Twenty-five years ago, I learned to hide my psychology degree in banking. Last week, it was exactly why they invited me back.
The Full Circle Moment
I started my career at the banking industry in São Paulo. Fresh out of university with a psychology degree, I quickly learned it wasn’t valued in that environment. It wasn’t “structured” enough. It wasn’t “business” enough.
I remember a senior banker watching me take notes and saying, almost surprised, “Wow, you’re so structured—you look like an engineer.” He meant it as a compliment.
This week, I returned to São Paulo, to another investment bank. But this time, I came as a psychologist who understands business, transformation, and technology. This time, my background wasn’t just accepted—it was exactly why I was there.
The room was filled with leaders eager to understand not just what AI can do, but how humans and AI can create something greater together.
Augmented Value: The Core Principle
This is what I call Augmented Value—the exponential potential that emerges when human intelligence collaborates with artificial intelligence.
Not replacement. Not automation for automation’s sake. But genuine augmentation, where each amplifies what the other does best.
The leaders I worked with aren’t just preparing for AI adoption. They’re reimagining what their organization can become when human intelligence and artificial intelligence work in true partnership.
Intelligence as a Service: The Game Changer
We’re witnessing a fundamental shift in how organizations access and leverage intelligence.
From samples to comprehensive analysis
For decades, companies made critical decisions based on samples. A subset of data. A representative slice. This was necessary—we simply couldn’t process everything.
AI has removed that limitation.
Now, leaders have access to comprehensive data analysis with possibilities that were unimaginable five years ago. This isn’t just about having more data. It’s about amplifying ideas, testing hypotheses across entire datasets, and discovering patterns that human analysis alone would never find.
The new competitive advantage
The strategic edge now belongs to organizations that can harness this intelligence to ask better questions, make faster decisions, and identify opportunities invisible to traditional analysis.
What is called “Intelligence as a Service” (I heard this first from Peter H. Diamandis) is transforming the very foundation of decision-making. And it’s available to all of us who have access to the digital world (3.9bi people, according to the president of Microsoft).
Three Strategic Priorities: A Real Roadmap
During the workshop, the leadership team identified three critical priorities where AI will drive transformation in 2026:
1. From Market Share to High-Value Projects
The old game of competing for volume is giving way to a more sophisticated strategy: identifying and executing projects that deliver disproportionate value.
AI enables this shift by analyzing opportunity costs, predicting project outcomes, and helping leaders allocate resources where they’ll generate the greatest strategic impact.
It’s not about doing more—it’s about doing what matters most.
2. From Reactive to Proactive Profiles at Entry Level
Perhaps the most exciting transformation is happening with junior talent.
Entry-level professionals are no longer expected to simply respond to requests or execute predefined tasks. With AI handling routine analysis and data processing, these team members are being liberated to propose, to innovate, to challenge assumptions.
The competence profile is shifting from technical execution to strategic thinking, from waiting for direction to identifying opportunities.
3. Organizational Design for Innovation and Legacy
The third priority addresses a tension every established organization faces: how to embrace innovation while maintaining the systems that currently generate value.
The answer isn’t choosing between them—it’s designing organizations that can absorb both.
This means creating structures where legacy data informs AI models, where experimental projects run parallel to established processes, and where different speeds of change coexist productively.
What This Means for Entry-Level Professionals
Entry-level roles are shifting toward human-centered coordination, critical thinking, and AI-augmented execution—work that strengthens trust, quality, and learning loops across the organization.
The new essential competencies:
Human connection and trust-building – Building genuine relationships becomes the differentiator when AI handles routine interactions.
Courageous communication and psychological safety – Speaking up, challenging assumptions, and creating environments where experimentation is safe and learning happens fast.
Problem framing and experimentation – Asking better questions, testing hypotheses, and designing experiments that generate insight before AI can solve anything.
AI-enabled execution with human judgment – Using AI to accelerate analysis while applying human judgment to interpret results and make context-aware decisions.
Culture and change enablement – Acting as change agents who help colleagues adopt new tools and model adaptive behaviors.
Learning agility and cross-functional teaming – Learning quickly, collaborating across functions, and synthesizing diverse perspectives.
Values-aligned service and craft – Ensuring work serves the right purpose and reflects organizational values, even as technology accelerates execution.
What This Means for Leaders
Leadership is undergoing an even more fundamental transformation.
The role shifts from supervising tasks to designing the systems—purpose, culture, operating model, and governance—that enable small teams to use AI to learn faster and deliver trustable outcomes.
Modern leaders must excel at:
Setting direction where AI can’t: purpose, principles, and priorities – These remain uniquely human domains. Leaders define what success means beyond metrics and establish the values that guide decisions.
Building a culture of courage, candor, and learning – Psychological safety isn’t a nice-to-have; it’s infrastructure. Leaders create environments where teams can experiment, fail safely, and learn rapidly.
Architecting the AI operating model – Designing how AI integrates with existing workflows, what decisions it informs versus makes, and where human judgment remains non-negotiable.
Reducing bureaucracy, increasing autonomy with accountability – AI enables small teams to accomplish what once required large departments. Leaders dismantle unnecessary approval layers while building clear accountability.
Leading with trust and human connection – As span of control increases and teams become more distributed, leadership effectiveness depends on trust.
Investing in capability compounding – Learning becomes the primary competitive advantage. Leaders build systems where every project strengthens team capability.
Managing risk and resilience amid volatility – Leaders must anticipate failure modes, build resilient systems, and maintain organizational adaptability in rapidly changing environments.
Measuring outcomes, not output – The shift from activity-based to results-based assessment is critical. Leaders define what impact looks like and measure what matters.
Three Leadership Archetypes for the AI Age
As leaders navigate this transformation, three critical roles emerge
The Translator connects strategy and technology, bridging human goals with AI capabilities. These leaders speak both languages fluently—understanding business objectives while grasping what AI can and cannot deliver.
The Orchestrator redesigns roles and systems for seamless human-AI collaboration. They rethink workflows, eliminate friction points, and create the conditions for augmented teams to thrive.
The Curator of Judgment ensures ethics and sense-making guide AI-human decisions. They ask the questions AI cannot: Should we? What might we miss? Whose voices aren’t represented?
Every leader needs all three capacities, but most will find one is their natural strength and another is their growth edge.
Which one resonates most with you right now?
Augmented Skills: My Personal Journey
Standing in that conference room in São Paulo, I felt the profound symmetry of the moment.
I started my career in banking, moved into technology, and now focus on the human dimensions of transformation. Three distinct chapters that, only in retrospect, reveal themselves as a coherent narrative.
What I once had to hide—my training in understanding human behavior, motivation, and cognition—has become the very thing that makes me valuable in conversations about AI and the future of work.
The “soft skills” that were dismissed as secondary are now recognized as irreplaceable.
I call this Augmented Skills—the unique competitive advantage of professionals who can bridge worlds. Who understand both the technological possibilities and the human realities. Who can speak the language of business strategy and psychological safety. Who can connect the emerging future with the established present.
Living at the Intersection
We are living at an extraordinary inflection point. Not just between two technologies, but between two eras of how humans work, create value, and find meaning in what they do.
I feel tremendous excitement about this moment.
Not because the future is certain—it’s not. Not because the transformation will be easy—it won’t be.
But because for the first time in my professional life, the full range of human capability is not just welcomed but essential.
The investment bank leaders I worked with aren’t just preparing for AI adoption. They’re reimagining what their organization can become when human intelligence and artificial intelligence work in true partnership. When psychological insight informs technological implementation. When strategic vision is amplified by unlimited analytical capability.
I am honored to be a connector between these two worlds, these two eras.
To help leaders see that the most profound technological transformation in generations isn’t really about technology at all—it’s about augmenting what makes us most human: our ability to create, to connect, to imagine what doesn’t yet exist.
The Question That Matters
The future belongs to those who can hold both, who can be both. Who understand that the most powerful question isn’t “What can AI do?” but rather:
“What becomes possible when we combine what AI does best with what humans do best?”
That’s the future we’re building. That’s the conversation we’re having. And that’s why, after twenty-five years and a complete revolution in how we work, I’ve never been more excited about what comes next!