What if the reason you can’t figure something out isn’t that you haven’t thought hard enough? What if part of the answer lives with someone else?

When change is moving quickly, no one person has the whole picture. The knowledge we need is distributed across the people closest to the work, technical experts, skeptics, customers, people navigating risk, and sometimes the person who quietly tried six months ago what everyone else is still debating.

That changes what expertise looks like.

In this episode of Technically Joyful, Gabrielle Kohlmeier explores why connection is not just a nice leadership trait. It is a capability for navigating complexity.

Drawing on her experience leading generative AI transformation inside a Fortune 30 company, Gabrielle shares how what first looked like a technology challenge quickly revealed an interconnected system of people, processes, incentives, risks, dependencies, and knowledge that no one person or function could see alone.

The job wasn’t to know every piece. It was to get better at finding the pieces, connecting them, and exercising judgment across what emerged.

Connection also gives us something else: energy. Sometimes another person gives us the question we hadn’t thought to ask, shows us a possibility we’d stopped seeing, or simply makes a difficult problem interesting again.

Hard things require energy. Change requires energy. Learning requires energy. Sometimes we borrow that energy from one another.

That’s joy as fuel.

In This Episode

• Why no one person has the whole picture
• How distributed knowledge changes what expertise looks like
• Why “Who knows something we don’t?” can be a better question than “Who needs to approve this?”
• How human relationships help knowledge move
• Why accountability is different from solitary knowledge ownership
• How connection can replenish energy for hard things
• How AI can surface missing perspectives without replacing lived knowledge
• Why curiosity says “I can learn” and connection says “I don’t have to learn alone”

Your Rep: Widen the Aperture

Think of one real thing you’re trying to figure out.

Ask your AI tool:

“I’m trying to figure out X. Give me five perspectives I may be missing, who might hold each one, and one question I should ask them.”

Then pick one actual person who holds a perspective you need and ask:

“I’m trying to figure out X. What are you seeing?”

AI can widen your aperture. It can’t give you someone else’s lived knowledge.

One person. One question. One rep.

Sources & Resources

• Paul Leonardi & Tsedal Neeley, “What Managers Need to Know About Social Tools,” Harvard Business Review
• Amanda Palmer, The Art of Asking
• Carol Tavris & Elliot Aronson, Mistakes Were Made (But Not by Me)

Ways to Connect with Gabrielle

Subscribe to Technically Joyful on Apple Podcasts, Spotify, and YouTube: technicallyjoyful.com

Newsletter: technicallyjoyful.com
GK Strategic Advisory: gkstrategic.com
LinkedIn: linkedin.com/in/gabrielle-kohlmeier

How do you lead through AI-driven change when the map hasn’t been drawn yet?

Anna Gressel, partner and global co-head of AI at Freshfields, has built a career exploring questions without established answers, from neuroscience to some of the hardest legal, safety, governance, and strategy questions in AI.

In this conversation, Anna and Gabrielle explore what it takes to move into unfamiliar territory with curiosity, creativity, and sound judgment.

For Anna, the fact that something is new isn’t a reason to avoid it. It can be the reason to explore. That mindset shapes how she approaches novel problems: turning the prism, connecting ideas across disciplines, asking what might still be missing, and “scaffolding forward” toward challenges that haven’t fully arrived yet.

But exploration isn’t the opposite of rigor. Anna works on high-stakes AI matters where safety, compliance, liability, and judgment matter enormously. The joy comes from helping clients solve hard problems, create responsibly, and find a wise path forward.

The conversation also moves from individual AI fluency to organizational strategy. AI often doesn’t create entirely new organizational problems; it throws existing questions into sharper relief. What should we preserve? What needs to change? What is our competitive edge? Are we adopting AI because it serves a strategic goal, or simply for adoption’s sake?

The goal isn’t predicting exactly where AI will be in five years. It’s building capabilities now that create more options later.

In This Episode

• Why unexplored territory can be an invitation rather than a warning
• Turning the prism: connecting ideas across disciplines
• Building AI fluency through experimentation and peer learning
• Why even AI experts still feel behind
• Holding joy, creativity, risk, and judgment at the same time
• Why AI can surface organizational challenges that already existed
• Strategic AI adoption vs. adoption for adoption’s sake
• Building capabilities now to create future optionality
• Unlearning the comfort of familiar patterns

Your Rep: Challenge the Familiar

Think of one thing you hate doing or one familiar process you rarely question.

Ask AI to interview you about how it works today, where the pain points are, and what might be removed, simplified, or done differently.

Then ask: What could I stop doing? What could AI help me automate? What would I redesign if I were starting from scratch?

You don’t have to automate everything. The rep is to challenge the comfort of the pattern and explore what might be possible.

Chapter Markers

02:32 Everyday AI joy: spreadsheets as a thought partner
04:15 Why unexplored territory is worth pursuing
11:00 Turning the prism across disciplines
17:05 Building AI fluency through exploration
22:05 Why even experts feel behind
26:00 Joy, risk, and sound judgment
33:15 How AI surfaces existing organizational challenges
35:35 Why AI adoption needs a strategy
38:15 Building capabilities for an uncertain future
39:25 Unlearning the comfort of the pattern
42:20 Your Rep: challenge a familiar way of working
43:30 What makes the future of AI exciting

Sources & Resources

• Anna Gressel, The AI Drop (https://www.freshfields.com/en/our-thinking/podcasts/the-ai-drop)
• ABA Commission on Women in the Profession + ABA Center for Innovation, 21 Days of AI: A Grit and Growth Mindset Challenge (https://www.americanbar.org/groups/diversity/women/initiatives_awards/grit-project/ai-grit-challenge-home/)
• Sebastian Seung / EyeWire, connectomics and brain-mapping research

Ways to Connect with Gabrielle

Subscribe to Technically Joyful on Apple Podcasts, Spotify, and YouTube: technicallyjoyful.com

Newsletter: technicallyjoyful.com
GK Strategic Advisory: gkstrategic.com
LinkedIn: linkedin.com/in/gabrielle-kohlmeier

Feel like everyone else has figured out AI while you’re still trying to catch up?

Here’s the problem: “caught up” may be the wrong goal.

AI is changing too quickly for any of us to finish learning it. The leaders who will navigate this era best won’t be the people who know everything. They’ll be the people who build the capacity to keep learning, ask better questions, exercise judgment, experiment, and adapt as the ground moves.

In the first episode of Technically Joyful, Gabrielle Kohlmeier explores why curiosity may be one of our most important change strategies in the AI era, especially for accomplished people who are used to being the ones with the answers.

Drawing on her own journey from perfectionism to leading AI transformation, Gabrielle explores growth mindset, digital fluency, intellectual humility, psychological safety, and the power of becoming comfortable being experienced and a beginner at the same time.

And this is where joy matters. Joy is not the opposite of rigor or discipline. It is fuel for exploration. Fear narrows our field of view. Curiosity, interest, and positive emotion can help broaden it, giving us more capacity to see possibilities, take smart risks, and keep learning when the work gets uncomfortable.

Because you don’t need to catch up before you begin. Beginning is how you catch up.

In This Episode

• Why AI fluency is not the same as knowing everything
• The “30% rule” for digital fluency
• Moving from “I don’t know” to “I don’t know yet” to “let’s find out”
• How to be experienced and a beginner at the same time
• How perfectionism can disguise itself as excellence
• Why intellectual humility is different from insecurity
• Why leaders need to model beginnerhood
• How joy can fuel learning and change
• Reframing anxiety as excitement
• Why curiosity is a change strategy

Your Rep: Play the ELI Game

Pick one thing you keep thinking you should already understand.

Ask your AI tool to explain it at progressively deeper levels:

ELI7: Explain it like I’m seven.
ELI12: Explain it like I’m 12. What did you add?
ELI17: I’m 17 and pretty smart. Take me a level deeper.
ELII: Explain it like I’m an intern.
ELIE: Explain like I’m an expert. What are the three things I actually need to understand, and what can I safely ignore for now?

Keep going until you move from “I don’t understand this” to “I have a foothold.”

Then verify what matters. AI can hallucinate, oversimplify, and miss nuance. The goal is not to hand over your judgment. It is to use AI to accelerate curiosity while retaining it.

Sources & Resources

• Tsedal Neeley & Paul Leonardi, The Digital Mindset
• Carol S. Dweck, Mindset
• Reshma Saujani, Brave, Not Perfect
• Amy C. Edmondson, Right Kind of Wrong
• Tenelle Porter et al., “Predictors and Consequences of Intellectual Humility”
• Barbara L. Fredrickson, “The Role of Positive Emotions in Positive Psychology”
• Alison Wood Brooks, “Get Excited: Reappraising Pre-Performance Anxiety as Excitement”

Ways to Connect with Gabrielle

Subscribe to Technically Joyful on Apple Podcasts, Spotify, and YouTube: technicallyjoyful.com

Newsletter: technicallyjoyful.com
GK Strategic Advisory: gkstrategic.com
LinkedIn: linkedin.com/in/gabrielle-kohlmeier