From AI Hype to Real Business Impact in 39 Minutes
- Gilbert Eijkelenboom
- Sep 3
- 7 min read
MindSpeaking Podcast Episode 35 - Rosanne Werner
🎙️Listen on your favorite channel:
🎧 Spotify
Highlights:
00:01 – Introduction by Gilbert
00:35 – Biggest leadership mistake in data
00:37 – Lead by example drives adoption
02:24 – Habit loop for AI change
04:39 – Making tools easy to use
05:56 – Resistance: trust and relevance
08:02 – Storytelling to gain buy-in
09:26 – Emotions drive decision-making
11:11 – AI fails from unclear goals
13:28 – Translating numbers into stories
14:46 – Insights profile: blue & yellow
17:50 – Tailoring message to audience
18:57 – Tips for active listening
21:16 – Reading body language in meetings
23:24 – AI as sparring partner
24:50 – Five C’s for future skills
27:54 – AI takes on grunt work
29:05 – Neuroscience for better learning
30:24 – Power of group learning
39:22 – Key takeaway: keep learning
Summary
In this conversation, Gilbert Eijkelenboom and Rosanne Werner explore how leaders can drive AI and data adoption by leading by example, using data storytelling techniques, and presenting data to stakeholders in ways that feel relevant, human, and actionable. They cover building trust with stakeholders, gaining stakeholder buy-in, managing stakeholder expectations, and connecting with non-technical audiences. You’ll hear practical ways to reduce friction, form habits, and use stories to drive data impact—without drowning people in jargon or excessive detail.
Data Storytelling Techniques for Business
🎙️ Gilbert Eijkelenboom
Rosanne, welcome to the show.
🗣 Rosanne Werner
Hi Gilbert, thank you for having me.
🎙️ Gilbert
I’m excited about this follow-up—people, resistance, psychology, and more. You built a global data mindset program at Coca-Cola for over 2,000 people. What’s the number one leadership mistake that kills data adoption?
🗣 Rosanne
Not leading by example. When leaders don’t use data to inform choices, they signal that data doesn’t matter. Effective stakeholder communication starts at the top: ask “Do we have the data?”, “What does it tell us?”, “Have we analyzed patterns?”, and challenge assumptions. This sets the tone that presenting data to stakeholders is expected and that business-focused data insights guide decisions.
🎙️ Gilbert
Why don’t leaders lead by example?
🗣 Rosanne
Habits. People default to what’s comfortable. Pushing outside comfort zones to question the status quo is hard.
Building Trust and Managing Stakeholder Expectations
🎙️ Gilbert
Talk about habit formation and social learning—especially for AI success and organizational change.
🗣 Rosanne
There’s a four-step habit loop: cue → craving → response → reward. For AI and analytics, design cues in team rituals. For example, 15 minutes in every weekly team meeting reviewing the dashboard. Over time, it becomes automatic. This supports confidence-building for analysts and makes data storytelling insights part of daily work.
🎙️ Gilbert
How do we reduce friction so employees embrace AI?
🗣 Rosanne
Make the “cookie jar” easy to reach. Intuitive UIs, low-friction access, and quick wins create dopamine hits that reinforce the habit—key for gaining stakeholder buy-in and managing stakeholder expectations.
🎙️ Gilbert
Resistance is inevitable. How do we overcome it—or should that even be the goal?
🗣 Rosanne
Resistance often stems from fear, lack of incentives, or “I don’t trust the data.” Build transparency: show data lineage and use, invite teams into validation, and highlight success stories. Also, make it personally relevant to their role—how business-focused data insights help decisions, efficiency, and career growth. And co-create: don’t push top-down; involve employees early with feedback loops. That’s how you build trust with stakeholders.
Engaging Non-Technical Audiences with Data
🎙️ Gilbert
Devil’s advocate: getting buy-in takes months. How do we get it faster?
🗣 Rosanne
Storytelling. When people feel heard, they remember more with less effort. Use using stories to drive data impact: make it personal—why it matters, what actions to take—so they recall and act.
🎙️ Gilbert
AI programs are often led by technical folks who overestimate rational arguments. Emotions drive decisions, right?
🗣 Rosanne
Yes. Research shows decisions start with emotion; logic justifies after. To influence decisions, connect emotionally first—then land the data. That’s the essence of data storytelling techniques and presenting data to stakeholders effectively.
🎙️ Gilbert
So emotional impact is central. Is that why many AI initiatives fail—or are there other reasons?
🗣 Rosanne
Many fail from unclear objectives. Don’t chase shiny tools or copy competitors. Define the core problem, verify that AI is the right tool (sometimes simple automation suffices), and align with company goals. Otherwise, you get solutions that don’t meet business needs—wasting time, money, and attention.
🎙️ Gilbert
I hear “We need AI” a lot—without a goal. Breaking the problem down helps.
🗣 Rosanne
Exactly. Tackle capabilities step by step.
Avoiding Excessive Detail and Technical Language
🎙️ Gilbert
You’re both analytical and creative—and people-oriented. Advantage?
🗣 Rosanne
Definitely. My finance/data side digs into numbers; my creative side translates insights into stories that resonate—ideal for connecting with non-technical audiences and avoiding technical language.
🎙️ Gilbert
When did you realize you’re both?
🗣 Rosanne
An insights-based personality assessment at Coca-Cola showed me as both blue (analytical) and yellow (creative)—opposite ends of the spectrum. It explained why I love bridging data and people to drive data storytelling insights and transformation.
🎙️ Gilbert
Ever felt misunderstood?
🗣 Rosanne
Not really. I lean on active listening and adapt to my audience—sometimes more analytical, sometimes more creative. It’s understanding stakeholder needs in real time.
🎙️ Gilbert
How do you tailor in everyday conversations?
🗣 Rosanne
Ask open questions, then follow up (“What do you mean by that?” “Can you give an example?”). It shows people they’re heard and deepens the connection—critical for effective stakeholder communication.
🎙️ Gilbert
Tips for being present and a better listener?
🗣 Rosanne
Maintain eye contact and read facial cues. Don’t process everything at once—pick one thing you heard and ask a follow-up or share a brief, relevant story. This balance avoids interrogation-mode and supports gaining stakeholder buy-in.
🎙️ Gilbert
Right—only asking questions can feel intrusive. Sharing a bit yourself builds connection.
🗣 Rosanne
Exactly. Also mirror body language lightly—it helps people feel heard. It’s a “conversation dance.”
🎙️ Gilbert
How do you use body language in meetings when presenting data to stakeholders?
🗣 Rosanne
Match posture and space—don’t crowd relaxed people. Observe gestures and cultural context carefully; a crossed arm can mean different things across cultures. Contextual nuance is where humans still excel versus AI.
Using Stories to Drive Data Impact (with AI as a Partner)
🎙️ Gilbert
Can AI help with buy-in, clarity, or handling executive pushback?
🗣 Rosanne
Yes—as a brainstorming partner. Draft talking points and ask AI for structure suggestions. Use voice trainers to reduce filler words and improve clarity. It’s a feedback loop that sharpens effective stakeholder communication and limiting excessive detail in presentations.
🎙️ Gilbert
How does this support soft skills?
🗣 Rosanne
Think Five Cs: curiosity, creativity, collaboration, critical thinking, communication.
Curiosity: Use AI to explore angles—but you still define the problem.
Critical thinking: Audit AI outputs for bias or hallucinations; keep the human voice.
Creativity: Spot patterns and new approaches with AI as a sparring partner.These remain human skills—AI augments them.
🎙️ Gilbert
Future-of-work reports keep ranking these skills highly—alongside data and AI.
🗣 Rosanne
Exactly. As AI handles repetitive tasks and large-scale analysis, humans focus on complex, ambiguous problems—the valuable, enjoyable work where building trust with stakeholders really happens.
🎙️ Gilbert
So the future looks promising—if we lean into the opportunities.
Understanding Stakeholder Needs Through Neuroscience
🎙️ Gilbert
Should everyone study neuroscience? It seems essential for culture change and habit-building.
🗣 Rosanne
At least the basics. Understanding how the brain learns helps us learn more with less effort—for example, bite-sized learning that moves into long-term memory. Social learning matters too: in groups, we feel safe and remember more. That’s why workshops—with practice, peer teaching, and Q&A—boost retention and adoption of data storytelling techniques.
🎙️ Gilbert
Exactly. Workshops create a very different, active dynamic.
🗣 Rosanne
There’s a rule of thumb: we retain far less from reading alone, and far more when we teach others. Explaining forces us to reprocess and adapt our understanding—accelerating business-focused data insights and team capability.
Rapid Fire
🎙️ Gilbert
Most valuable people skill?
🗣 Rosanne
Networking through active listening. I love hearing people’s stories and remembering how I made them feel—core to building trust with stakeholders.
🎙️ Gilbert
2) What should data professionals know about neuroscience?
🗣 Rosanne
Use it to shape your data story—structure information so the brain remembers and acts. That’s presenting data to stakeholders with impact.
🎙️ Gilbert
3) One tip to improve collaboration with the business?
🗣 Rosanne
Walk in their shoes. Understand workflows, tools, and pain points—understanding stakeholder needs turns insights into outcomes.
🎙️ Gilbert
4) How do you survive being both analytical and creative?
🗣 Rosanne
Embrace it. Dial up analysis for analytical audiences, inspiration for creative ones—tailoring boosts gaining stakeholder buy-in.
🎙️ Gilbert
5) Best way to measure data-driven culture success?
🗣 Rosanne
Adoption and utilization metrics. If tools aren’t used, decisions are likely gut-based. Track logins, time-in-tool, and—crucially—value created.
🎙️ Gilbert
Do organizations measure this consistently?
🗣 Rosanne
Some do—usage is trackable. The quality of use needs feedback: are people getting value or just clicking around? Pair quant with qualitative insights.
🎙️ Gilbert
6) Red flag a company isn’t truly data-driven?
🗣 Rosanne
Gut-over-data decisions and treating data as an IT problem instead of a strategic business asset.
🎙️ Gilbert
7) How can leaders drive AI adoption in resistant teams?
🗣 Rosanne
Make it small and relatable. Example: “Type what’s in your fridge; ask for dinner ideas.” Quick, meaningful wins spark curiosity and lower friction—great for confidence-building for analysts and non-analysts alike.
🎙️ Gilbert
8) One thing AI will never replace in business?
🗣 Rosanne
Human connection and contextual awareness—especially across diverse teams. That’s the heart of effective stakeholder communication.
From Investment to Impact: Getting Value from Data & AI
🎙️ Gilbert
What are you working on now?
🗣 Rosanne
I help companies bridge the gap between tool investment and people empowerment—clarifying roles in the data strategy, helping teams make business-focused data insights faster, and ensuring the human element moves in step with technology so value isn’t left on the table.
🎙️ Gilbert
Where can people follow your work?
🗣 Rosanne
LinkedIn—I share regular insights and welcome discussion.
🎙️ Gilbert
Final takeaway?
🗣 Rosanne
Technology moves fast—keep learning in small steps. Continuous improvement builds the cognitive skills we need. Share success stories—when you teach others, you learn twice.
🎙️ Gilbert
Thank you, Rosanne—loved diving into neuroscience, the human side of data, and how data storytelling techniques help in presenting data to stakeholders and gaining stakeholder buy-in.
🗣 Rosanne
Thank you for having me.
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