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

Chris Daigle
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On "Using AI at Work", your host Chris Daigle and his expert guests help business leaders, executives, and teams who want to turn artificial intelligence into a real competitive advantage. Each episode shares real-world AI applications and AI transformation stories from companies successfully using AI in the workplace to improve productivity, decision-making, and operations. You’ll hear from Chief AI Officers, innovators, and forward-thinking executives who are putting generative AI at work, from AI productivity tools and AI-powered workflows to non-technical AI training and workplace AI adoption strategies. We cover: AI for business leaders – how executives use AI to lead change and drive ROIGenerative AI tools – practical, easy-to-implement solutions for teamsAI automation in business – streamline operations without massive tech budgetsExecutive AI education – upskilling leaders and managers for the AI eraReal-world AI case studies – lessons learned from successful AI implementationAI in operations management – optimizing processes and reducing costsEthical AI in business – navigating responsible and effective AI use Whether you’re exploring AI adoption, leading AI-powered transformation, or looking for AI implementation guides, this podcast delivers a clear, non-technical roadmap to succeed in the AI-driven economy. New episodes weekly. Start learning how to put AI to work in your business today.

  1. 5 DAYS AGO

    99: Using AI Automation to Build Smarter Workflows Across Your Organization with Marc Boscher

    Send us Fan Mail Most companies think they are “doing AI” but are still stuck in single-player mode. In this episode Chris talks with Marc Boscher, Founder and CEO of Unito, a workflow integration platform, about why AI adoption breaks down at the organizational level. Marc explains that the real barrier is not model capability, but fragmented systems, missing context, and lack of trust. He introduces the shift from prompt engineering to context engineering, and why connecting systems and data is the key to unlocking AI that works across teams, not just for individuals. The conversation explores how leaders can move from isolated productivity gains to true enterprise impact by building context libraries, enabling dynamic data access, and reducing operational friction. Marc also breaks down the importance of trust, deterministic vs non-deterministic systems, and why change management remains the biggest challenge. This episode gives leaders a practical lens for turning AI from a tool employees use into infrastructure the business runs on. Chapters: 00:00:00 Introduction 00:00:36 Why Trust and Context Are Critical for AI Agents 00:01:00 Context vs Prompts: What Actually Matters 00:03:48 Single Player vs Multiplayer AI in Business 00:06:30 Why Context Unlocks Enterprise-Level AI Value 00:08:28 What “Context” Really Means in AI Systems 00:11:34 Building Context-Rich AI Use Cases (Sales Example) 00:13:42 Static vs Dynamic Context Explained 00:20:12 Why Context Engineering Replaces Prompt Engineering 00:24:04 From Human-in-the-Loop to Autonomous AI Systems 00:27:29 The Context Gap and Operational Inefficiency 00:36:01 Why Change Management Is the Real Bottleneck 00:42:03 Deterministic vs Non-Deterministic AI Systems 🔎 Find Out More About Marc Boscher: LinkedIn: https://www.linkedin.com/in/marcboscher  Unito: https://unito.io  🛠 AI Tools and Resources Mentioned: Unito – https://unito.io Salesforce – https://www.salesforce.com ServiceNow – https://www.servicenow.com GitHub – https://github.com HubSpot – https://www.hubspot.com NetSuite – https://www.netsuite.com Workday – https://www.workday.com ChatGPT – https://chat.openai.com Claude – https://claude.ai Gemini – https://gemini.google.com Copilot – https://copilot.microsoft.com

    50 min

  2. 6 APR

    98: How to Build AI Agents That Automate Workflows Without Coding with Etan Polinger

    Send us Fan Mail Most leaders think AI agents are too technical to build, but the real barrier is not skill, it is clarity. In this episode Chris talks with Etan Polinger, AI Solutions Architect and Head of AI Solutions, about how non-technical professionals can design, build, and deploy AI agents that drive real business outcomes. Etan breaks down what an agent actually is, how to think about automation versus agentic workflows, and why fundamentals matter more than tools in a rapidly changing AI landscape. They explore practical examples from inbox automation to project intelligence systems, along with the frameworks Etan uses to help operators move from idea to deployed solution. If you want to move beyond AI curiosity and start building systems that create leverage inside your business, this episode shows you where to begin and how to think about it. Chapters: 00:00 Introduction 00:12 Why Asking Better Questions Unlocks AI 00:33 What Is Actually Possible With AI Today 00:52 What an AI Agent Really Is 01:46 Bridging AI Hype and Real Execution 03:05 Why Non-Technical People Can Now Build 05:19 Where Business Leaders Should Start 08:52 Real Examples of AI Agents in Action 13:57 The Right Way to Start Building With AI 17:36 How Long It Takes to Learn This Skill 22:13 Why Your AI Builds Keep Breaking 33:29 Common Mistakes When Building Agents 38:02 The SCOUTS Framework Explained 44:20 The Most Powerful Question You Can Ask AI 🔎 Find Out More About Etan Polinger LinkedIn:  https://www.linkedin.com/in/etan-polinger  🛠 AI Tools and Resources Mentioned AI Agents + Automation Certification https://www.CAIO.cx/agent ChatGPT (OpenAI) https://chat.openai.com Claude (Anthropic) https://claude.ai OpenAI https://openai.com Cursor (AI Code Editor) https://cursor.sh Lovable (AI App Builder) https://lovable.dev OpenClaw (AI Agent Framework) https://github.com/openclaw/openclaw N8N (Workflow Automation) https://n8n.io Salesforce https://www.salesforce.com Notion https://www.notion.so Perplexity AI https://www.perplexity.ai Context7 (Code + Documentation Tool) https://context7.com Chief AI Officer Program https://chiefaiofficer.com

    1hr 1min

  3. 30 MAR

    97: Using AI for Customer Support: Voice AI vs Humans in Customer Service Strategy with Nathan Strum

    Send us Fan Mail Most leaders assume AI in customer service means replacing people, but the data tells a more complicated story. In this episode Chris talks with Nathan Strum, CEO of Abby Connect, about what actually works when deploying voice AI in real business environments. Drawing on two decades of customer service experience, Nathan explains why AI excels at structured workflows like scheduling, but still struggles with unpredictable edge cases where human judgment matters most. He also shares why many companies that experiment with full automation quietly return to human support, and how Abby is growing both its AI and human workforce at the same time. The conversation goes deeper into practical implementation, including where AI is safe to deploy today, why outbound AI calling is a high-risk move, and how to design systems that combine speed, scalability, and trust. Nathan also outlines a leadership approach to AI adoption that focuses on reducing friction across systems, reskilling employees, and using AI to enhance rather than replace human capability. This episode gives leaders a grounded, experience-based framework for deciding where AI belongs in their customer experience strategy. Chapters: 00:00 Introduction 01:00 Where Voice AI Delivers Immediate Value 02:29 Introducing Abby’s AI + Human Strategy 04:21 The Limits of AI in Real Customer Interactions 06:52 Best Use Cases: AI Scheduling vs Human Sales Calls 08:30 Why AI Adoption Is Increasing Human Headcount 11:04 Lessons from Failed “AI-Only” Customer Service Experiments 15:23 Where AI Is Safe vs Risky in Phone Workflows 17:31 Why Transparency About AI Improves Customer Trust 23:06 The Future of Offshore, AI, and Voice Technology 27:29 AI as a System Redesign Tool, Not Just Cost Reduction 29:56 Managing Employee Fear During AI Adoption 32:57 Selling Outcomes Instead of AI Products 35:18 How to Evaluate AI Vendors in Customer Experience 🔎 Find Out More About Nathan Strum Abby Connect Website https://www.abbey.com LinkedIn https://www.linkedin.com/in/nathanstrum https://www.linkedin.com/company/abby-connect/ Facebook https://www.facebook.com/abbyconnect/ X: https://x.com/abbyconnect Website: https://www.abby.com/ 🛠 AI Tools and Resources Mentioned OpenAI https://openai.com Anthropic https://www.anthropic.com Google Gemini https://gemini.google.com ElevenLabs https://elevenlabs.io

    38 min

  4. 23 MAR

    96: Using AI Adoption Strategies That Actually Deliver ROI for Your Business with Jim Spignardo

    Send us Fan Mail Most companies aren’t struggling to buy AI, they’re struggling to use it well. In this episode Chris sits down with Jim Spignardo, Director of Cloud Strategy and AI Enablement at ProArch, to break down what’s really happening inside organizations adopting AI today. Jim shares why many companies are stuck after purchasing licenses, how to move from experimentation to structured adoption, and what separates companies seeing real ROI from those chasing hype. He outlines a practical playbook that starts with executive alignment, prioritizes high-value use cases, and builds toward secure, governed AI systems that scale. They also explore how organizations can recoup AI investments within months, why data governance is the hidden foundation of success, and how to balance rapid innovation with risk management as agents and automation evolve.  If you’re leading AI adoption or trying to turn early momentum into measurable business value, this episode offers a clear, experience-backed path forward. Chapters: 00:00 Introduction 00:14 Where Companies Are Today in Their AI Journey 00:49 The Future: AI, Robotics, and What’s Next 01:30 Why AI Strategy Matters for Business Leaders 02:38 Common Challenges: Risk, Use Cases, and Leadership Gaps 05:06 Building an AI Adoption Playbook 06:23 From Buying Licenses to Lacking Direction 10:00 What Executives Need to Understand About AI 13:01 The Shift from Productivity Tools to AI Agents 17:47 How Long It Takes to See Real Results 19:25 Measuring ROI and Tracking AI Value 22:12 Real Example: AI Improving RFP Win Rates 30:12 Change Management and Driving Adoption 31:16 Training, Governance, and Building AI Culture 40:12 Managing Risk While Enabling Innovation 45:04 What’s Next: AI + Robotics Convergence 🔎 Find Out More About Jim Spignardo LinkedIn: https://www.linkedin.com/in/spignardo  ProArch: https://www.proarch.com 🛠 AI Tools and Resources Mentioned: Microsoft Copilot https://www.microsoft.com/en-us/microsoft-365/copilot Microsoft Defender for Cloud Apps https://learn.microsoft.com/en-us/defender-cloud-apps/what-is-defender-for-cloud-apps Microsoft Purview (Data Loss Prevention & Information Protection) https://learn.microsoft.com/en-us/purview/ Azure OpenAI Service https://azure.microsoft.com/en-us/products/ai-services/openai-service OpenAI / ChatGPT https://chat.openai.com Claude (Anthropic) https://www.anthropic.com/claude Cursor (AI coding assistant) https://www.cursor.sh

    51 min

  5. 16 MAR

    95: The Dark Side of Gen AI: When Platforms Move Faster Than Regulation with Jesse Jameson

    Send us Fan Mail What happens when the AI tool helping you scale your business also gains permanent rights to your voice? In this episode Chris talks with Jesse Jameson, digital marketing veteran and founder of HeyNow Interactive, about the opportunities and emerging risks inside the generative AI ecosystem. Jesse shares his experience participating in a voice licensing program with ElevenLabs, where his AI voice quickly became one of the most widely used on the platform. What began as a simple experiment in passive income through voice cloning eventually uncovered deeper questions around creator consent, data ownership, and how AI companies structure their business models. The conversation explores how leaders should think about AI adoption today, including the tension between rapid innovation and responsible governance. From biometric data rights and AI regulation to the strategic reality that businesses cannot afford to ignore generative AI, Jesse and Chris discuss how executives can embrace AI’s advantages while remaining thoughtful about the risks that come with it. This episode offers an important perspective for leaders navigating AI adoption in a rapidly evolving landscape. Chapters:00:00 AI Voice Licensing and the Start of a Major Discovery 00:45 Introducing Jesse Jameson and the Rise of AI Voice Technology 03:15 From Early Internet Marketing to the Age of AI 04:22 Joining the ElevenLabs Voice Actors Program 06:13 Discovering Discrepancies in Voice Usage and Payments 08:29 The Consent Problem and Hidden Licensing Terms 10:31 Regulatory Questions and Biometric Data Laws 12:15 The Hidden Risks of Using Generative AI Tools 17:21 Bias, Control, and the Influence of AI Models 26:23 Investigating Platform Abuse and Free Voice Usage 36:29 Documenting the Experience and Reporting to Regulators 44:06 Practical Advice for Leaders Using New AI Tools 🔎 Find Out More About Jesse Jameson LinkedIn: Jesse Jameson Substack: @jpjameson Youtube: @jpjameson Website: https://11laudit.com The Voice Cloning Scam That Hit $11 Billion: https://www.youtube.com/watch?v=2wPdQyrWhl0&t=2s  Book: The Conversation You Can't Explain: Finding Yourself in the Age of AI 🛠 AI Tools and Platforms Mentioned ElevenLabs: https://elevenlabs.io/  OpenAI: https://openai.com/  Anthropic: https://www.anthropic.com  LLaMA: https://www.llama.com

    47 min

  6. 9 MAR

    94: Using AI vs Human Intelligence: When Should Leaders Trust Machines with Vasant Dhar

    Send us Fan Mail The real challenge with AI is not the technology, it is knowing when leaders should trust the machine and when they should not. In this episode Chris sits down with Vasant Dhar, professor at NYU Stern and the NYU Center for Data Science, longtime AI practitioner, and author of Thinking with Machines: The Brave New World of AI. With more than four decades working in artificial intelligence across finance, healthcare, and research, Dhar shares a practical framework for deciding when leaders should trust AI and when human oversight still matters. His “trust map” evaluates two variables: how often the system is wrong and the consequences of its errors. The conversation also tackles why so many AI pilots fail, why fear rather than greed is driving AI adoption in many organizations, and how leaders should prioritize their first AI initiatives. Dhar explains why deep domain knowledge becomes even more valuable in the AI era, why executives must understand their data before deploying AI, and why the future belongs to people who learn to think with machines rather than simply ask them for answers. Leaders who want a clearer way to evaluate AI opportunities and avoid costly missteps will find this discussion well worth their time. Chapters 00:00 Introduction 03:23 The Origin of the “Trust AI” Question 05:14 The Trust Framework: Predictability vs Cost of Error 07:01 Crossing the Automation Frontier 09:07 The Three Barriers Holding Leaders Back from AI 11:51 Why 95% of AI Projects Fail 14:39 How Leaders Should Choose Their First AI Projects 19:17 Fear vs Greed in Today’s AI Adoption 25:20 Why Leaders Should “Think Slowly” About AI Strategy 44:16 The Bifurcation of Humanity in the Age of AI 🔎 Find Out More About Vasant Dhar Website: https://vasantdhar.com  Book: Thinking with Machines: The Brave New World of AI Podcast: Brave New World Substack Newsletter: https://vasantdhar.substack.com 🛠 AI Tools and Resources Mentioned ChatGPT https://chat.openai.com Claude https://claude.ai Grok https://x.ai Chief AI Officer (Sponsor) https://chiefaiofficer.com Using AI at Work https://usingaiatwork.com

    56 min

  7. 2 MAR

    93: Using Generative AI to Develop a Winning Strategy for Business Leaders with Justin Trombold

    Send us Fan Mail Most leaders aren’t struggling with AI tools, they’re struggling with how to lead the transformation those tools require. In this episode, Chris interviews Justin Trombold, President of Antesyn Advisors who works with leadership teams navigating the uncertainty of generative AI strategy across industries from healthcare to enterprise services. During the conversation, he explains why most organizations go wrong by treating generative AI as an IT deployment rather than a transformation initiative, centralizing tool decisions while failing to connect use cases to business strategy, incentives, and operating models. Chris and Justin unpack what it actually looks like to deploy AI in the real world: separating enterprise strategy from use-case experimentation, starting small with tightly defined pilots, defining KPIs before declaring success, and anticipating downstream bottlenecks that AI acceleration often creates. They also explore why cross-functional collaboration, incentive alignment, and curiosity matter more than technical horsepower — and why leaders must shift from “installing AI” to building organizational readiness for it. If you want a practical lens for turning generative AI into measurable advantage — without triggering organizational friction — this episode is for you! Chapters: (00:00) Introduction (02:01) Meet Justin Trombold (05:03) What Companies Get Right — and Wrong — About Generative AI (07:38) Why Generative AI Is Not an IT Project (08:55) Centralizing Tools, Decentralizing Use Cases (16:31) Who Should Be in the Room for AI Strategy (17:28) Enterprise Strategy vs. Use Case Execution (20:15) When AI Just Shifts the Bottleneck (29:40) The Five Pillars of AI Readiness (33:18) Designing Small AI Experiments That Scale (41:09) Building Real AI Fluency Inside Your Organization 🔎 Find Out More About Justin Trombold Website: https://www.antesynadvisors.com LinkedIn: https://www.linkedin.com/in/trombold  🛠 AI Tools and Resources Mentioned ChatGPT (OpenAI) https://chat.openai.com Claude (Anthropic) https://claude.ai Gemini (Google) https://gemini.google.com Grok (xAI) https://x.ai

    48 min

  8. 23 FEB

    92: Using AI for Smarter Marketing: Synthetic Audiences, OpenClaw & AI Agents with Justin Brooke

    Send us Fan Mail Before you spend another dollar on ads, what if you could test your message against a digital version of your exact market? In today’s episode, Justin Brooke, founder of AdSkills and Agent Skills AI, joins Chris Daigle to break down how synthetic audiences and virtual focus groups are transforming modern marketing. After getting his start interning for Russell Brunson and famously turning $60 into six figures with Google Ads, Justin has spent two decades mastering message-to-market match.  Now, he’s using AI to simulate highly detailed customer personas, running ads, landing pages, and even full funnels through structured “virtual focus groups” before a single dollar is deployed. In this conversation, Justin explains how to build high-quality AI personas using real demographic, psychographic, and empathy-map data; how multi-persona scoring systems are outperforming gut instinct; and why this approach may soon become the first step in every serious marketing strategy. He also shares his perspective on emerging agent frameworks like  OpenClaw, the security implications leaders need to consider, and where AI is realistically delivering value today—without hype. If you want a practical framework for reducing marketing risk and increasing message precision before you go live, this episode will reshape how you think about AI in your growth strategy. 🔎 Find Out More About Justin Brooke X: @IMJustinBrooke Website: https://www.adskills.com 🛠 AI Tools and Resources Mentioned MindStudio - https://mindstudio.ai Make – https://www.make.com Claude – https://claude.ai OpenAI – https://openai.com DigitalOcean – https://www.digitalocean.com Docker – https://www.docker.com CrewAI – https://www.crewai.com LangChain – https://www.langchain.com Fathom – https://fathom.video Chapters: 00:00 Introduction 03:13 “Virtual Focus Groups” and Why They Matter 03:47 Justin’s Origin Story: From Intern to Advertiser 08:45 From Personas to Synthetic Audiences 15:24 How the System Produces Variations and Picks Winners 20:09 How “Mad Men” Marketers React to Market Feedback 22:21 Building Real ICPs: 1,000+ Words, Not One-Liners 27:15 The New York Times “Digital Twin” and 92% Accuracy 30:13 Tool Stack: MindStudio, Claude Projects, and Agent Frameworks 35:16 OpenClaw, AI Agents & Security Considerations 49:55 Staying Focused: Pick Your Lane in AI

    52 min
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About

On "Using AI at Work", your host Chris Daigle and his expert guests help business leaders, executives, and teams who want to turn artificial intelligence into a real competitive advantage. Each episode shares real-world AI applications and AI transformation stories from companies successfully using AI in the workplace to improve productivity, decision-making, and operations. You’ll hear from Chief AI Officers, innovators, and forward-thinking executives who are putting generative AI at work, from AI productivity tools and AI-powered workflows to non-technical AI training and workplace AI adoption strategies. We cover: AI for business leaders – how executives use AI to lead change and drive ROIGenerative AI tools – practical, easy-to-implement solutions for teamsAI automation in business – streamline operations without massive tech budgetsExecutive AI education – upskilling leaders and managers for the AI eraReal-world AI case studies – lessons learned from successful AI implementationAI in operations management – optimizing processes and reducing costsEthical AI in business – navigating responsible and effective AI use Whether you’re exploring AI adoption, leading AI-powered transformation, or looking for AI implementation guides, this podcast delivers a clear, non-technical roadmap to succeed in the AI-driven economy. New episodes weekly. Start learning how to put AI to work in your business today.

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