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

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

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

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

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

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