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Generative AI is promising us the future—but for most organizations, it’s quietly doing the opposite. Employees are drowning in digital exhaustion, leaders are confused by conflicting ROI studies, and companies are deploying tools with the hope that something—anything—will “transform” the business.
But technology isn’t the real problem. The real barrier is us. Our structures. Our workflows. Our incentives. Our leadership muscles that weren’t built for the speed and ambiguity of AI.
What if the biggest risk with AI isn’t job loss, compliance, or hallucinations—but the erosion of the soul of work itself? That spark of ownership, creativity, and meaning that makes workplaces feel human?
This is the tension we unpack in my conversation with Rebecca Hinds, Head of the Work AI Institute at Glean, who led the Work Transformation 100 study—a sweeping collection of insights from over a hundred leaders, technologists, and researchers on what actually drives successful AI transformation.
Her findings reveal a truth that few companies want to admit: generative AI doesn’t fix a broken organization. It amplifies it. And if leaders don’t redesign how work happens, AI will simply accelerate the dysfunction already in motion.
Listen to the episode here on Apple Podcast & leave a review!
AI Is Not a Tool Problem—It’s a Workflow Problem
One of the patterns emerging from forward-thinking organizations is the shift away from treating AI as a personal productivity tool and toward redesigning work at the system level.
Companies that fail with AI tend to bolt tools onto old workflows, hoping for efficiency. Companies that succeed re-engineer the workflow itself.
They embed AI into the flow of work—not beside it. They rethink team processes, not just individual tasks. They redesign incentives and metrics to measure real value, not vanity usage.
This shift is significant because, as Rebecca notes, AI magnifies whatever already exists: good processes become great, bad processes become painful faster, and unclear structures become chaotic.
When AI amplifies the wrong things—overwork, speed obsession, unclear ownership, broken coordination—the result isn’t transformation. It’s burnout.
This Episode is sponsored by Glean:
The AI Transformation 100 is here — Glean’s Work AI Institute reveals what’s really working with AI at work
The AI Transformation 100, authored by Dr. Rebecca Hinds, Head of the Work AI Institute at Glean and Stanford’s Bob Sutton surfaces 100 hard-won lessons from leaders actually deploying AI at scale. It’s not about what AI could do — it’s about what works, what fails, and what companies have to get right to make AI real. One takeaway: AI doesn’t fix broken systems. It amplifies them.
The Structural Shift Every Organization Must Confront
Rebecca and I explored one of the most overlooked truths about AI transformation: organizational structure is now a strategic differentiator.
Some companies are experimenting with the centralization of AI strategy to ensure governance and standards. Others are decentralizing AI experimentation to empower functions and business lines. The most successful companies blend both—standardized principles with local autonomy.
This hybrid model allows organizations to move faster without losing control. But it also introduces a deeper challenge: traditional hierarchies weren’t designed for a world where humans and AI agents collaborate dynamically.
That’s why companies like Moderna, Zapier, and others are beginning to rethink the connection between HR and IT, the roles employees hold, and the way teams assemble to get work done. Dynamic, AI-assisted “flash teams,” workflow-specific agents, and cross-functional AI champions are becoming signs of an organization ready to evolve.
But structure isn’t just about who reports to whom. It’s about the social architecture—how people learn, share information, make decisions, and feel connected to their work.
AI doesn’t replace that architecture. It demands a better one.
Avoiding the Silent Erosion of the Soul of Work
Perhaps the most surprising insight from Rebecca’s research is how easily organizations can automate away the very things that give people meaning.
When AI drafts every idea, response, or creative asset, employees lose the “IKEA effect”—the sense of pride and ownership that comes from building something yourself. When AI overloads people with apps and notifications, digital exhaustion replaces deep thinking. When leaders treat AI purely as an efficiency engine, they unintentionally strip away craftsmanship, judgment, and the human experience of work.
But Rebecca also shared how the smartest organizations are protecting the soul of work while accelerating transformation. They’re doing this by being intentional—about where AI enters the workflow, where humans stay in the loop, and how work is evaluated and recognized.
They aren’t avoiding automation; they’re elevating humanity.
And that shift requires a new kind of leadership—leaders who model AI use, who understand the rhythms of change, who recognize where creativity matters, and who give teams the psychological safety and strategic guidance to adapt.
Listen to the episode here on Apple Podcast & leave a review!
Strategies Every Leader Should Adopt—Without Breaking the Flow of the Article
Rebecca highlighted several practices used by companies getting AI right. They all share a common thread: AI transformation is not about adopting tools—it’s about adopting behaviors.
- Embed AI directly into workflows so employees don’t need to context-switch into separate apps.
- Redesign metrics so AI supports team success, not individual vanity KPIs like “tool clicks.”
- Pair top-down strategy with bottom-up learning through AI champions in each function.
- Use telemetry data to understand real usage patterns instead of relying on employee self-reports.
- Resist flattening org charts prematurely, waiting until AI proves it can transform a role.
- Protect creative and ownership-driven tasks, ensuring AI amplifies—not replaces—the human spark.
- Align HR and IT to create a unified approach to digital employee experience, cultural change, and responsible AI adoption.
None of these strategies function as isolated tactics. They work because they are interconnected—operating as part of a system-level redesign of how work happens, who does it, and how success is measured.
This is the kind of transformation AI can accelerate—but only if leaders take responsibility for the parts of the system only humans can fix.
Why This Matters Now More Than Ever
AI is moving faster than organizational operating systems can adapt. That gap is where burnout grows, distrust festers, and transformation stalls. But the organizations that redesign workflows before redesigning technology—those who protect meaning, ownership, and collaboration—will not only avoid these pitfalls. They’ll build a future-ready workforce equipped to thrive in an age of intelligent systems.
If you want to go deeper into the insights behind these strategies—including how 100+ leaders are making AI work inside real organizations—listen to the full conversation with Rebecca Hinds on the Future Ready Leadership podcast.
This episode is one of the most actionable AI roadmaps leaders, CHROs, and executives will hear all year—and a reminder that AI doesn’t take the soul out of work. Poor design does.Good leadership puts it back.
