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

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

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

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