The View from Up Here

GUEST POST from Kellee M. Franklin, PhD.

“Sometimes you have to go up really high to understand how small you really are.” — Felix Baumgartner

These words, spoken by Felix Baumgartner from the edge of space, capture more than the physical awe of the stratosphere. They echo a deeper truth about perspective — one that is essential as we navigate the uncharted territory of artificial intelligence (AI) in learning and development.

Just weeks ago, the crew of NASA’s Artemis II mission soared farther from Earth than any humans in over half a century. From 252,756 miles away, they were not just testing spacecraft systems. They were gaining a new vantage point — on our planet, on human collaboration, and on what is possible when preparation, humility, and shared purpose converge.

And as I prepare to engage with PhD scholars at Thailand’s National Institute of Development Administration (NIDA), where “Wisdom for Sustainable Development” is both motto and mission, I am reminded: the same principles that guide astronauts and skydivers can guide us in building ethical, human-centered AI in the workplace.

The View from Above: A New Lens on Learning

Baumgartner’s jump was not about adrenaline. It was about data, safety, and pushing boundaries to protect future pioneers. Similarly, Artemis II was not just a technical milestone — it was a masterclass in systems thinking, psychological resilience, and real-time decision-making under uncertainty.

In our organizations, AI adoption often feels like a race to automate, to optimize, to cut costs. But true innovation begins not with tools, but with mindset.

Like those astronauts, holistic AI adoption asks us to rise above the noise. It challenges us to see beyond isolated chatbots or content generators and view learning as an integrated ecosystem — one where technology amplifies human potential, not replaces it.

When we elevate our thinking — leveraging AI for personalization, insight, and empowerment — we create experiences that are more human, not less.

Wisdom in the ASEAN Context: Ethics as the Compass

At NIDA, the focus is not just on knowledge — it is on wisdom. The PhD program cultivates leaders who can navigate complex development challenges across Southeast Asia with integrity, evidence-based analysis, and a commitment to the public good.

This ethos is vital as ASEAN nations embrace AI. Regional frameworks like the ASEAN Guide on AI Governance and Ethics emphasize transparency, bias mitigation, and culturally relevant safeguards. Singapore’s Model AI Governance Framework and Indonesia’s National AI Strategy reflect a growing consensus: technology must serve people, not the other way around.

In this context, AI in learning is not just about efficiency. It is about equity — ensuring rural institutions have access to digital tools, that curricula foster ethical reasoning, and that AI literacy is woven into leadership development.

The mission?

To build a talent pipeline that can harness AI for climate action, health, agriculture, and inclusive growth — because sustainable development starts with wise leadership.

Three Human-Centered Design Principles for AI-Enhanced L&D

Drawing from space missions and scholarly insight, three core learning objectives emerge for leaders in this new era:

1. Model Continuous Learning and Psychological Safety

Baumgartner did not jump alone. He had a team — engineers, medics, mentors — supporting him every step. That trust, that safety, is what allowed him to take the leap.

In the workplace, leaders must do the same: embrace vulnerability, normalize growth, and make it safe to fail forward. When AI is introduced, curiosity should be rewarded, not punished. Questions like “How does this work?” or “What if it’s wrong?” are not resistance — they are engagement. Create spaces where teams can experiment, reflect, and learn together. Because innovation thrives not in silence — or silos — but in dialogue.

2. Embed Learning into Workflow and Performance Systems

Artemis II did not just test hardware — it tested human systems. How do crew members exercise in microgravity? How do they respond to emergencies? The answers were not found in a manual, but in integrated, real-time practice.

Similarly, AI-powered learning should live “in the flow of work.” Personalized learning paths, virtual coaching, and just-in-time feedback should be woven into daily tasks — not delayed and minimized for training modules.

And when we measure success, let us reward collaboration, effort, effectiveness, and skill growth — not just outcomes. Because how we learn matters as much as what we learn.

3. Foster AI Fluency with a Human-Centric, Growth Mindset

AI is not a replacement. It is a collaborator — one that can amplify empathy, creativity, and critical thinking.

Begin by having employees create the “raw material” — drafts, ideas, problem statements, visions — before using AI to refine, critique, and expand. This preserves ownership and mastery while leveraging AI’s analytical strength.

Provide clear, role-specific guidelines, prompt libraries, and peer-sharing platforms. Support upskilling with dedicated centers, updated certifications, and incentives. And always maintain human oversight — because trust is built when people feel in control. AI adoption succeeds not when systems are flawless, but when individuals retain agency. It is about designing experiences where people guide the technology — not the other way around.

From Insight to Impact: A Changemaker’s Lens on Coherence in ASEAN

As AI reshapes the global landscape, ASEAN stands at a unique inflection point where technology does not just drive efficiency — it fosters coherence. The rise of the coherence-centric organization marks a shift from fragmented hierarchies to integrated, adaptive systems guided by shared purpose. AI, far from replacing leaders, is redefining leadership itself: elevating it from command-and-control to a higher vantage point — one of wisdom, context, and collective alignment.

In this new architecture, leaders become curators of meaning, using AI to synthesize vast flows of data into clarity. They no longer need to know all the answers but must ask the right questions — infused with cultural insight, ethical grounding, and a sense of wonder at what’s possible. Across ASEAN’s diverse economies, this shift enables a uniquely regional form of innovation: one that balances rapid digital transformation with deep-rooted values of harmony, community, and long-term stewardship.

This vision is already taking root. William Malek, a former Stanford University instructor and business thought-leader now residing in Thailand, has emerged as a recognized global change-maker, guiding corporations and government leaders in embracing coherence-centric models. His work, including a recent collaboration at NIDA with me to share insights with PhD executive-scholars, highlights how leadership grounded in coherence can drive transformative change across sectors.

AI becomes the lens through which leaders see patterns, anticipate disruptions, and align teams around a coherent vision. The future belongs not to those who merely adopt AI, but to those who rise above the chaos and confusion — leading from above the clouds, where data meets wisdom, and technology serves humanity.

The Rhythm of Growth: Making Space for Questions

As I work with diverse executives in Bangkok, I am always struck by how often the most powerful moments come not from answers, but from questions.

• What does ethical AI look like in our context?
• How might we ensure AI serves the many, not the few?
• How might we prepare leaders to navigate uncertainty with wisdom?
• How might we lead with wúwéi — action through non-forcing — so progress flows like water, not against resistance?
• And in cultivating paññā (wisdom) and mettā (loving-kindness), how might we make certain AI serves human dignity, not just efficiency?

These are not technical questions. They are human ones.

And just as the Artemis II crew returned with data that will shape future missions, our conversations in classrooms and boardrooms today will shape the future of work.

Because the stakes are real. AI could boost ASEAN’s GDP by 10–18% and add around $1 trillion by 2030 — but only if guided by strong, forward-thinking leadership. This is not just about technology. It is about trust. About inclusion. About ensuring AI serves the many, not the few.

That future depends on leaders who are not just digitally fluent, but humancentered — balancing data analytics and AI regulations with emotional intelligence and ethical judgment. It calls for strategic upskilling that blends technical mastery with wise decision-making, and for regional coordination that harmonizes policies across borders — from Singapore’s pioneering frameworks to Thailand’s, Malaysia’s, and Indonesia’s emerging AI agencies.

And above all, it demands collaboration: industry and academia, urban and rural, government and community. Because true progress is not measured in GDP alone, but in equitable access, in resilient ecosystems, and in the wisdom to lead with purpose. Coherence and collaboration.

So let us keep dreaming big — above the clouds, beyond the noise. Let us build learning ecosystems that are not just smart, but wise. That are not just efficient, but equitable.

Because the view from up here?

Absolutely worth it!

Image credits: Kellee M. Franklin

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