What happens when the leaders we trust to guide transformation become the bottleneck slowing it down? In this episode, Monica Marquez—with 25+ years in people transformation at Goldman Sachs, Google, and beyond—reveals why the old equation of effort equals success is breaking down, and what leaders must unlearn to thrive in the age of AI.
The Leadership Crisis Nobody Trained You For
“No one ever really teaches you what it really takes to be a leader. You know what you do really well, but how do you help other people do that too? That’s when I realized it comes down to becoming a really good leader.”
Monica’s origin story captures a universal struggle: being promoted for technical excellence, then discovering that leading people requires completely different skills. She spent her career at organizations like Goldman Sachs, Bank of America, Ernst & Young, and Google realizing that systems weren’t built for everyone—and that the real work of leadership is redesigning those systems to unlock human potential. Today, through her company Flipwork, she helps leaders and teams become what she calls “agentic humans”—people who leverage AI to get ahead rather than getting left behind.
The Command and Control Trap
“Most leadership development still rewards the command and control archetype. The person who has all the answers, the decisive hero. But AI moves so fast that when you think you’ve fixed something, it changes the next day. Leaders are starting to become bottlenecks.”
The research shows the problem clearly: middle management is where AI adoption stalls. These leaders cling to command and control because relinquishing it feels like losing their value. Worse, they have an unspoken fear of managing AI agents—they don’t want to be liable for outputs they don’t fully control. Monica reframes this: treat your AI tools like an artificial intern, not artificial intelligence. You wouldn’t take an intern’s first draft and hand it to leadership. You train them, provide context, and finesse the output. The same discipline applies to LLMs.
Rewriting the Success Equation
“Effort = success is the old equation. That’s pre-AI. The new equation is impact equals success. Output equals success, and impact equals worth.”
This might be the most important shift leaders need to make. When tasks that took 4 hours now take 30 minutes, deeply conditioned beliefs about work ethic get threatened. Monica sees leaders questioning their worth because they’re producing faster. “I was always taught I have to work twice as hard to get half as far,” she shares. “Now what used to take me 10 hours, I can get done in 4. Am I not worthy anymore of being a high performer?” The answer is to measure impact, not effort—and that requires rewiring beliefs that may be decades old.
Why Individual AI Adoption Doesn’t Scale
“Teams are using AI as individual contributors, but they aren’t using AI in their actual workflows and the handoffs. That’s why leaders are scratching their heads, like, why aren’t we seeing the ROI bubble up into the team?”
Here’s the gap most organizations miss: individuals save an hour or two per day using AI for personal productivity, but the team never sees compounding benefits. The handoffs between team members remain manual. The friction points persist. Monica’s solution is “flip labs”—90-day sprints where teams take one critical workflow, dissect it, and rebuild it with AI. Where can AI handle the $10 tasks so humans can focus on $10,000 decisions? Where should humans remain in the loop? IKEA did this with customer service, retraining displaced workers into design roles. Revenue increased without adding headcount.
Leading Through Uncertainty
“We’re humans wired for certainty, but Agile is a system designed for uncertainty. That’s where the behavioral psychology comes in—how do you help people move forward despite the uncertainty?”
The fundamental challenge is biological: our brains seek certainty, but the only certain thing now is that change will come faster than we can adapt. Monica works with teams to create psychologically safe spaces for experimentation—AB testing old workflows against AI-augmented ones, measuring outputs, and learning from failures. “Sometimes we learn more from the failures than we do the successes,” she notes. The leaders who create permission for testing and learning will pull ahead; those who demand control will become the bottleneck that slows their entire organization.
About Monica Marquez
Monica Marquez is a leadership and workplace AI advisor with 25+ years in people transformation. She coined the “returnship” at Goldman Sachs, helped found Google’s Product Inclusion Council, and now guides leaders and teams to adopt AI, agile, and inclusion practices that drive results through her company Flipwork, Inc.
You can connect with Monica Marquez on LinkedIn and subscribe to her Ay, Ay, Ay! AI newsletter at themonicamarquez.com.
