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Generative AI is promising us the long run—however for many organizations, it’s quietly doing the other. Workers are drowning in digital exhaustion, leaders are confused by conflicting ROI research, and corporations are deploying instruments with the hope that one thing—something—will “rework” the enterprise.
However know-how isn’t the true drawback. The true barrier is us. Our buildings. Our workflows. Our incentives. Our management muscular tissues that weren’t constructed for the velocity and ambiguity of AI.
What if the largest danger with AI isn’t job loss, compliance, or hallucinations—however the erosion of the soul of labor itself? That spark of possession, creativity, and which means that makes workplaces really feel human?
That is the strain we unpack in my dialog with Rebecca Hinds, Head of the Work AI Institute at Glean, who led the Work Transformation 100 examine—a sweeping assortment of insights from over 100 leaders, technologists, and researchers on what really drives profitable AI transformation.
Her findings reveal a reality that few corporations need to admit: generative AI doesn’t repair a damaged group. It amplifies it. And if leaders don’t redesign how work occurs, AI will merely speed up the dysfunction already in movement.
Take heed to the episode right here on Apple Podcast & go away a evaluate!
AI Is Not a Software Downside—It’s a Workflow Downside
One of many patterns rising from forward-thinking organizations is the shift away from treating AI as a private productiveness device and towards redesigning work on the system stage.
Firms that fail with AI are inclined to bolt instruments onto previous workflows, hoping for effectivity. Firms that succeed re-engineer the workflow itself.
They embed AI into the circulation of labor—not beside it. They rethink crew processes, not simply particular person duties. They redesign incentives and metrics to measure actual worth, not vainness utilization.
This shift is important as a result of, as Rebecca notes, AI magnifies no matter already exists: good processes turn out to be nice, dangerous processes turn out to be painful quicker, and unclear buildings turn out to be chaotic.
When AI amplifies the fallacious issues—overwork, velocity obsession, unclear possession, damaged coordination—the consequence isn’t transformation. It’s burnout.
This Episode is sponsored by Glean:
The AI Transformation 100 is right here — Glean’s Work AI Institute reveals what’s actually 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 classes from leaders really deploying AI at scale. It’s not about what AI might do — it’s about what works, what fails, and what corporations must get proper to make AI actual. One takeaway: AI doesn’t repair damaged programs. It amplifies them.
The Structural Shift Each Group Should Confront
Rebecca and I explored one of the vital ignored truths about AI transformation: organizational construction is now a strategic differentiator.
Some corporations are experimenting with the centralization of AI technique to make sure governance and requirements. Others are decentralizing AI experimentation to empower capabilities and enterprise strains. Essentially the most profitable corporations mix each—standardized ideas with native autonomy.
This hybrid mannequin permits organizations to maneuver quicker with out dropping management. But it surely additionally introduces a deeper problem: conventional hierarchies weren’t designed for a world the place people and AI brokers collaborate dynamically.
That’s why corporations like Moderna, Zapier, and others are starting to rethink the connection between HR and IT, the roles staff maintain, and the way in which groups assemble to get work accomplished. Dynamic, AI-assisted “flash groups,” workflow-specific brokers, and cross-functional AI champions have gotten indicators of a company able to evolve.
However construction isn’t nearly who reviews to whom. It’s in regards to the social structure—how individuals be taught, share info, make selections, and really feel related to their work.
AI doesn’t exchange that structure. It calls for a greater one.
Avoiding the Silent Erosion of the Soul of Work
Maybe essentially the most stunning perception from Rebecca’s analysis is how simply organizations can automate away the very issues that give individuals which means.
When AI drafts each concept, response, or inventive asset, staff lose the “IKEA impact”—the sense of delight and possession that comes from constructing one thing your self. When AI overloads individuals with apps and notifications, digital exhaustion replaces deep pondering. When leaders deal with AI purely as an effectivity engine, they unintentionally strip away craftsmanship, judgment, and the human expertise of labor.
However Rebecca additionally shared how the neatest organizations are defending the soul of labor whereas accelerating transformation. They’re doing this by being intentional—about the place AI enters the workflow, the place people keep within the loop, and the way work is evaluated and acknowledged.
They aren’t avoiding automation; they’re elevating humanity.
And that shift requires a brand new sort of management—leaders who mannequin AI use, who perceive the rhythms of change, who acknowledge the place creativity issues, and who give groups the psychological security and strategic steering to adapt.
Take heed to the episode right here on Apple Podcast & go away a evaluate!
Methods Each Chief Ought to Undertake—With out Breaking the Move of the Article
Rebecca highlighted a number of practices utilized by corporations getting AI proper. All of them share a standard thread: AI transformation is just not about adopting instruments—it’s about adopting behaviors.
- Embed AI straight into workflows so staff don’t must context-switch into separate apps.
- Redesign metrics so AI helps crew success, not particular person vainness KPIs like “device clicks.”
- Pair top-down technique with bottom-up studying by AI champions in every perform.
- Use telemetry information to grasp actual utilization patterns as a substitute of counting on worker self-reports.
- Resist flattening org charts prematurely, ready till AI proves it may possibly rework a job.
- Defend inventive and ownership-driven duties, making certain AI amplifies—not replaces—the human spark.
- Align HR and IT to create a unified method to digital worker expertise, cultural change, and accountable AI adoption.
None of those methods perform as remoted techniques. They work as a result of they’re interconnected—working as a part of a system-level redesign of how work occurs, who does it, and the way success is measured.
That is the sort of transformation AI can speed up—however provided that leaders take accountability for the elements of the system solely people can repair.
Why This Issues Now Extra Than Ever
AI is transferring quicker than organizational working programs can adapt. That hole is the place burnout grows, mistrust festers, and transformation stalls. However the organizations that redesign workflows earlier than redesigning know-how—those that defend which means, possession, and collaboration—won’t solely keep away from these pitfalls. They’ll construct a future-ready workforce geared up to thrive in an age of clever programs.
If you wish to go deeper into the insights behind these methods—together with how 100+ leaders are making AI work inside actual organizations—hearken to the total dialog with Rebecca Hinds on the Future Prepared Management podcast.
This episode is without doubt one of the most actionable AI roadmaps leaders, CHROs, and executives will hear all 12 months—and a reminder that AI doesn’t take the soul out of labor. Poor design does.Good management places it again.
