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

Chris Daigle
  • 3.7 (6)
  • MANAGEMENT
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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. 6D AGO

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

    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

  2. MAR 16

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

    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

  3. MAR 9

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

    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

  4. MAR 2

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

    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

  5. FEB 23

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

    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

  6. FEB 16

    91: Using AI in Sales to Automate Go-to-Market Execution with Jason Eubanks

    Most companies are experimenting with AI. The leaders who win are rebuilding around it. In this episode, Chris Daigle sits down with Jason Eubanks, Co-Founder and CEO of Aurasell AI, to explore why incremental AI experiments aren’t enough—and why go-to-market teams must shift to an AI-native operating model. Jason explains why simply plugging AI into legacy systems won’t change your productivity model, and why companies that fully embrace intelligent automation now will create an advantage competitors won’t be able to close. They discuss how AI-native architecture can double productivity, eliminate CRM busywork, and cut onboarding time for sales teams by 50%. From removing copy-and-paste workflows to automating outreach, enrichment, and follow-up, Jason outlines what happens when AI doesn’t just provide insights—but executes. He also introduces Aurasell’s new GTM operating system that sits on top of existing CRMs like Salesforce and HubSpot, plus an agent builder that enables powerful AI-driven workflows through simple natural language prompts. If you’re looking to unlock real productivity gains—not just incremental improvements—this episode outlines what that shift actually requires. 🔎 Find Out More About Jason Eubanks LinkedIn: https://www.linkedin.com/in/jason-eubanks-a775ba 🌐 Learn More About Aurasell AI https://aurasell.ai 🛠 AI Tools and Resources Mentioned Aurasell GTM Operating System https://www.aurasell.ai Chat Gpt https://chatgpt.com/  Salesforce https://www.salesforce.com/  HubSpot https://www.hubspot.com  Chapters: (00:00) Introduction (01:17) What “AI-native” really means (beyond chat wrappers) (03:02) The productivity gap: why incremental AI adoption fails (06:45) Urgency explained: first movers and 2–3x productivity gains (10:08) Fixing the broken B2B sales productivity model (12:27) Case study: carving out teams to go all-in on AI (15:07) The AI-native GTM platform and unified customer journey (21:26) Cutting onboarding time by 50% with intelligent automation (26:10) Eliminating sales busywork and manual CRM toil (28:46) Agentic workflows: natural language → automated execution

    44 min

  7. FEB 9

    90: Using AI at Work to Create an AI Quality Assurance System with Hernan Lardiez

    Chris Daigle sits down with Hernan Lardiez, COO of RagMetrics, to break down AI evaluations (evals) and why monitoring matters when you put GenAI into production especially in regulated or high-risk environments. Hernan explains what “good evals” actually look like without getting lost in technical weeds: building test datasets, measuring accuracy and consistency, and then continuously re-testing so you can catch drift before it becomes a business problem. They compare the “spreadsheet + spot check” approach to automated eval pipelines that can run fast, repeatable tests at scale. The conversation also covers a practical way to think about pre-production testing vs. in-production monitoring, why token usage and cost should be part of evaluation, and how small RAG tuning decisions (like Top-K chunks) can improve accuracy while cutting token consumption. If you’re leading AI adoption and you want confidence not guesswork this episode will help you build the control points and guardrails to scale GenAI safely. 🔎 Find Out More About Hernan Lardiez Hernan Lardiez on LinkedIn https://www.linkedin.com/in/hlardiez/ RagMetrics https://ragmetrics.ai/ 🛠 AI Tools and Resources Mentioned RagMetrics - https://ragmetrics.ai The AI Exchange (Rachel Woods) - https://www.theaiexchange.com/ Chief AI Officer -  https://www.chiefaiofficer.com/ 📌 Chapters 00:00 Why regulated industries can’t “hope” with AI 02:04 What model evaluations (evals) actually are 05:08 The two audiences: business owner vs builders 08:52 Pre-production testing vs in-production monitoring 14:23 Why “monitoring is required” to reduce risk 16:14 Manual spreadsheet grading vs automated evals 18:01 Building test datasets + injecting through the pipeline 31:21 Measuring accuracy AND token consumption (cost) 34:01 Continuous evals to catch drift over time 42:11 RAG tuning: Top-K chunks, accuracy vs noise, token savings 49:21 Evals as “low-cost insurance” for production AI 50:27 Closing advice: control points + IT boundaries In this clip from the Using AI at Work podcast, we explore the challenges of AI implementation, particularly for organizations in regulated markets. The discussion highlights the critical role of effective risk management in navigating potential outcomes. We identify key stakeholders, like the business owner and the development team, who are crucial for understanding AI requirements and ensuring compliance. This session emphasizes the importance of strategic ai leadership and how ai business can integrate these considerations for successful operations management.

    53 min

  8. FEB 2

    89: Using AI at Work to Lead Through Change Without Losing Trust with Bill Gallagher

    Chris Daigle sits down with Bill Gallagher, leadership expert and longtime advisor to executives, to explore what it really means to use AI at work during periods of rapid organizational change. Bill shares why technology alone never drives transformation and how trust, clarity, and human leadership remain the deciding factors when AI enters the workplace. The conversation focuses on how leaders can introduce AI without creating fear, resistance, or confusion, how to avoid treating AI as a shortcut instead of a responsibility, and how strong leadership principles apply even more as automation increases. This episode is a practical guide for executives who want to adopt AI while maintaining credibility, alignment, and trust across their teams. 🔎 Find Out More About Bill Gallagher https://www.linkedin.com/in/billgall/ 🛠 AI Tools and Resources Mentioned ChatGPT Internal AI tools within organizations 📌 Chapters 00:00 Introduction to Bill Gallagher 04:12 Leadership challenges during AI driven change 10:08 Why trust matters more than technology 17:26 How leaders should talk about AI internally 23:41 Avoiding fear and resistance during AI adoption 30:05 The human role in AI driven organizations 37:18 Leading with clarity in times of uncertainty 43:02 Final thoughts on leadership and AI 48:10 How to connect with Bill Gallagher

    51 min
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Ratings & Reviews

3.7
out of 5
6 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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