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. 1D AGO

    104: Using AI Coworkers to Build Smarter Business Operations with Karl Simon

    Send us Fan Mail Most companies are using AI, but very few are redesigning work around it. In this episode Chris sits down with Karl Simon, co-founder and CTO of Subatomic, an AI workflow orchestration company, to explore why task based AI adoption is limiting business impact. They discuss the shift from isolated AI use cases toward unified workflows powered by clean data, AI coworkers, and cross functional orchestration. The conversation also explores how organizations may flatten hierarchies as AI takes over information movement and decision support responsibilities. Chris and Karl unpack practical steps leaders can take to move from experimentation into operational transformation, including workflow discovery, data readiness, security, and ROI prioritization. Leaders looking to move beyond AI pilots and toward business redesign will find this episode especially valuable. Chapters: 00:00 Introduction 01:05 Meet Karl Simon and Subatomic 04:59 From Hierarchy to Intelligence Layers 07:58 Why Unified Data Changes Everything 11:10 What Companies Get Wrong with AI Adoption 13:06 Integration vs Workflow Orchestration 16:40 What AI Workflow Orchestration Looks Like 19:42 Building a Unified Data Layer 25:00 Where AI Delivers the Fastest ROI 30:47 Security and Compliance by Design 33:08 What are AI Coworkers 35:00 Managing Teams with AI Coworkers Resources: 🔎 Find Out More About Karl Simon Karl Simon LinkedIn https://www.linkedin.com/in/karlsimon Subatomic Website https://getsubatomic.ai/ Subatomic LinkedIn https://www.linkedin.com/company/subatomicai Subatomic YouTube https://www.youtube.com/channel/UCvluGpd82E00q-s-wXBx4FQ 🛠 AI Tools and Resources Mentioned: Subatomic  https://getsubatomic.ai ChatGPT https://chatgpt.com Microsoft Copilot https://copilot.microsoft.com Block https://block.xyz Sequoia Capital https://www.sequoiacap.com Nate B. Jones YouTube https://www.youtube.com/@NateBJones Vistage  https://www.vistage.com

    50 min

  2. MAY 11

    103: Using AI in Manufacturing: Generative vs. Predictive and Autonomous AI with Bryan DeBois

    Send us Fan Mail Most manufacturers are chasing the wrong AI problem. In this episode Chris talks with Bryan DeBois, Director of Industrial AI at RoviSys, about why industrial AI for manufacturing requires a different approach than generative AI. Bryan explains the limits of generative AI on the plant floor, why deterministic systems matter in high risk environments, and how analytical AI, predictive AI, computer vision, and autonomous AI are already being used to improve quality, safety, throughput, and asset performance. Leaders should listen to understand how industrial AI can protect expertise, strengthen operations, and create practical advantage beyond the ChatGPT conversation. Chapters: 00:00 Introduction 01:16 Why Factory Floor AI Is Different From Knowledge Work AI 03:58 The Four Types of AI Used in Manufacturing Today 05:50 Why Generative AI Fails in High Risk Operational Environments 10:56 Manufacturing Risks Also Apply to Construction and Life Sciences 11:36 The Workforce Crisis Driving Industrial AI Adoption 15:26 Why Manufacturing Careers May Be Safer Than White Collar Jobs 20:42 Why Humanoid Robots Are Not the Future of Manufacturing 24:53 Capturing Tribal Knowledge Before Experts Retire 40:00 Who Should Own AI Inside Manufacturing Organizations 43:24 Meta’s Cicero Project and the Future of Hybrid AI Systems 47:08 Deterministic AI vs Probabilistic AI in Critical Industries 49:27 Where to Follow Brian De Bois and Learn More About Industrial AI Resources: 🔎 Find Out More About Bryan DeBois Bryan DeBois on LinkedIn: https://www.linkedin.com/in/bryan-debois RoviSys Industrial AI:  https://www.rovisys.com/ai RoviSys: https://www.rovisys.com 🛠 AI Tools and Resources Mentioned: ChatGPT: https://chatgpt.com/ Claude: https://claude.com/ Grok: https://grok.com/ Meta AI CICERO: https://ai.meta.com/research/cicero Google DeepMind AlphaGo: https://deepmind.google/research/breakthroughs/alphago Microsoft HoloLens: https://www.microsoft.com/hololens Obsidian: https://obsidian.md SAP: https://www.sap.com

    52 min

  3. MAY 4

    102: The AI-Native Company: What Comes After the Org Chart with Melissa Reeve

    Send us Fan Mail Most AI strategies fail because the organization never changes. In this episode Chris sits down with Melissa Reeve, creator of the Hyperadaptive Model and author of an upcoming book on AI-native organizations, to explore why legacy structures block AI progress and what leaders must redesign to unlock real value. They discuss how companies can move from siloed, handoff-heavy operating models to adaptive systems built for continuous learning, faster decisions, and human-centered execution. Leaders responsible for transformation, growth, or operating performance will gain a practical lens for turning AI ambition into sustainable organizational change. Chapters: 00:00 Introduction 00:00 Meet Melissa Reeve and the Hyperadaptive Model 00:00 Why Legacy Operating Models Limit AI Results 00:00 Moving Beyond Automation Thinking 00:00 The Shift to AI-Native Organizations 00:00 Redesigning Roles, Teams, and Workflows 00:00 Building a Human-Centered AI Transformation Strategy 00:00 Creating Continuous Learning Systems 00:00 How Leaders Scale AI Adoption Across the Business 00:00 What the Future Organization Looks Like 🔎 Find Out More About Melissa Reeve Melissa Reeve LinkedIn  https://www.linkedin.com/in/melissamreeve Hyperadaptive Solutions http://hyperadaptive.solutions Book Waitlist https://hyperadaptive.solutions/book Blueprint Session https://hyperadaptive.solutions/why-us#contactForm 🛠 AI Tools and Resources Mentioned: AI Integration Guide http://hyperadaptive.solutions AI Learning Flywheel Ebook http://hyperadaptive.solutions/flywheel-ebook Applied AI Workshop  http://hyperadaptive.solutions/labs

    52 min

  4. APR 27

    101: How to Audit Your Dev Partner in the Age of AI with Matt Strippelhof

    Send us Fan Mail Most companies want innovation, but few can tolerate unpredictable tech costs. In this episode Chris talks with Matt Strippelhoff, Partner, CEO / CRO of Red Hawk Technologies, about how mid-market companies can approach software development with greater financial control and operational confidence. They explore why traditional project models often create risk, and how recurring service models can better align technology execution with business goals. Matt shares lessons from leading web, mobile, integration, maintenance, and emerging AI initiatives while maintaining strong long-term client retention. Leaders will hear practical ideas for reducing technology uncertainty, modernizing critical systems, and creating a more dependable path to innovation, making this episode well worth your time. Chapters: 00:00 Introduction 00:45 Why Mid-Market Companies Struggle with Tech Spend 02:10 The Problem with Traditional Project Pricing 04:05 A Fixed Fee Model for Software Development 06:20 Reducing Operational Risk Through Predictability 08:00 Modernizing Legacy Applications 10:15 Building Web, Mobile, and Middleware Solutions 12:05 Where AI Assistants Fit Into Business Operations 14:10 Driving Retention Through Better Delivery Models 16:00 Leadership Lessons for Scaling Technology Investments 🔎 Find Out More About Matt Strippelhoff Matt Strippelhoff LinkedIn https://www.linkedin.com/in/redhawktech/  Red Hawk Technologies https://www.redhawk-tech.com/ 🛠 AI Tools and Resources Mentioned: Claude https://claude.ai ChatGPT https://chat.openai.com Google Firebase Studio https://firebase.google.com/ Gemini https://gemini.google.com/ Cursor https://cursor.com/ Salesforce https://www.salesforce.com/

    49 min

  5. APR 20

    100: Human Plus AI Strategy: Redefining Team Structure in the Age of Automation with Evan J Schwartz

    Send us Fan Mail Most leaders are asking the wrong AI question. In this episode Chris sits down with Evan J Schwartz, technology leader, adjunct professor, and Chief Innovation Officer, to discuss why AI should be used for growth, not simply cost cutting. Evan shares his vision for the future organization: flatter companies, human stewards managing AI agents, and teams focused on strategy, relationships, and judgment while automation handles repetitive execution. They also explore AI in education, workforce development, sustainability, and why leaders who wait may lose to faster-moving competitors.  If you want a practical framework for using AI to grow smarter without losing your people advantage, this episode is worth your time. Chapters 00:00 Introduction 02:05 Chris Introduces Evan J Schwartz 03:40 Person Plus AI vs Doom and Gloom Narratives 08:30 Which Industries AI Will Disrupt First 09:23 Mentoring Global Students Solving Real Problems with AI 11:12 How AI Could Reduce Food Waste at Scale 18:30 What Colleges Are Getting Wrong About AI 23:38 Why Companies That Wait Will Fall Behind 31:19 The Rise of the Steward Role in Business 41:30 Use AI for Growth, Not Headcount Cuts 🔎 Find Out More About Evan J Schwartz Evan J Schwartz LinkedIn https://www.linkedin.com/in/evan-schwartz-live AMCS Group https://www.amcsgroup.com 🛠 AI Tools and Resources Mentioned: ChatGPT  https://chat.openai.com Anthropic Claude https://www.anthropic.com/claude Docker https://www.docker.com SAP  https://www.sap.com Chief AI Officer  https://chiefaiofficer.com

    58 min

  6. APR 13

    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

  7. APR 6

    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

    1h 1m

  8. MAR 30

    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
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4.9
out of 5
30 Ratings

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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