Using AI at Work: AI in the Workplace & Generative AI for Business Leaders

AI search visibility means little if the recommendation gets your business wrong. In this episode, Chris sits down with Justin Inman, founder and CEO of emberos and a former Google enterprise growth leader, to explore how AI-generated answers shape brand discovery. They discuss generative engine optimization, the shift toward zero-click search, and why accurate recommendations depend on signals across your website, reviews, publishers, and creators.
Justin explains how his team approaches AI brand management by tracing the sources behind inaccurate answers and identifying which information to correct. The conversation covers testing customer questions across chatbots, the limits of visibility scores and content shortcuts, and the challenge of measuring AI-assisted purchases. Justin also shares how Granola, Claude, and HubSpot support his meeting preparation, with human review remaining essential. 
Listen to learn what to check first and how to assess whether your brand is being recommended for the right reasons.
Chapters:
(00:00) Introduction
(03:10) How AI Recommendations Change Brand Discovery
(12:00) AI Brand Management and the Brand Knowledge Graph
(13:39) Generative Engine Optimization Beyond Traditional SEO
(21:18) When AI Gets Your Brand and Products Wrong
(24:29) Tracing and Correcting Inaccurate AI Answers
(26:33) Running an AI Search Visibility Audit
(30:32) Why Internal AI Agents Need Fresh Context and Human Review
(37:04) AI Meeting Preparation with Granola, Claude, and HubSpot
(40:49) Testing AI Recommendations with Real Customer Questions
(42:36) Measuring AI-Assisted Purchases in a Zero-Click World
Resources:
🔎 Find Out More About Justin Inman:
Justin Inman on LinkedIn:
https://www.linkedin.com/in/jinman11/
emberos | AI Brand Management:
https://www.emberos.ai
🛠 AI Tools and Resources Mentioned:
Granola | AI Meeting Notes:
https://www.granola.ai/ The AI Notepad for back-to-back meetings
Claude | AI Assistant:
https://claude.ai/ Claude Help Center
HubSpot | CRM Platform:
https://www.hubspot.com/ Homepage

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What changes when AI-enhanced virtual assistants take on more of your business operations? In this episode, Chris sits down with Joe Rare, business builder and founder of Level 9 Virtual, to explore how human-AI collaboration can expand team capacity while keeping people responsible for direction, quality, and customer relationships. Joe explains how his team combines AI analysis with human follow-up to reactivate cold leads, support revenue recovery, and build business workflows.
The conversation covers where AI workflow automation creates value, why some implementations add work without improving results, and how leaders can decide between employee AI training and hiring skilled support. 
Joe also shares how he uses AI reporting to make faster business decisions, the 1-3-1 framework for turning problems into recommendations, and his approach to learning with Google’s NotebookLM. Listen to identify practical ways to delegate more effectively, strengthen execution, and preserve the human relationships your business depends on.
Chapters:
(00:00) Introduction
(03:20) Building Businesses Run by Virtual Assistants
(06:41) The 10-80-10 Model for Human-AI Collaboration
(07:52) AI-Enhanced Virtual Assistants for Lead Reactivation
(11:32) Human Quality Control for AI Workflows
(18:15) Why AI Automation Fails to Deliver Business Value
(21:55) Employee AI Training vs. Hiring Skilled Support
(27:07) AI Reporting and the 1-3-1 Decision Framework
(32:31) AI Upskilling and Employee Accountability
(37:55) Learning AI with Personalized Lessons and NotebookLM
(42:34) Keeping Customer Relationships Human as AI Scales
Resources:
🔎 Find Out More About Joe Rare:
Joe Rare | Business Systems and Strategic Delegation:
https://joerare.com/ Joe Rare
Level 9 Virtual | Virtual Staffing and Revenue Recovery:
https://level9virtual.com/ Level 9 Virtual
🛠 AI Tools and Resources Mentioned:
Google NotebookLM / Notebook | Learning and Audio Overviews:
https://notebook.google/ AI Research Tool & Thinking Partner
ChatGPT:
https://chatgpt.com/
Claude:
https://claude.com/
Grok:
https://grok.com/
Google Gemini:
https://gemini.google.com/
1-3-1 Decision Framework:
One clearly defined problem, three possible solutions, and one recommended action.
10-80-10 Human-AI Workflow:
Humans define the task, AI handles the heavy lifting, and humans review the result.
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Can AI for leadership help you give your people more attention? In this episode Chris sits down with Jon Harmeling, a Chick-fil-A Operator, Army veteran, and former West Point instructor, to explore how leaders can turn AI productivity gains into better employee coaching and development. Drawing on his restaurant experience and his book, Frontline AI Leadership, Jon shares a practical framework: Machines do. Managers decide. Leaders develop.
Chris and Jon discuss using AI to track employee goals, recognize overlooked contributions, prepare for difficult conversations, and follow through on commitments. They also examine how to measure real AI time savings, reduce context switching, and keep human judgment at the center of workplace automation. 
Listen to learn how to reinvest the time AI creates in stronger relationships and more intentional leadership.

Chapters:
(00:00) Introduction
(06:06) Management vs. Leadership and the AI Capacity Dividend
(15:51) Making Time for Employee Coaching and Development
(18:44) Reducing Context Switching When Working with AI
(20:37) Measuring Real AI Time Savings and Accountability
(23:28) Frontline AI Adoption, AI Search, and Data Privacy
(27:49) From AI Agents to Writing Frontline AI Leadership
(33:01) Machines Do. Managers Decide. Leaders Develop.
(35:50) Tracking Employee Goals with AI
(39:22) AI Scheduling and the Limits of Automation
(41:19) Preparing for Difficult Conversations with AI
Resources:
🔎 Find Out More About Jon Harmeling:
Website:
https://www.jonharmeling.com 
Frontline AI Leadership Book:
https://www.jonharmeling.com/book 
https://www.amazon.com/dp/B0HNDTHR36 
LinkedIn:
https://www.linkedin.com/in/jonharmeling/
X:
https://x.com/JonHarmeling
🛠 AI Tools and Resources Mentioned:
Claude and Claude Cowork:
https://claude.com/product/cowork
ChatGPT:
https://chatgpt.com

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What if your sales team could practice its toughest conversations before speaking to real customers? In this episode, Chris sits down with Paul Burani, Co-Founder and CRO of Atlas Primer, to explore how AI sales roleplay brings realistic practice and personalized feedback into sales training. They discuss how short, regular sessions help teams develop human skills, prepare for objections, and approach high-stakes conversations with greater confidence.
Paul explains how to tailor simulations to specific prospects, incorporate your sales methodology, and connect AI sales coaching to measurable business outcomes. He also shares his AI workflow for following up on stalled deals and the data privacy questions leaders should ask before adopting new tools. Listen to discover practical ways to strengthen your team’s skills and make better use of the time AI saves.

Chapters
(00:00) Introduction
(06:19) How Atlas Primer Builds Conversational Skills
(09:25) Getting Sales Teams to Embrace AI Coaching
(13:05) Building a Regular Sales Practice Habit
(14:24) Inside an AI Roleplay Training Session
(22:17) Preparing for Specific Prospects with LinkedIn
(24:13) Connecting Sales Training to Business Outcomes
(29:41) Adapting Sales Methodologies and Extending Coaching
(32:53) The Handoff: AI Follow-Ups for Stalled Deals
(36:13) Data Privacy Questions Every Leader Should Ask
(41:46) Reinvesting AI Time Savings Without Burning Out Teams
Resources:
🔎 Find Out More About Paul Burani:
LinkedIn: 
https://www.linkedin.com/in/pburani linkedin.com
Atlas Primer: 
https://atlasprimer.com/
Atlas Primer Roleplay: 
https://roleplay.atlasprimer.com/ Atlas Primer
🛠 AI Tools and Resources Mentioned:
Gong: 
https://www.gong.io/
OpenClaw: 
https://openclaw.ai/
HubSpot: 
https://www.hubspot.com/
Tableau: 
https://www.tableau.com/
Microsoft Power BI: 
https://www.microsoft.com/en-us/power-platform/products/power-bi
The AI-Driven Leader by Geoff Woods: 
https://www.aileadership.com/book 
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What if your AI tools aren't underperforming because of the technology, but because they don't know your business? In this episode Chris sits down with Rob Collie, CEO of P3 Adaptive, former Microsoft Power BI developer, and author of Fair Game: Customizing AI to Your Business Is Easier Than You Think, to explore why buying ChatGPT or Claude subscriptions isn't enough to achieve meaningful enterprise AI adoption.
Rob explains the "knowledge cliff" that prevents generic AI tools from delivering reliable business results, why employees shouldn't be responsible for repeatedly teaching AI how their company works, and how leaders can build customized AI systems grounded in company knowledge. Through practical examples involving Claude Desktop, Claude Cowork, Notion, and AI-assisted workflows, they discuss context engineering, organizational knowledge, trusted sources of truth, and AI governance. 
Listen to discover how leaders can move beyond AI experimentation and create systems their teams can actually trust and use.

Chapters:
(00:00) Why AI Needs Trusted Business Knowledge
(02:53) From Microsoft Power BI to the AI Revolution
(05:25) Why Buying AI Subscriptions Isn't Enough
(09:22) The Claude Desktop Experiment That Changed Everything
(11:46) The Knowledge Cliff: Why AI Doesn't Know Your Business
(14:16) Bot Sitting and the Hidden Cost of AI Adoption
(16:50) Why Business Leaders Must Own AI Context
(21:48) How to Customize AI with Claude Cowork
(24:12) Building a Personalized AI Editor
(39:24) Fair Game and the Future of Business AI

Resources: 
🔎 Find Out More About Rob Collie
LinkedIn: https://www.linkedin.com/in/robcollie/
P3 Adaptive: https://p3adaptive.com/
Raw Data with Rob Collie Podcast: https://p3adaptive.com/rawdatapodcast/
The Goldilocks Altitude Newsletter (Substack): https://goldilocks1.substack.com/ 
Fair Game: Customizing AI to Your Business Is Easier Than You Think by Rob Collie: https://www.amazon.com/Fair-Game-Customizing-Business-Easier/dp/1615470948 
🛠 AI Tools and Resources Mentioned:
ChatGPT (OpenAI): https://chatgpt.com/
Claude:  https://claude.ai/
Microsoft Copilot: https://copilot.microsoft.com/
Notion: https://www.notion.so/
OpenAI Codex: https://openai.com/codex/
Model Context Protocol (MCP): https://modelcontextprotocol.io/

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