Using AI at Work: Episode 87 – AIME - Solo Episode - PodEdit - D1

Host: Chris Daigle
Date: January 19, 2026

Episode Overview

In this solo episode, host Chris Daigle delivers a practical, insight-rich guide tailored to business leaders and professionals looking to make the most of AI in the workplace. Instead of featuring an outside guest, Chris shares his recommended AI tool stack for executives heading into 2026 and explores the critical concepts of "thinking in AI," real-world job automation, and strategies for building company-wide AI fluency. Chris’s tone is conversational, accessible, and non-technical—focused on immediate, actionable value.

Key Concepts and Discussion Points

1. Why an AI Tool Stack Matters

Timestamp: 01:00–03:20

• The pace of AI tool development is rapid and confusing for many executives.
• Many tools once seen as essential (e.g., GPT wrappers, plugins) have been replaced as model capabilities expand.
• Chris’s recommended tool stack is designed to be:
  • Best-in-class
  • Durable (not likely to vanish soon)
  • Easy to use
  • Immediately beneficial to knowledge workers

2. The Concept of “Thinking in AI”

Timestamp: 03:25–07:30

• “Thinking in AI” is the shift from seeing AI as a one-off utility (e.g., email writing aid) to routinely considering AI’s potential in any business action.
• Aha Moment: Realizing, “If ChatGPT or Claude can do this, then it could also do this.”
  • “The matrix kind of opens up for the individuals and they go from thinking about using generative AI in this like discrete application... to somebody who every time they're, they're taking an action in the business... [asks] ‘How could AI support this?’” (Chris Daigle, 04:49)
• Three steps:
  • Aha moment: Recognizing new, broader AI potential
  • Reflex: Begin defaulting to, “Let me ask the models,” in everyday situations
  • Evangelist: Sharing these discoveries with teammates—spreading AI fluency throughout the company
• Company-wide knowledge exchange and enthusiasm for AI is the key to real impact; governance is important and will be discussed in a future episode.

3. Will AI Replace My Job?

Timestamp: 07:31–13:17

• Persistent anxiety since ChatGPT 3.5: “Oh no, AI is going to take my job.”
• Chris draws a distinction:
  • Human-level AI: Can do work as a human, with context, relationships, strategy, and judgment.
  • Economic-level AI: Automates and assists tasks and projects, but not entire jobs (roles).
• Key Insight: “Even now, if you were fully enabled with the technology, only about 12% of the knowledge work that's occurring in your industry, your business, can be handled by AI.” (Chris Daigle, 10:42, referencing MIT data)
• AI excels at:
  • Task-level activities (drafting emails, summarizing reports, analyzing spreadsheets)
  • Project assistance (budget cycles, campaign management), but not full project automation
• Limits:
  • Still needs human input for “context, relationships, judgment, strategy, accountability.”
  • Jobs comprise both projects and the tasks—and only a portion are AI-friendly.
• Productivity impact: AI can fully automate 10-15% and significantly assist with 30-40% of most knowledge workers’ tasks; overall, AI should save 100–300 hours per employee per year.
  • “It will be impacting the economics of that role, but it will not be replacing the employee. That's my prognostication.” (Chris Daigle, 12:52)

4. Chris's Recommended 2026 AI Tool Stack

Timestamp: 13:18–16:06

• Fathom (AI Meeting Assistant)
  • Automatically records, summarizes, and contextualizes meetings—builds a documented organizational memory
  • Frees users to focus during the meeting, ensures nothing is missed
  • “...on a more macro level, you're building context of what's happening in the business at a granular level. Very important.” (Chris Daigle, 13:58)
• Perplexity (AI Web Research)
  • Modern alternative to Google for fast, current, accurate research
  • “Next time you need to Google something, plex it instead.” (Chris Daigle, 14:45)
• Comet Browser by Perplexity
  • Offers agentic, AI-powered web browsing; Chrome-like experience
  • Replacing the need for ChatGPT's Atlas browser in Chris’s workflow
• NotebookLM (by Google)
  • A “fantastic resource for creating a learning environment, a knowledge environment for you personally or your team.”
• Gamma
  • AI-powered slide deck and presentation generator; “Instant executive-level decks, slide decks from a prompt.”
• Nano Banana (in Gemini via Google)
  • Image generation; “Google's AI image generator is the kind of top of the pack today as of this recording.”

Tool Stack Recap

Timestamp: 16:07–16:44

• Fathom – AI-powered meeting notes
• Perplexity – Knowledge search and research
• Comet Browser – Future of productive browsing
• NotebookLM – Knowledge and learning management
• Gamma – AI-generated presentations
• Nano Banana – AI image creation

5. Why Community and Collective Intelligence Matter

Timestamp: 16:45–17:46

• Filtering AI information and tool options is impossible solo; community provides collective, cross-functional perspective.
• “Plug in somewhere... Having that, that collective perspective allows for the filtering of all of this information... and you get the benefit of knowing, hey, I got a question about this. Oh, I got somebody, Hey, I got a question about this. Oh, she's really good at that, right?” (Chris Daigle, 17:20)
• Direct encouragement to join AI-forward communities (like Chief AI Officer community) for ongoing learning and implementation.

Notable Quotes & Memorable Moments

• On the “aha” moment and thinking in AI:
  "To me, thinking in AI is that moment when you or somebody on your team, they're working with a tool ... and they have that aha moment. They're like, oh, wait a minute, if ChatGPT or Claude ... can do this, that means it can do this ... and just really the matrix kind of opens up for the individuals."
  — Chris Daigle [04:48]

• On the human/economic-level AI divide:
  "AI is not ready for that job-level work of replacing the CFO, replacing the sales director, replacing the operations manager. And the main reason is that jobs themselves require context, relationships, judgment, strategy, accountability, that in its current state at the beginning of 2026, AI cannot provide that."
  — Chris Daigle [11:58]

• On plugging into community:
  “If you're doing this on your own, you're missing out on the power of this kind of like collective intelligence... Plug in somewhere, find that group... [where] they're as enthusiastic about discovering AI and becoming fluent in AI as we are in the Chief AI Officer community.”
  — Chris Daigle [17:10]

• On assessing real impact:
  "If that's what you got from your AI enablement efforts inside of your organization, that matters. Depending on the size of your organization especially, it really matters."
  — Chris Daigle [12:26]

Major Timestamps

• 01:00: Why an AI tool stack matters for leaders
• 03:25: “Thinking in AI”—concept and organizational impact
• 07:31: Will AI truly replace jobs?
• 10:42: Data on current AI job/task automation (MIT report)
• 13:18: Chris's 2026 AI tool recommendations
• 16:45: Why you need an AI community
• 17:46: Closing advice and call to action

Takeaways for Business Leaders

• Adopt a durable, proven tool stack: Don’t get distracted by every new AI launch; use proven, executive-approved tools for meetings, research, learning, presentations, and content.
• Foster “thinking in AI” culture: Move your organization from siloed AI experiments to an environment where everyone considers and shares AI-powered process improvements.
• Don’t fear job loss—focus on augmentation: AI will transform how tasks and projects are handled, saving significant time, but won’t replace roles requiring judgment and context (at least for now).
• Leverage communities for speed and clarity: Stay current and avoid analysis paralysis by plugging into cross-disciplinary AI communities.

For free resources and deeper engagement, visit chiefaiofficer.com or join the Chief AI Officer community for ongoing learning.