistPersonal vs enterprise AI accounts, and where your team's data can end upConnect with StellaLinkedIn: https://www.linkedin.com/in/wenxingl/Data Science x AI newsletter: https://datasciencexai.substack.comAI Evals and Analytics course on Maven: https://maven.com/ai-evals-and-analytics/ai-evals-analytics-playbookMentioned: Shadow AI - https://theaihat.com/shadow-aiTake the AI Opportunity Score: https://theaihat.com/ai-opportunity-score/Watch on YouTube: https://youtu.be/0cKSJOtBASs Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Why AI Automation Fails (And What To Fix First) with Ty Givens

You Bought the AI. Why Is the Day Longer?

Count the tabs it takes to move one renewal. Management system, carrier portal, the other carrier portal, quoting platform, email, Teams, back to the CRM, then a spreadsheet. That is eight, and not one of them is the conversation with the client. Nobody designed it that way. Nobody approved it. And you are paying your most expensive person to do it. In this solo episode, Mike Allton makes the case that the most expensive piece of integration software in your agency is a licensed producer, and that the AI you bought last year did not shorten that list. It lengthened it, and the new switches cost more than the old ones, because every one of them makes you rebuild your context out loud. Then he gives you the fix, in three steps you can run Monday morning without spending a dollar: Count, Name, Seat. Count the switches in one recurring job. Name the one where the most context has to get rebuilt from nothing, which is almost never the one that annoys you. Then give that context a seat to live in, using the three shapes of a Digital Crew: Scout, Scribe, and Coach. Also in this episode: why memory features do not solve this, the switchboard operator who kept getting better boards instead of a better question, how one benefits manager in Utah stopped being the cable between his carriers, the three rails to set before any client data goes near an AI tool, and the four objections Mike hears in every room. The wedge is the same as always. Redesign the work before you deploy AI. Take the AI Adoption Reality Check: https://theaihat.com/reality-check/ Read the companion piece on the Toggle Tax: https://theaihat.com/what-is-the-toggle-tax/ Show notes: https://theaihat.com/how-to-increase-insurance-agent-productivity-without-buying-another-tool/ Connect with Mike: https://www.linkedin.com/in/mikeallton/

AI Belongs on Your Org Chart, Not Your Tech Stack

Your best people are losing most of the week to work they were never hired to do - and the fix isn't another tool. In this solo episode, Mike Allton opens with a confession: there was a stretch of his career when a guest canceling on his own podcast felt like relief. Two of his shows died at exactly twelve episodes each, and between those funerals he changed everything - the tools, the format, the frequency, the topic - except the one variable that killed them both. That story turns out not to be a podcasting story at all. It's the same reason 95% of enterprise AI pilots fail: companies make a software purchase when the situation calls for a staffing decision. Nobody writes the role. Nobody defines what the AI is responsible for, who it reports to, or how anyone would know it's doing a good job. So Mike makes the argument he's building his entire business around: AI belongs on your org chart, not your tech stack. Not to replace the people you have - to finally staff the work no one was ever hired to do. You'll hear: - Why every business runs on two org charts - the official one, and the real one hiding in your team's calendars - The job description that took interview prep from two-plus hours to twenty minutes, and took the show past 120 episodes - The Apollo answer to "this is how the replacement starts" - Why an off-the-shelf AI employee is still a software purchase wearing a name tag - A ten-minute homework assignment: find the seat that's been empty the longest Read the full manifesto at theaihat.com: https://theaihat.com/ai-belongs-on-your-org-chart-not-your-tech-stack/ Learn more about your ad choices. Visit megaphone.fm/adchoices

Stop Losing $30K a Month Per Rep: The AI Sales Enablement Playbook with Vernon Ross

If your top reps are stuck training new hires instead of closing deals, this AI sales enablement playbook will help. Enterprise seller Vernon Ross joins Mike Allton to show how to scale your best performers' knowledge without stealing their selling time, and why that "teaching jail" is quietly costing you around $30K a month per rep. Vernon has carried quota, closed enterprise deals, and built the AI training tools that make other sellers faster. Inside, he shares the one diagnostic question that finds your highest-ROI automation, why AI pilots die the moment they add friction instead of removing it, and how he uses NotebookLM, private podcasts, and voice cloning to cut top-rep onboarding from 30 hours down to 10. He and Mike also get tactical on where AI belongs inside a MEDDPICC deal, how to tie content consumption to real revenue, and the one automation any team can build this quarter without a six-figure budget. Vernon Ross drove 75 to 85% increases in new client acquisition at a 32% conversion rate, closed deals with Procter & Gamble, GE, and AT&T, and has generated over $500,000 in enterprise SaaS sales. As president of Vernon Ross Consulting and an enterprise podcaster, he now advises Fortune 1000 companies on AI-driven learning. The hard truth: you cannot clone your top performers. So you stay stuck in an endless loop of manual knowledge transfer while your competitors build AI-powered learning engines that run around the clock. This episode is how you break the loop. Still letting shadow AI run unmanaged on your sales floor? Download the free Executive Guide to Shadow AI at theaihat.com/shadow-ai. Chapters: 00:00 Top Rep Pain Points 00:59 Podcast Theme Intro 02:08 Show Mission Setup 03:15 Guest Vernon Ross 05:11 Sales Enablement Gap 07:34 AI Adoption That Sticks 10:58 AI Hosted Training Podcasts 13:46 NotebookLM And Voice Clones 16:28 MEDDPICC With AI 18:52 Onboarding Without Teaching Jail 21:25 Shadow AI Sponsor Break 22:33 Measuring Podcast ROI 28:38 Fast Time To Value 30:37 Compliance And Risk 33:48 First Automation To Build 36:34 Where To Find Vernon 37:18 Final Wrap Up Resources: Vernon Ross: linkedin.com/in/vernonross | vernonross.com | enterprisepodcaster.com | aiplanner.com Mentioned in this episode: Wondercraft.ai, Google NotebookLM, Wispr Flow, ZoomInfo, Apollo, HubSpot, Otter.ai, Claude Code, Gemini, Supporting Cast, MEDDPICC Connect with Mike Allton: linkedin.com/in/mikeallton | Newsletter theaihat.com/newsletter | Podcast theaihat.com/podcast Learn more about your ad choices. Visit megaphone.fm/adchoices

Your AI Stack is Broken: A Revenue Leader's Framework for Success with Dan Knowlton

Your revenue team doesn't have a tools problem. It has a process problem. Dan Knowlton, co-founder of UK-based Knowlton Marketing, joins Mike Allton for an honest, boots-on-the-ground conversation about what's actually working in AI implementation - and what isn't. No polished frameworks. No hype. Just real lessons from an agency owner who is figuring this out in real time while growing a business. In this episode, Dan shares how his team recently won a pitch with one of Europe's largest health and wellness brands - not because they were the most creative, but because AI caught every objection the prospect raised in the discovery call. Objections that would have been missed with manual notes. You'll learn how to stop chasing shiny AI tools and start asking the one question that separates useful technology from expensive distraction. Dan also breaks down how to identify which workflows should be handed to AI, where human experience is irreplaceable, and how to run a simple calendar audit that surfaces hours of recoverable time in your team's week. If your AI pilots keep stalling, this episode will show you why - and where to start instead. 🎁 Download the free Executive Guide to Shadow AI: https://theaihat.com/shadow-ai CHAPTERS: 00:00 Manual Sales Discovery 01:00 Podcast Theme Intro 02:31 Why AI Pilots Fail 03:46 Shiny Tool Syndrome 05:29 Problem First Approach 06:05 AI-Powered Pitching 07:24 Transcripts Close Deals 10:05 Where AI Shouldn't Pretend 13:59 Humans Plus AI Creativity 16:47 Overcoming Team Pushback 19:42 Shadow AI Governance Ad 20:56 Tool Stack and Evaluation 27:06 Making Time for AI Learning 29:25 Workflow Audit to Start 32:19 Wrap Up and Where to Connect 33:18 Final Outro Learn more about your ad choices. Visit megaphone.fm/adchoices

Revenue Architecture 101: How to Build GTM Systems That Scale Without Breaking

If your revenue team is hitting a ceiling despite adding headcount and new tools, the problem isn't your people - it's your architecture. In this episode, Mike Allton sits down with Amanda Rubin, SVP of Revenue at Frameplay and former EVP of Growth at Enthusiast Gaming, where she drove four consecutive years of revenue growth. Amanda unpacks what she calls the "architect's mindset" - the long-view, systems-first approach that separates true Revenue Leaders from sales managers who are simply trying to hit this quarter's number. You'll hear how Amanda built scalable GTM frameworks from the ground up - first with nothing but a color-coded Google Sheet, and now with an AI-powered tech stack that eliminates admin drag and gives sellers back the time they need to actually sell. She breaks down exactly how she structures account lists, ladders sales teams, and deploys tools like We Flow, Fyxer AI, and Apollo to create a revenue engine that scales without breaking. What you'll walk away with: Why the difference between a Sales Leader and a Revenue Leader changes everything about how you build your org How to structure account tiers so no opportunity falls through the cracks The AI tech stack Amanda is architecting right now at Frameplay - and the honest truth about what it takes to implement it Connect with Amanda Rubin: LinkedIn Resources mentioned: We Flow - AI-powered activity tracking and pipeline intelligence Fyxer AI - AI email organization and post-meeting draft automation Apollo - Sales sequencing and outreach automation Download the free Executive Guide to Shadow AI: theaihat.com/shadow-ai CHAPTERS: 00:00 Meeting Follow Up Basics 00:23 Podcast Intro Theme 01:32 Welcome and Mission 01:56 Scaling Chaos Problem 02:33 Meet Amanda Rubin 04:05 Sales vs Revenue Leadership 05:53 Revenue Architect Mindset 07:07 GTM Narrative and Positioning 08:01 Designing the Sales Org 10:21 Frameworks That Break 11:14 Account Lists and CRM Discipline 12:44 Tiering and Activity Tracking 13:36 People Roles and Incentives 15:18 Enthusiast Gaming Playbook 17:29 Packaging and Storytelling 19:41 Building Seller Pods 22:07 Diagnosing Capacity Leaks 23:27 Support vs Sales Spend 24:29 AI for Spec Sheets 24:52 Wildfire GPT Brain 25:59 Shadow AI Governance 27:15 Fix Workflows First 27:42 WeFlow Setup and CRM 30:51 Conference Intelligence Dashboards 33:33 Fyxer Inbox and Followups 35:09 Apollo Sequences and Outreach 36:37 Frameplay Pitch and Audience 39:06 WeFlow Activity Warnings 41:25 Fail Fast Tool Decisions 42:56 Story Before Headcount 44:01 Connect on LinkedIn 44:42 Final Shadow AI Reminder Learn more about your ad choices. Visit megaphone.fm/adchoices