GTM AI Podcast with Coach K and Jonathan Moss

www.aibusinessnetwork.ai www.gtmaipodcast.com www.gtmaiacademy.com https://www.linkedin.com/in/kenbabcock/ https://www.tango.ai/ Ken Babcock, CEO of Tango, reveals how AI is solving sales teams' biggest pain point: administrative work that keeps reps away from selling. With 2M+ users and partnerships with Walmart and Nike, Tango evolved from documentation tool to AI automation platform. The CRM Problem: Sales reps spend 70%+ time on admin instead of customer-facing activities. "No one ever hired a sales rep because of how good they were with the CRM," Babcock notes. Speed 60 Method: Tango's approach compresses post-call work into 15-minute blocks: 45 minutes customer interaction, 10 minutes CRM updates, 5 minutes prep for next call. Trust Through Transparency: Unlike "black box" AI tools, successful automation requires human oversight and real-time visibility into processes. Competitive Advantage: Quick follow-up wins deals. One prospect told Babcock: "I forgot all those vendor conversations. The one that emailed me? I'm going with them." Start AI implementation with specific pain points like CRM updates Maintain human validation to build trust in automated processes Use data to identify low-adoption workflows for automation opportunities Quick response times after prospect meetings create momentum Build learning-oriented culture with regular career development conversations Focus on behaviors, not just values, when establishing company culture Tango's journey shows that successful AI adoption comes from solving real user problems while keeping humans in control of the process. Sales Reps Don't Wake Up Excited About CRM Updates: How AI Is Finally Fixing the Administrative NightmareKey InsightsMain Takeaways

www.gtmaipodcast.com www.aibusinessnetwork.ai www.gtmaiacademy.com Summary Ross Rich, CEO and co-founder of Accord, brings a unique perspective to sales technology after scaling Stripe's sales organization from three to 300 people. In this conversation from GoNimbly's RevFest, Rich reveals how execution excellence goes beyond doing more work to creating clarity, consistency, and reinforcing winning behaviors across the customer journey. The foundation of execution excellence starts with data and knowing exactly who you're talking to. Rich emphasizes that most sales teams fail because they engage with associates and below-the-line people rather than senior stakeholders and decision makers. At Accord, they track both the number of stakeholders and the frequency of engagement as primary indicators of deal health. This focus on stakeholder mapping becomes even more critical as buying committees expand and decisions require broader consensus. AI represents both an opportunity and a threat for sales professionals. The technology can handle transactional SMB deals, pushing human sellers toward more complex mid-market and enterprise opportunities. However, this concentration means top performers who previously closed one or two deals annually might now close three to five, potentially increasing the revenue contribution of the top 20% of sellers from 80% to 90% or more. Those at the bottom who rely on lucky breaks or helpful buyers will find their roles increasingly challenged by technology. The practical application of AI in sales focuses on two key areas. First, deep research that previously required hours of manual work analyzing 10-Ks, financial statements, and stakeholder backgrounds can now happen in seconds. This allows thoughtful sellers to craft more informed outreach and stand out from the noise. Second, AI helps identify and engage the right senior stakeholders with relevant messages. Counterintuitively, Rich finds higher response rates when reaching out to more senior executives because thoughtful, informed messages stand out more in a CEO's inbox than in a mid-level manager's cluttered email. The implementation of AI tools must meet sellers where they already work rather than asking them to become prompt engineers. Rich points out that if revenue operations leaders struggle to get representatives to input data into Salesforce, expecting them to master AI prompting is unrealistic. Instead, AI should be embedded into existing workflows like account research, stakeholder mapping, and business case development. This approach eliminates the need for additional tabs, tools, or manual updates while enhancing the work sellers already do.

www.gtmaipodcast www.aibusinessnetwork.ai www.gtmaiacademy.com https://www.getpeel.ai/ https://www.linkedin.com/in/brannon-santos/ The Genesis Story Brannon Santos brings a unique perspective as a founder - he's not a technologist who stumbled into sales problems, but a seasoned sales leader who deliberately chose entrepreneurship. His background includes choosing his college specifically for its entrepreneurship program and strategically entering sales to understand how businesses operate from the inside out. This sales-first DNA permeates Peel's entire approach. The conversation reveals a painful truth about modern B2B sales: the process is riddled with friction. Santos shares a perfect example - a CMO who hasn't spoken to a salesperson in 15 years because her calendar is perpetually full, yet she researches solutions at 11 PM when sales teams are offline. This temporal mismatch between when buyers want to engage and when sellers are available represents billions in lost opportunity. Peel positions itself as a "voice AI layer" that creates intelligent, conversational agents for brands. But this isn't your typical chatbot - these agents can: Conduct full discovery calls in 5 minutes instead of 30-45 minutes Generate detailed "tear sheets" formatted to match specific sales methodologies Create automated "Peel Rooms" (similar to deal rooms) with all conversation insights Enable stakeholders to have the same conversation asynchronously One of the most compelling use cases Santos demonstrates is Peel's ability to conduct mass qualitative research. A marketing agency used Peel to interview 38 sales professionals about lead quality, creating a study called "Do My Leads Really Suck?" What traditionally costs thousands of dollars and takes months can now be done in a day, with results that update in real-time as more participants engage. Santos reveals how Peel uses the Winning by Design bow tie framework, allowing companies to deploy conversational agents at every stage of the customer journey - from awareness through renewal. This strategic approach ensures conversations are contextually appropriate whether someone is just discovering the brand or negotiating renewal terms. The discussion unveils key insights for training conversational AI: Start with easy, closed-ended questions Include personal questions early (people enjoy talking about themselves) Focus on present challenges and near-term goals Build dynamically based on responses Santos predicts that within a year, the entire enterprise sales cycle could theoretically be handled by AI agents. He envisions a world of "agent-to-agent" commerce where your personal AI assistant negotiates with vendor AI assistants on your behalf. While acknowledging human relationship-building will remain important, he sees AI eliminating the mechanical, repetitive aspects of sales.

www.gtmaipodcast.com www.aibusinessnetwork.ai www.gtmaiacademy.com https://www.linkedin.com/in/anuraggoel2/ The Hidden Crisis: Why Your AI Investment Is Probably Failing (And How to Fix It) If you're like most executives diving into AI, you're doing it wrong. Dead wrong. And the numbers prove it. In this week's explosive episode of the Go to Market AI podcast, enterprise transformation expert Anurag Goel (Red Hat, Salesforce, Adobe) drops a truth bomb that should terrify every C-suite executive: 88% of AI pilots never make it to production. But here's the kicker – he also reveals exactly how his team turned a simple POC into a $5 million value driver. The Problem Nobody Wants to Admit Let's start with the uncomfortable truth. While everyone's racing to implement AI tools, Goel exposes the fundamental flaw in most approaches: "AI founders are so passionate about what they have built... they jump to the shiny object. Look at the features that my technology has. It's so cool. Guess what? Executive buyers don't care." This isn't just philosophical musing. BCG's research backs it up – 68% of AI pilots fail to scale because companies skip the critical step of defining clear objectives and success metrics. They're essentially burning money on technology theater. The Strategic Framework That Changes Everything Goel's approach flips the script entirely. Instead of starting with tools (the mistake 90% of companies make), he advocates for a three-phase transformation framework: Phase 1: Problem Archaeology Dig past symptoms to find root causes Map the actual business process (not the idealized version) Identify where value is being destroyed, not just where AI could be added Phase 2: The Hypothesis-Led Discovery This is where things get interesting. Rather than running blind pilots, Goel's team creates what he calls a "hypothesis business case" BEFORE touching any technology. In the energy company example he shares, they identified a million-dollar opportunity in incident resolution time – then exceeded it by 10% during the pilot. Phase 3: Power Dynamics Navigation Here's the brutal reality: Your POC champion isn't your buyer. Goel emphasizes the critical transition from "proof of concept" to "proof of value" – packaging results in a way that speaks to economic buyers who control budgets.

www.aibusinessnetwork.ai www.gtmaiacademy.com https://theaihat.com/podcast/ https://www.linkedin.com/in/mikeallton/ Just wrapped up an incredible conversation with Mike Alton, Chief Storyteller at Agorapulse, and my mind is still buzzing from all the AI gold he dropped. If you're feeling overwhelmed by AI or wondering how to actually use it in your day-to-day work, this one's for you. Here's what struck me most about Mike: he's a coder who speaks human. After 20+ years in digital marketing and a computer science background, he's become what I call a "translator" - someone who can take complex AI concepts and make them click for regular folks like us. Mike discovered something fascinating when he asked AI to analyze him based on their conversations. It identified his superpower: bridging the gap between highly technical concepts and simple, practical applications. And honestly? That's exactly what we need more of in the AI space. One of the biggest takeaways was Mike's RICC prompting framework. Here's the breakdown: R - Role: Tell the AI who it needs to be I - Instructions: What you want to accomplish C - Context: All the relevant background info C - Constraints: Any limitations or specific requirements But here's the kicker - Mike always adds "Take your time. Ask me whatever questions you need before we move on." This simple addition transforms AI from a one-way output machine into an actual collaborative partner. During our chat, I asked Mike about the small tweaks that make big differences. Beyond just using a framework, here's what moves the needle: Chain Prompting: Instead of asking for a finished product, break it down. For a blog post, start with topic ideas, then outline, then headline, then content. Each step builds on the last. Let AI Ask Questions: Most people don't realize AI won't push back unless you tell it to. Give it permission to clarify, and watch your outputs improve dramatically. Specific Use Cases: The magic happens when you show someone exactly how AI solves THEIR specific problem, not generic examples. The Bridge Between Tech and RealityThe RICC Framework That Changes EverythingThe 20% Game-ChangersReal-World Magic in ActionThe Creativity Factor That Blew My MindThe Agent Revolution Is HereThe Mindset Shift for Leaders and DoersMy Personal TakeawaysYour Next Steps

Part 2: Building Autonomous Businesses with AI Agents (Jonathan Moss Interview)Podcast Description Jonathan Moss welcomes Amos Bar Joseph, co-founder and CEO of Swan AI (getswan.ai), for a strategic discussion on the autonomous business model that's challenging Silicon Valley's traditional playbook. Having built and sold multiple startups, Amos explains why he's now focused on reaching $30M ARR with just three founders using AI agents. This episode covers the philosophical framework behind autonomous businesses, detailed breakdowns of Swan's agentic technology, and exclusive announcements about new tools that democratize access to AI-powered go-to-market strategies. 99% of companies fail chasing funding rounds Focus shifts from value creation to "valuation inflation" Building for investors rather than customers "These types of companies, they don't pursue value creation, but what they are actually focused is valuation inflation." "It's not the fault of the founders I've been there myself. It's just that it's kinda like the natural tendency of building for the next round all the time." Website: getswan.ai LinkedIn: https://www.linkedin.com/in/amos-bar-joseph/

Part 1: The Autonomous Business Revolution with Amos Bar Joseph (Coach K Interview)Podcast Description Join Coach K (Jonathan Kvarfordt) for an energetic conversation with his friend Amos Bar Joseph, CEO of Swan AI (getswan.ai), who's rewriting the startup playbook by building to $30M ARR with just three founders and AI agents. After burning out on the traditional "unicorn playbook" through two successful exits, Amos shares his revolutionary approach to scaling with intelligence instead of headcount. This episode features a deep dive into Swan's actual AI agent ecosystem, controversial takes on popular GTM tools, and a practical framework for implementing AI in any business. Companies focus on "valuation inflation" over value creation The VC route makes founders forget customers and employees Building on "sick foundations" by scaling before product-market fit "I'm sick of the unicorn playbook... It hasn't changed for the last 15 years. It's outdated, it's not relevant for 2025." "They forget about their customers. They forget about their employees, they forget about how to build a company." AI will create MORE jobs, not fewer Hundreds of thousands of new autonomous businesses will emerge SMBs can now compete at enterprise scale "A three person team could achieve what took a 1000 team before that." Website: getswan.ai Connect: https://www.linkedin.com/in/amos-bar-joseph/

www.aibusinessnetwork.ai www.gtmaiacademy.com www.gtmaipodcast.com https://www.linkedin.com/in/tasleem1/ Tas Newsletter: https://www.linkedin.com/newsletters/7245478675247173632/?displayConfirmation=true The Experiment That Exposed Everything When Tas Hirani, a veteran enablement leader with a Six Sigma background from GE, noticed her sales teams struggling despite having access to cutting-edge AI tools, she did something radical. She didn't run another survey or schedule more training sessions. Instead, she went undercover as a sales rep while maintaining her enablement role. What she discovered explains why companies are spending millions on AI tools that collect dust while reps continue drowning in admin work. The Brutal Truth About Sales AI Adoption "Everyone's got LinkedIn, LinkedIn Navigator, ChatGPT, Perplexity... but when I actually sat in the seat and tried to use these tools the way reps do, it was Pandora's box," Hirani reveals. The problem isn't the technology—it's how we're implementing it. Here's why 90% of sales AI tools fail: The "Dead Weight" Problem: Traditional tech forced salespeople to adapt their workflow to the tool. As Hirani puts it, "Technology was like dead weight that people were hauling up the hill... trying to get to this sale, but I can't get there because I have to go to 12 different places." The Generic Solution Trap: Companies throw in Microsoft Copilot or ChatGPT behind a firewall and declare themselves "AI-enabled." Hirani calls this "a recipe for failure" because it ignores business-specific context. The IT Power Play: When IT departments impose generic AI solutions because they have "those two magic letters," adoption inevitably fails. The tools that work are chosen by the business teams who actually use them. The Reality Check That Changed Everything During her time in the sales trenches, Hirani discovered something shocking. When she shared AI tools that worked brilliantly for her, the reactions from her team were mixed: "Some reps said, 'I don't have any confidence in AI. It doesn't sound like me. My prospect is gonna know that it's not me if I haven't felt the pain and written that email myself.'" This revelation led to a fundamental insight: Every rep is at a different point in their AI adoption journey, and one-size-fits-all solutions are doomed to fail. Visual learners needed completely different tools than text-based processors New reps loved real-time coaching popups; veterans found them distracting Some thrived with vanilla ChatGPT; others needed specialized solutions

Scott Martinez, CEO and founder of B2B Catalyst, revolutionizes the conversation on go-to-market strategies. He shares a striking revelation: generating leads doesn't guarantee revenue, as evidenced by a staggering 700 MQLs yielding zero revenue. Scott emphasizes the critical importance of account qualification, revealing that proper criteria can boost close rates by 2-5x. He also discusses the power of AI in enhancing sales efficiency, advocating for tailored methodologies and deep data insights to refine sales strategies effectively.

www.gtmaiacademy.com www.aibusinessnetwork.ai https://www.linkedin.com/in/lauren-schiavone/ https://www.wonderconsultingllc.com/ Navigating AI Transformation: A Conversation with Lauren Morgenstein Join host Jonathan Kvarfordt, AKA Coach K, in the latest episode of the G-T-M-A-I podcast, as he engages with Lauren Morganstein. Lauren shares her journey from a 16-year career at P&G to venturing into the dynamic field of AI. They discuss her decision to found Wonder Consulting and her passion for demystifying AI for non-technical leaders. The conversation delves into practical applications of AI in business, the importance of upskilling, and the transformational potential of AI within organizations. Lauren also outlines her five-step AI transformation framework and shares insights on the evolving landscape of AI native companies and the critical role of effective AI councils. 00:00 Introduction and Guest Welcome 00:47 Lauren's Background and Career Journey 01:20 Diving into AI and Its Impact 02:48 Upskilling and Learning AI 05:08 AI in Consumer Insights and Innovation 12:42 AI Councils and Organizational Transformation 17:33 The Future of Prompting in AI 17:58 Adoption and Tool Recommendations 18:27 Maximizing Approved Tools 20:28 Balancing AI and Human Roles 22:59 Trends in AI for 2025 23:46 AI Native Companies 27:15 Culture and Change Management in AI 30:43 Personal AI Tools and Final Thoughts