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

Hosted by Chris Daigle

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128

Latest episode

Nov 2026

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EN-US

About the show

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.

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60 recent

November 9, 202651 min

How Generative Engine Optimization Changes the Way Customers Find You with Justin Inman

AI search visibility means little if the recommendation gets your business wrong. In this episode, Chris sits down with Justin Inman, founder and CEO of emberos and a former Google enterprise growth leader, to explore how AI-generated answers shape brand discovery. They discuss generative engine optimization, the shift toward zero-click search, and why accurate recommendations depend on signals across your website, reviews, publishers, and creators. Justin explains how his team approaches AI brand management by tracing the sources behind inaccurate answers and identifying which information to correct. The conversation covers testing customer questions across chatbots, the limits of visibility scores and content shortcuts, and the challenge of measuring AI-assisted purchases. Justin also shares how Granola, Claude, and HubSpot support his meeting preparation, with human review remaining essential. Listen to learn what to check first and how to assess whether your brand is being recommended for the right reasons. Chapters: (00:00) Introduction (03:10) How AI Recommendations Change Brand Discovery (12:00) AI Brand Management and the Brand Knowledge Graph (13:39) Generative Engine Optimization Beyond Traditional SEO (21:18) When AI Gets Your Brand and Products Wrong (24:29) Tracing and Correcting Inaccurate AI Answers (26:33) Running an AI Search Visibility Audit (30:32) Why Internal AI Agents Need Fresh Context and Human Review (37:04) AI Meeting Preparation with Granola, Claude, and HubSpot (40:49) Testing AI Recommendations with Real Customer Questions (42:36) Measuring AI-Assisted Purchases in a Zero-Click World Resources: 🔎 Find Out More About Justin Inman: Justin Inman on LinkedIn: https://www.linkedin.com/in/jinman11/ emberos | AI Brand Management: https://www.emberos.ai 🛠 AI Tools and Resources Mentioned: Granola | AI Meeting Notes: https://www.granola.ai/ The AI Notepad for back-to-back meetings Claude | AI Assistant: https://claude.ai/ Claude Help Center HubSpot | CRM Platform: https://www.hubspot.com/ Homepage Support the show

November 2, 202649 min

How AI-Enhanced Virtual Assistants Help Businesses Scale with Joe Rare

What changes when AI-enhanced virtual assistants take on more of your business operations? In this episode, Chris sits down with Joe Rare, business builder and founder of Level 9 Virtual, to explore how human-AI collaboration can expand team capacity while keeping people responsible for direction, quality, and customer relationships. Joe explains how his team combines AI analysis with human follow-up to reactivate cold leads, support revenue recovery, and build business workflows. The conversation covers where AI workflow automation creates value, why some implementations add work without improving results, and how leaders can decide between employee AI training and hiring skilled support. Joe also shares how he uses AI reporting to make faster business decisions, the 1-3-1 framework for turning problems into recommendations, and his approach to learning with Google’s NotebookLM. Listen to identify practical ways to delegate more effectively, strengthen execution, and preserve the human relationships your business depends on. Chapters: (00:00) Introduction (03:20) Building Businesses Run by Virtual Assistants (06:41) The 10-80-10 Model for Human-AI Collaboration (07:52) AI-Enhanced Virtual Assistants for Lead Reactivation (11:32) Human Quality Control for AI Workflows (18:15) Why AI Automation Fails to Deliver Business Value (21:55) Employee AI Training vs. Hiring Skilled Support (27:07) AI Reporting and the 1-3-1 Decision Framework (32:31) AI Upskilling and Employee Accountability (37:55) Learning AI with Personalized Lessons and NotebookLM (42:34) Keeping Customer Relationships Human as AI Scales Resources: 🔎 Find Out More About Joe Rare: Joe Rare | Business Systems and Strategic Delegation: https://joerare.com/ Joe Rare Level 9 Virtual | Virtual Staffing and Revenue Recovery: https://level9virtual.com/ Level 9 Virtual 🛠 AI Tools and Resources Mentioned: Google NotebookLM / Notebook | Learning and Audio Overviews: https://notebook.google/ AI Research Tool & Thinking Partner ChatGPT: https://chatgpt.com/ Claude: https://claude.com/ Grok: https://grok.com/ Google Gemini: https://gemini.google.com/ 1-3-1 Decision Framework: One clearly defined problem, three possible solutions, and one recommended action. 10-80-10 Human-AI Workflow: Humans define the task, AI handles the heavy lifting, and humans review the result. Support the show

October 26, 202650 min

How to Use AI for Leadership, Employee Coaching, and Development with Jon Harmeling

Can AI for leadership help you give your people more attention? In this episode Chris sits down with Jon Harmeling, a Chick-fil-A Operator, Army veteran, and former West Point instructor, to explore how leaders can turn AI productivity gains into better employee coaching and development. Drawing on his restaurant experience and his book, Frontline AI Leadership , Jon shares a practical framework: Machines do. Managers decide. Leaders develop. Chris and Jon discuss using AI to track employee goals, recognize overlooked contributions, prepare for difficult conversations, and follow through on commitments. They also examine how to measure real AI time savings, reduce context switching, and keep human judgment at the center of workplace automation. Listen to learn how to reinvest the time AI creates in stronger relationships and more intentional leadership. Chapters: (00:00) Introduction (06:06) Management vs. Leadership and the AI Capacity Dividend (15:51) Making Time for Employee Coaching and Development (18:44) Reducing Context Switching When Working with AI (20:37) Measuring Real AI Time Savings and Accountability (23:28) Frontline AI Adoption, AI Search, and Data Privacy (27:49) From AI Agents to Writing Frontline AI Leadership (33:01) Machines Do. Managers Decide. Leaders Develop. (35:50) Tracking Employee Goals with AI (39:22) AI Scheduling and the Limits of Automation (41:19) Preparing for Difficult Conversations with AI Resources: 🔎 Find Out More About Jon Harmeling: Website: https://www.jonharmeling.com Frontline AI Leadership Book: https://www.jonharmeling.com/book https://www.amazon.com/dp/B0HNDTHR36 LinkedIn: https://www.linkedin.com/in/jonharmeling/ X: https://x.com/JonHarmeling 🛠 AI Tools and Resources Mentioned: Claude and Claude Cowork: https://claude.com/product/cowork ChatGPT: https://chatgpt.com Support the show

October 19, 202647 min

How to Use AI Roleplay to Improve Sales Conversations and Close More Deals with Paul Burani

What if your sales team could practice its toughest conversations before speaking to real customers? In this episode, Chris sits down with Paul Burani, Co-Founder and CRO of Atlas Primer, to explore how AI sales roleplay brings realistic practice and personalized feedback into sales training. They discuss how short, regular sessions help teams develop human skills, prepare for objections, and approach high-stakes conversations with greater confidence. Paul explains how to tailor simulations to specific prospects, incorporate your sales methodology, and connect AI sales coaching to measurable business outcomes. He also shares his AI workflow for following up on stalled deals and the data privacy questions leaders should ask before adopting new tools. Listen to discover practical ways to strengthen your team’s skills and make better use of the time AI saves. Chapters (00:00) Introduction (06:19) How Atlas Primer Builds Conversational Skills (09:25) Getting Sales Teams to Embrace AI Coaching (13:05) Building a Regular Sales Practice Habit (14:24) Inside an AI Roleplay Training Session (22:17) Preparing for Specific Prospects with LinkedIn (24:13) Connecting Sales Training to Business Outcomes (29:41) Adapting Sales Methodologies and Extending Coaching (32:53) The Handoff: AI Follow-Ups for Stalled Deals (36:13) Data Privacy Questions Every Leader Should Ask (41:46) Reinvesting AI Time Savings Without Burning Out Teams Resources: 🔎 Find Out More About Paul Burani: LinkedIn: https://www.linkedin.com/in/pburani linkedin.com Atlas Primer: https://atlasprimer.com/ Atlas Primer Roleplay: https://roleplay.atlasprimer.com/ Atlas Primer 🛠 AI Tools and Resources Mentioned: Gong: https://www.gong.io/ OpenClaw: https://openclaw.ai/ HubSpot: https://www.hubspot.com/ Tableau: https://www.tableau.com/ Microsoft Power BI: https://www.microsoft.com/en-us/power-platform/products/power-bi The AI-Driven Leader by Geoff Woods: https://www.aileadership.com/book Support the show

October 12, 202647 min

Why AI Adoption Fails Even When You Have the Right Tools with Rob Collie

What if your AI tools aren't underperforming because of the technology, but because they don't know your business? In this episode Chris sits down with Rob Collie, CEO of P3 Adaptive, former Microsoft Power BI developer, and author of Fair Game: Customizing AI to Your Business Is Easier Than You Think, to explore why buying ChatGPT or Claude subscriptions isn't enough to achieve meaningful enterprise AI adoption. Rob explains the "knowledge cliff" that prevents generic AI tools from delivering reliable business results, why employees shouldn't be responsible for repeatedly teaching AI how their company works, and how leaders can build customized AI systems grounded in company knowledge. Through practical examples involving Claude Desktop, Claude Cowork, Notion, and AI-assisted workflows, they discuss context engineering, organizational knowledge, trusted sources of truth, and AI governance. Listen to discover how leaders can move beyond AI experimentation and create systems their teams can actually trust and use. Chapters: (00:00) Why AI Needs Trusted Business Knowledge (02:53) From Microsoft Power BI to the AI Revolution (05:25) Why Buying AI Subscriptions Isn't Enough (09:22) The Claude Desktop Experiment That Changed Everything (11:46) The Knowledge Cliff: Why AI Doesn't Know Your Business (14:16) Bot Sitting and the Hidden Cost of AI Adoption (16:50) Why Business Leaders Must Own AI Context (21:48) How to Customize AI with Claude Cowork (24:12) Building a Personalized AI Editor (39:24) Fair Game and the Future of Business AI Resources: 🔎 Find Out More About Rob Collie LinkedIn: https://www.linkedin.com/in/robcollie/ P3 Adaptive: https://p3adaptive.com/ Raw Data with Rob Collie Podcast: https://p3adaptive.com/rawdatapodcast/ The Goldilocks Altitude Newsletter (Substack): https://goldilocks1.substack.com/ Fair Game: Customizing AI to Your Business Is Easier Than You Think by Rob Collie: https://www.amazon.com/Fair-Game-Customizing-Business-Easier/dp/1615470948 🛠 AI Tools and Resources Mentioned: ChatGPT (OpenAI): https://chatgpt.com/ Claude: https://claude.ai/ Microsoft Copilot: https://copilot.microsoft.com/ Notion: https://www.notion.so/ OpenAI Codex: https://openai.com/codex/ Model Context Protocol (MCP): https://modelcontextprotocol.io/ Support the show

October 5, 202649 min

How AI Security Helps Companies Adopt Generative AI Safely with Steven Walchek

How do you scale enterprise AI without exposing the sensitive data your business cannot afford to lose? In this episode Chris sits down with Steven Walchek, Founder and CEO of Liminal, to explore enterprise AI security, AI governance, data privacy, and how leaders can safely accelerate generative AI adoption. Steven explains how enterprises can protect sensitive information before it reaches an LLM, why governance needs to enable AI adoption rather than block it, and how AI agents and tools like Claude Code are changing what teams can build and automate. He also shares practical AI use cases, including his Pocket Sales Engineer and AI-powered product prioritization, showing how non-engineers can turn ideas into working applications without writing code. Leaders should listen for a practical look at balancing AI security, governance, productivity, and innovation as generative AI spreads across the enterprise. Chapters: (00:00) Introduction (03:47) The Data Privacy Risks Behind Generative AI (07:13) How Enterprise AI Security and Governance Work (10:29) Protecting Sensitive Data Before It Reaches an LLM (18:22) How AI Coding Tools Are Changing Software Development (23:16) A Crawl, Walk, Run Strategy for Enterprise AI Adoption (28:52) Why AI Governance Should Enable Innovation, Not Block It (31:53) AI Agents, Automation, and the Enterprise Complexity Problem (37:30) Building a Pocket Sales Engineer With Generative AI (42:44) How to Build AI Applications Without Writing Code Resources: 🔎 Find Out More About Steven Walchek Steven Walchek on LinkedIn https://www.linkedin.com/in/swalchek/ Liminal https://www.liminal.ai/ Liminal Resources and Blog https://www.liminal.ai/resources/blog 🛠 AI Tools and Resources Mentioned: ChatGPT https://chatgpt.com/ Claude https://claude.ai/ Claude Code https://claude.com/product/claude-code OpenAI Codex https://openai.com/codex/ Perplexity https://www.perplexity.ai/ Grok https://grok.com/ Meta AI https://www.meta.ai/ Gong https://www.gong.io/ OpenClaw https://github.com/openclaw/openclaw Support the show

September 28, 202651 min

How AI Workflow Automation Changes the Way Your Business Works with Justin Watt

Why do companies invest in AI without changing how work gets done? In this episode Chris sits down with Justin Watt, co-founder and CEO of Switchboard, to examine why AI adoption often stalls after teams get access to tools. They explore the move from individual AI use to AI workflow automation that supports work across departments. Justin explains why successful business process automation depends on clear handoffs, usable data, and the right permissions. He shares how simplifying a complicated proposal process created a practical opportunity for AI, then discusses how leaders can find a first use case and build the shared context needed for AI agents. Listen for a grounded approach to enterprise AI implementation that starts with the work your team actually does. Chapters: (00:00) Why AI Adoption Hasn’t Changed the Business (02:23) From Individual AI Use to Team Workflows (05:10) Where AI Workflow Automation Fits (09:57) Finding the First Business Process to Automate (16:12) Mapping How Teams Actually Work (20:13) Choosing an Internal AI Implementation Lead (24:42) Human Oversight for AI Agents (30:01) Building Shared Context From Business Data (36:15) AI Tools for Meetings and Delegation (40:11) Using Claude Code for Business Workflows (43:15) Automating Recurring Updates With an AI Skill Resources: 🔎 Find Out More About Justin Watt Switchboard: https://www.withswitchboard.com/ Justin Watt on LinkedIn: https://ca.linkedin.com/in/wattjustin 🛠 AI Tools and Resources Mentioned: Granola: https://www.granola.ai/ Claude, Claude Code, and Claude Cowork: https://claude.ai/ ChatGPT and Codex: https://chatgpt.com/ and https://openai.com/codex/ Grok Bot: https://grok.com/ Notion: https://www.notion.so Support the show

September 21, 202650 min

How to Make Enterprise AI Adoption Successful: Inside the Chief AI Officer Role with Denis Romanovskiy

AI transformation does not start with a massive AI project. In this episode Chris sits down with Denis Romanovskiy, Chief AI Officer at SOFTSWISS, to explore what enterprise AI adoption looks like when someone is actually responsible for turning the technology into business results. Denis explains why the Chief AI Officer role sits at the intersection of technology, operations, change management, security, and employee enablement. They discuss how companies can identify internal AI leaders, why Denis prefers measuring "economic effect" before chasing traditional ROI, and how small employee-led experiments can build momentum across an organization. Denis also shares lessons from SOFTSWISS's company-wide AI hackathon, including how non-technical employees became active builders when given the right support. For leaders trying to move AI from scattered experimentation into everyday work, this conversation offers a practical look at building adoption, accountability, and human oversight at scale. Chapters: (00:00) Introduction (01:54) What a Chief AI Officer Actually Does (05:35) Why Businesses Need Clear AI Ownership (07:26) Choosing the Right Internal AI Leader (14:38) Measuring AI by Economic Effect, Not Just ROI (19:45) How to Choose AI Use Cases That Build Momentum (22:37) Turning an AI Hackathon Into a Business Tool (27:34) Why Executive Support Drives AI Adoption (29:16) What Non-Technical Employees Can Build With AI Resources: 🔎 Find Out More About Denis Romanovskiy LinkedIn: https://www.linkedin.com/in/dionique SOFTSWISS: https://www.softswiss.com 🛠 AI Tools and Resources Mentioned: OpenAI: https://openai.com Anthropic: https://www.anthropic.com + NotebookLM: https://notebooklm.google Support the show

September 14, 202644 min

Why AI Pilots Fail: How to Escape AI Pilot Purgatory and Scale Enterprise AI with Ronnie Kwesi Coleman

Most AI pilots do not fail because the technology is weak. They fail because the organization was never prepared to turn the experiment into a real operating workflow. In this episode Chris sits down with Ronnie Kwesi Coleman, CEO of Puntt AI and a three-time founder focused on the future of work. They unpack the mistakes that keep enterprise AI stuck in AI pilot purgatory, why expert judgment matters more than simply giving AI more data, how AI agents should learn alongside experienced employees, and why productivity without measurable business outcomes and AI ROI is the wrong target. They also explore the shift from creation to review as a new AI bottleneck, the limitations of the "single company brain" idea, and the risks of building an enterprise AI strategy around one provider. Listen to learn how leaders can move AI pilots from experimentation into production while preserving the judgment, integrations, and strategic flexibility required for scaling AI across the organization. Chapters (00:00) Introduction (03:04) How to Choose the Right AI Pilots (05:47) The Five Deadly Sins of AI Pilot Purgatory (09:46) Starting Small While Planning to Scale (14:04) Moving From AI Productivity to Business ROI (18:02) Capturing Expert Judgment With AI Agents (23:07) How Much Should You Trust AI? (29:04) AI Agents and the New Review Bottleneck (32:33) Why the Single AI Brain Model Falls Short (38:22) Avoiding AI Vendor Lock-In and Hiring Agents Resources: 🔎 Find Out More About Ronnie Kwesi Coleman Puntt AI https://www.puntt.ai/ Ronnie Kwesi Coleman on LinkedIn https://www.linkedin.com/in/ronnie-kwesi-coleman/ 🛠 AI Tools and Resources Mentioned: Puntt AI https://www.puntt.ai/ Anthropic Claude https://www.anthropic.com/claude OpenAI https://openai.com/ Meta https://www.meta.com/ Fall in Love with the Problem, Not the Solution by Uri Levine https://www.simonandschuster.com/books/Fall-in-Love-with-the-Problem-Not-the-Solution/Uri-Levine/9781637746608 Support the show

September 7, 202646 min

How to Use AI Without Losing Human Judgment: AI Decision-Making and the Future of work | Rana Gujral

AI can make your team faster while quietly making them worse at thinking. In this episode Chris sits down with Rana Gujral, cognitive AI leader, CEO of Behavioral Signals, and author of The AI Instinct , to explore what happens when AI moves from a productivity tool into the cognitive infrastructure businesses use to make decisions. Rana explains why leaders need to distinguish between employees who are genuinely deciding and those who are simply approving AI output, how reversibility can determine when rigorous decision trails are necessary, and why organizations should deliberately preserve opportunities for people to exercise judgment without AI. He also shares his personal process for working with AI on strategic decisions and challenges leaders to measure what AI is doing to their team's thinking, not only their output. Listen to learn how to capture AI's advantages without quietly outsourcing the judgment your organization will need when the easy answers disappear. Chapters: (00:00) Introduction (03:34) AI as Cognitive Infrastructure (07:47) Building Rules for Human and AI Decisions (10:46) Preventing Automation Bias and Protecting Human Judgment (13:42) Redesigning Organizations Around AI Decision-Making (19:58) How AI Sculpts Human Attention (22:40) Are Your People Deciding or Just Approving? (25:14) When AI-Assisted Decisions Need an Audit Trail (28:26) Rana's Personal Process for Strategic AI Decisions (31:06) Building Senior Talent When AI Does the Junior Work (39:24) What Is AI Doing to the Way Your Team Thinks? Resources: 🔎 Find Out More About Rana Gujral Rana Gujral Website: https://ranagujral.com/ Rana Gujral on LinkedIn: https://www.linkedin.com/in/ranagujral Behavioral Signals: https://behavioralsignals.com/ Book: The AI Instinct: The Future of AI and Human Decision-Making https://ranagujral.com/book 🛠 AI Tools and Resources Mentioned: Claude: https://www.anthropic.com/claude Chat GPT: https://openai.com/ Gemini: https://gemini.google.com/ Chief AI Officer: https://chiefaiofficer.com/ Wiley: https://www.wiley.com Support the show