AI Explored Podcast: Human-First AI Adoption—Getting Your People Ready for Change

Host: Michael Stelzner, Social Media Examiner
Guest: Kristin Gin, Product Marketing Lead for AI Adoption at Microsoft, Founder of Transform Mei Shun
Date: January 6, 2026

Episode Overview

This episode delves into the challenge of adopting AI in organizations, focusing on a human-first approach. While AI promises increased productivity for individuals, translating these gains to the organization requires more than just rolling out tools—it’s about preparing people for real change. Michael Stelzner and AI strategist Kristin Gin discuss misconceptions, resistance points, human-centric frameworks, strategies for change, and the role of leadership and champions in successful AI adoption.

Key Discussion Points & Insights

1. Getting Into AI: A Personal Journey

• Kristin’s Start with AI (01:48): Kristin began experimenting with ChatGPT in late 2022, initially for fun but soon realized its work potential. She noticed a disconnect between individual gains and organizational results, which propelled her to focus on human readiness for AI.
  • Quote [03:37]:
    “Every time I started a conversation where I said, Hey, look at this amazing thing that I just did with ChatGPT, the number one reaction that I got back was, oh, I didn’t even think of that..." — Kristin Gin

2. Common Misconceptions About AI Adoption

• Tool Rollout ≠ Transformation (04:42): Many believe simply purchasing and rolling out AI tools will create instant magic. Traditional tech transitions (e.g., switching email platforms) differ fundamentally from adopting generative AI, which requires changing ingrained workflows rather than just swapping software.
  • Quote [05:16]:
    “When you look at generative AI... it’s very different from a regular tech rollout.” — Kristin Gin

3. The Real Benefits of AI When Done Well

• Organizational Level: Companies ready for AI adoption show 2.4x higher productivity gains (Accenture). Studies indicate up to 80% productivity boost among users (McKinsey).
• Individual Level: AI offloads tedious, time-consuming tasks, allowing humans to focus on higher-value, critical-thinking work.
  • Memorable Moment [07:40]:
    Michael reflects on how AI enables deeper, critical thinking by freeing up cognitive resources.

4. Human Nature: Barriers to Change

• Change Aversion is Deep-seated (12:06):
  • Fear of the unknown
  • Status quo bias—preferring familiar methods
  • Loss aversion—perceiving loss of old routines as greater than potential gains with AI

5. User Types: The Champion, Curious, and Reluctant

• Three User Personas (14:56):
  • Champion: Enthusiastic, proactive, early and heavy AI users.
  • Curious: Open but cautious, will engage if shown clear, relevant use cases.
  • Reluctant: Skeptical, disengaged, sometimes due to previous poor results or discomfort with new technology.
• Distribution Pie Chart (18:25):
  • Champions: ~5%
  • Curious: 50–70%
  • Reluctant: Remaining percentage, varies by organizational culture and industry
    • Quote [18:25]:
      “Most of the users are on the curious side... The reluctant bucket really depends on your industry and company culture.” — Kristin Gin

6. Moving Users Towards Adoption

• Practical Tactics (21:17):
  • Demonstrate “what’s in it for me” with specific use cases.
  • Address misconceptions, such as the notion that using AI is “cheating.”
    • Quote [22:50]:
      “Women just feel like, if I start using AI, I’m cheating because it’s not my work... But it is your work—you’re just doing different types of work.” — Kristin Gin

7. Mindsets & Framework for AI Use

• Four AI Mindsets (25:01):
  1. Assistant: Let AI perform repetitive or simple tasks quickly.
  2. Explorer: Use AI to brainstorm, weigh options, and generate diverse perspectives.
  3. Editor: Improve and refine existing work with AI’s help.
  4. Coach: Guide personal learning, tailoring AI explanations to your context.
  • Nonprofit Example (28:23):
    Kristin used the “explorer” mindset to analyze feedback in minutes that previously took a month.

8. Implementing Change: The Three Layers (30:43)

• Framework for Organizational AI Rollout:
  1. Lead from the Top Down: Leadership sets the vision and models AI adoption.
     • Small gestures (like noting AI-generated agendas) make AI use visible and normalize it.
     • Quote [33:00]: “If your leaders... aren’t actively using AI... that sends a message to your people... But if [they are], it makes it visible.” — Kristin Gin
  2. Inspire from Within: Champions and enablement teams provide grass-roots inspiration, share best practices and successful use cases, and help develop prompt libraries.
  3. Build from the Bottom Up: Equip and empower end-users to develop daily AI habits through training, tips, and recognizing gradual progress.

9. Habit Building & Overcoming Early Setbacks (41:01)

• Incremental Adoption: Start with simple prompts, track experiences, and notice improvements over time.
  • Journaling Prompt Use: Document prompts used and rate the outcomes; see tangible progress week after week.
  • Quote [42:09]: “In the beginning you will have a lot of fairly easy use cases and... some two or three-star ratings. But... you’ll get more comfortable... and see four, sometimes five-star ratings...” — Kristin Gin

Notable Quotes & Memorable Moments

• [06:50]
  “Those organizations who are ready for AI, they see a 2.4 times higher productivity gain than organizations who don’t embrace AI.” — Kristin Gin
• [10:29]
  “You can also look at generative AI like a thought partner... it helps you get better... you can actually start getting a different perspective.” — Kristin Gin
• [22:50]
  “The question I get is, ‘Well, but it’s cheating when I start using AI.’ ... But it is your work.” — Kristin Gin
• [32:55]
  “If your leader sends an email saying ‘agenda was generated with the help of AI,’ that makes it visible. It’s not intrusive, but it lets people know.” — Kristin Gin
• [41:01]
  “You have to help users build habits. That is one of the hardest things... Imagine that every day or once a week, you put down what you used AI for, and a star rating—you’ll see real progress.” — Kristin Gin

Timestamps for Key Segments

• 01:48–04:42: Kristin’s AI journey and the real human challenge of adoption
• 04:42–06:50: Myths of “just rolling out tech” and actual benefits of AI
• 12:06–14:56: Human psychology—change management, biases, and aversion
• 14:56–20:48: Three user personas and their influence on adoption
• 21:17–23:42: How to shift users from reluctant to curious; addressing ethical concerns
• 25:01–28:23: The four AI mindsets/lenses; practical examples
• 30:43–39:16: The three-layer framework for AI transformation in organizations
• 41:01–44:26: Habit building strategies for scalable, lasting change

Actionable Strategies

• Don’t treat AI adoption as “just another software update”—plan for intentional, human-centric change management.
• Identify your champion users and empower them as visible role models or AI mentors.
• Use frameworks and mindsets (assistant, explorer, editor, coach) to help users discover practical, role-relevant ways to start using AI.
• Have leaders regularly make their AI use visible, and encourage sharing AI wins and best prompts.
• Implement low-friction habit-building strategies: daily prompts, tracking progress, normalizing gradual improvements.
• Recognize and address psychological barriers; adoption is uneven and requires continued handholding and communication.

Connect with Kristin Gin

• LinkedIn: Kristin Gin
• Website: transformaishen.com — AI adoption resources, frameworks, and workshop info

For complete show notes and resources, visit socialmediaexaminer.com/aipod.