Podcast
Using AI at Work: AI in the Workplace & Generative AI for Business Leaders
Hosted by Chris Daigle · EN
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 ROI
- Generative AI tools – practical, easy-to-implement solutions for teams
- AI automation in business – streamline operations without massive tech budgets
- Executive AI education – upskilling leaders and managers for the AI era
- Real-world AI case studies – lessons learned from successful AI implementation
- AI in operations management – optimizing processes and reducing costs
- Ethical 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.
36episodes
Episodes
Newest firstAll episodes
104: Using AI Coworkers to Build Smarter Business Operations with Karl Simon
Yesterday00:49:54Summary readySend us Fan MailMost 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 Introduction01:05 Meet Karl Simon and Subatomic04:59 From Hierarchy to Intelligence Layers07:58 Why Unified Data Changes Everything11:10 What Companies Get Wrong with AI Adoption13:06 Integration vs Workflow Orchestration16:40 What AI Workflow Orchestration Looks Like19:42 Building a Unified Data Layer25:00 Where AI Delivers the Fastest ROI30:47 Security and Compliance by Design33:08 What are AI Coworkers35:00 Managing Teams with AI CoworkersResources:🔎 Find Out More About Karl SimonKarl Simon LinkedIn https://www.linkedin.com/in/karlsimonSubatomic Website https://getsubatomic.ai/Subatomic LinkedIn https://www.linkedin.com/company/subatomicaiSubatomic YouTube https://www.youtube.com/channel/UCvluGpd82E00q-s-wXBx4FQ🛠 AI Tools and Resources Mentioned:Subatomic https://getsubatomic.aiChatGPT https://chatgpt.comMicrosoft Copilot https://copilot.microsoft.comBlock https://block.xyzSequoia Capital https://www.sequoiacap.comNate B. Jones YouTube https://www.youtube.com/@NateBJonesVistage https://www.vistage.com
Summary103: Using AI in Manufacturing: Generative vs. Predictive and Autonomous AI with Bryan DeBois
1w ago00:52:07Summary readySend us Fan MailMost 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 Introduction01:16 Why Factory Floor AI Is Different From Knowledge Work AI03:58 The Four Types of AI Used in Manufacturing Today05:50 Why Generative AI Fails in High Risk Operational Environments10:56 Manufacturing Risks Also Apply to Construction and Life Sciences11:36 The Workforce Crisis Driving Industrial AI Adoption15:26 Why Manufacturing Careers May Be Safer Than White Collar Jobs20:42 Why Humanoid Robots Are Not the Future of Manufacturing24:53 Capturing Tribal Knowledge Before Experts Retire40:00 Who Should Own AI Inside Manufacturing Organizations43:24 Meta’s Cicero Project and the Future of Hybrid AI Systems47:08 Deterministic AI vs Probabilistic AI in Critical Industries49:27 Where to Follow Brian De Bois and Learn More About Industrial AIResources:🔎 Find Out More About Bryan DeBoisBryan DeBois on LinkedIn:https://www.linkedin.com/in/bryan-deboisRoviSys Industrial AI: https://www.rovisys.com/aiRoviSys: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/ciceroGoogle DeepMind AlphaGo: https://deepmind.google/research/breakthroughs/alphagoMicrosoft HoloLens: https://www.microsoft.com/hololensObsidian: https://obsidian.mdSAP:https://www.sap.com
Summary102: The AI-Native Company: What Comes After the Org Chart with Melissa Reeve
2w ago00:52:12Summary readySend us Fan MailMost 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 Introduction00:00 Meet Melissa Reeve and the Hyperadaptive Model00:00 Why Legacy Operating Models Limit AI Results00:00 Moving Beyond Automation Thinking00:00 The Shift to AI-Native Organizations00:00 Redesigning Roles, Teams, and Workflows00:00 Building a Human-Centered AI Transformation Strategy00:00 Creating Continuous Learning Systems00:00 How Leaders Scale AI Adoption Across the Business00:00 What the Future Organization Looks Like🔎 Find Out More About Melissa ReeveMelissa Reeve LinkedIn https://www.linkedin.com/in/melissamreeveHyperadaptive Solutionshttp://hyperadaptive.solutionsBook Waitlisthttps://hyperadaptive.solutions/bookBlueprint Sessionhttps://hyperadaptive.solutions/why-us#contactForm🛠 AI Tools and Resources Mentioned:AI Integration Guidehttp://hyperadaptive.solutionsAI Learning Flywheel Ebookhttp://hyperadaptive.solutions/flywheel-ebookApplied AI Workshop http://hyperadaptive.solutions/labs
Summary101: How to Audit Your Dev Partner in the Age of AI with Matt Strippelhof
3w ago00:48:45Summary readySend us Fan MailMost 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 Introduction00:45 Why Mid-Market Companies Struggle with Tech Spend02:10 The Problem with Traditional Project Pricing04:05 A Fixed Fee Model for Software Development06:20 Reducing Operational Risk Through Predictability08:00 Modernizing Legacy Applications10:15 Building Web, Mobile, and Middleware Solutions12:05 Where AI Assistants Fit Into Business Operations14:10 Driving Retention Through Better Delivery Models16:00 Leadership Lessons for Scaling Technology Investments🔎 Find Out More About Matt StrippelhoffMatt Strippelhoff LinkedInhttps://www.linkedin.com/in/redhawktech/ Red Hawk Technologieshttps://www.redhawk-tech.com/🛠 AI Tools and Resources Mentioned:Claude https://claude.aiChatGPThttps://chat.openai.comGoogle Firebase Studiohttps://firebase.google.com/Gemini https://gemini.google.com/Cursor https://cursor.com/Salesforcehttps://www.salesforce.com/
Summary100: Human Plus AI Strategy: Redefining Team Structure in the Age of Automation with Evan J Schwartz
4w ago00:57:49Summary readySend us Fan MailMost 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.Chapters00:00 Introduction02:05 Chris Introduces Evan J Schwartz03:40 Person Plus AI vs Doom and Gloom Narratives08:30 Which Industries AI Will Disrupt First09:23 Mentoring Global Students Solving Real Problems with AI11:12 How AI Could Reduce Food Waste at Scale18:30 What Colleges Are Getting Wrong About AI23:38 Why Companies That Wait Will Fall Behind31:19 The Rise of the Steward Role in Business41:30 Use AI for Growth, Not Headcount Cuts🔎 Find Out More About Evan J SchwartzEvan J Schwartz LinkedIn https://www.linkedin.com/in/evan-schwartz-liveAMCS Grouphttps://www.amcsgroup.com🛠 AI Tools and Resources Mentioned:ChatGPT https://chat.openai.comAnthropic Claudehttps://www.anthropic.com/claudeDockerhttps://www.docker.comSAP https://www.sap.comChief AI Officer https://chiefaiofficer.com
Summary99: Using AI Automation to Build Smarter Workflows Across Your Organization with Marc Boscher
Apr 1300:49:38Summary readySend us Fan MailMost 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 Introduction00:00:36 Why Trust and Context Are Critical for AI Agents00:01:00 Context vs Prompts: What Actually Matters00:03:48 Single Player vs Multiplayer AI in Business00:06:30 Why Context Unlocks Enterprise-Level AI Value00:08:28 What “Context” Really Means in AI Systems00:11:34 Building Context-Rich AI Use Cases (Sales Example)00:13:42 Static vs Dynamic Context Explained00:20:12 Why Context Engineering Replaces Prompt Engineering00:24:04 From Human-in-the-Loop to Autonomous AI Systems00:27:29 The Context Gap and Operational Inefficiency00:36:01 Why Change Management Is the Real Bottleneck00:42:03 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.ioSalesforce – https://www.salesforce.comServiceNow – https://www.servicenow.comGitHub – https://github.comHubSpot – https://www.hubspot.comNetSuite – https://www.netsuite.comWorkday – https://www.workday.comChatGPT – https://chat.openai.comClaude – https://claude.aiGemini – https://gemini.google.comCopilot – https://copilot.microsoft.com
Summary98: How to Build AI Agents That Automate Workflows Without Coding with Etan Polinger
Apr 601:00:41Summary readySend us Fan MailMost 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 Introduction00:12 Why Asking Better Questions Unlocks AI00:33 What Is Actually Possible With AI Today00:52 What an AI Agent Really Is01:46 Bridging AI Hype and Real Execution03:05 Why Non-Technical People Can Now Build05:19 Where Business Leaders Should Start08:52 Real Examples of AI Agents in Action13:57 The Right Way to Start Building With AI17:36 How Long It Takes to Learn This Skill22:13 Why Your AI Builds Keep Breaking33:29 Common Mistakes When Building Agents38:02 The SCOUTS Framework Explained44:20 The Most Powerful Question You Can Ask AI🔎 Find Out More About Etan PolingerLinkedIn: https://www.linkedin.com/in/etan-polinger 🛠 AI Tools and Resources MentionedAI Agents + Automation Certificationhttps://www.CAIO.cx/agentChatGPT (OpenAI)https://chat.openai.comClaude (Anthropic)https://claude.aiOpenAIhttps://openai.comCursor (AI Code Editor)https://cursor.shLovable (AI App Builder)https://lovable.devOpenClaw (AI Agent Framework)https://github.com/openclaw/openclawN8N (Workflow Automation)https://n8n.ioSalesforcehttps://www.salesforce.comNotionhttps://www.notion.soPerplexity AIhttps://www.perplexity.aiContext7 (Code + Documentation Tool)https://context7.comChief AI Officer Programhttps://chiefaiofficer.com
Summary97: Using AI for Customer Support: Voice AI vs Humans in Customer Service Strategy with Nathan Strum
Mar 3000:38:22Summary readySend us Fan MailMost 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 Introduction01:00 Where Voice AI Delivers Immediate Value02:29 Introducing Abby’s AI + Human Strategy04:21 The Limits of AI in Real Customer Interactions06:52 Best Use Cases: AI Scheduling vs Human Sales Calls08:30 Why AI Adoption Is Increasing Human Headcount11:04 Lessons from Failed “AI-Only” Customer Service Experiments15:23 Where AI Is Safe vs Risky in Phone Workflows17:31 Why Transparency About AI Improves Customer Trust23:06 The Future of Offshore, AI, and Voice Technology27:29 AI as a System Redesign Tool, Not Just Cost Reduction29:56 Managing Employee Fear During AI Adoption32:57 Selling Outcomes Instead of AI Products35:18 How to Evaluate AI Vendors in Customer Experience🔎 Find Out More About Nathan StrumAbby Connect Websitehttps://www.abbey.comLinkedInhttps://www.linkedin.com/in/nathanstrumhttps://www.linkedin.com/company/abby-connect/Facebook https://www.facebook.com/abbyconnect/X: https://x.com/abbyconnectWebsite: https://www.abby.com/🛠 AI Tools and Resources MentionedOpenAIhttps://openai.comAnthropichttps://www.anthropic.comGoogle Geminihttps://gemini.google.comElevenLabshttps://elevenlabs.io
Summary96: Using AI Adoption Strategies That Actually Deliver ROI for Your Business with Jim Spignardo
Mar 2300:50:55Summary readySend us Fan MailMost 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 Introduction00:14 Where Companies Are Today in Their AI Journey00:49 The Future: AI, Robotics, and What’s Next01:30 Why AI Strategy Matters for Business Leaders02:38 Common Challenges: Risk, Use Cases, and Leadership Gaps05:06 Building an AI Adoption Playbook06:23 From Buying Licenses to Lacking Direction10:00 What Executives Need to Understand About AI13:01 The Shift from Productivity Tools to AI Agents17:47 How Long It Takes to See Real Results19:25 Measuring ROI and Tracking AI Value22:12 Real Example: AI Improving RFP Win Rates30:12 Change Management and Driving Adoption31:16 Training, Governance, and Building AI Culture40:12 Managing Risk While Enabling Innovation45:04 What’s Next: AI + Robotics Convergence🔎 Find Out More About Jim SpignardoLinkedIn: https://www.linkedin.com/in/spignardo ProArch: https://www.proarch.com🛠 AI Tools and Resources Mentioned:Microsoft Copilothttps://www.microsoft.com/en-us/microsoft-365/copilotMicrosoft Defender for Cloud Appshttps://learn.microsoft.com/en-us/defender-cloud-apps/what-is-defender-for-cloud-appsMicrosoft Purview (Data Loss Prevention & Information Protection)https://learn.microsoft.com/en-us/purview/Azure OpenAI Servicehttps://azure.microsoft.com/en-us/products/ai-services/openai-serviceOpenAI / ChatGPThttps://chat.openai.comClaude (Anthropic)https://www.anthropic.com/claudeCursor (AI coding assistant)https://www.cursor.sh
Summary95: The Dark Side of Gen AI: When Platforms Move Faster Than Regulation with Jesse Jameson
Mar 1600:47:09Summary readySend us Fan MailWhat 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 Discovery00:45 Introducing Jesse Jameson and the Rise of AI Voice Technology03:15 From Early Internet Marketing to the Age of AI04:22 Joining the ElevenLabs Voice Actors Program06:13 Discovering Discrepancies in Voice Usage and Payments08:29 The Consent Problem and Hidden Licensing Terms10:31 Regulatory Questions and Biometric Data Laws12:15 The Hidden Risks of Using Generative AI Tools17:21 Bias, Control, and the Influence of AI Models26:23 Investigating Platform Abuse and Free Voice Usage36:29 Documenting the Experience and Reporting to Regulators44:06 Practical Advice for Leaders Using New AI Tools🔎 Find Out More About Jesse JamesonLinkedIn: Jesse JamesonSubstack: @jpjamesonYoutube: @jpjamesonWebsite: https://11laudit.comThe 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 MentionedElevenLabs:https://elevenlabs.io/ OpenAI:https://openai.com/ Anthropic:https://www.anthropic.com LLaMA:https://www.llama.com
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