If you’re the leadership of Amazon or Accenture, the answer appears to be a resounding “no.”
Gartner predicts 20% of organizations will use AI to flatten their structures this year, cutting more than half of middle management positions. Accenture exited 11,000 employees deemed untrainable for an AI-driven business. Amazon cut their corporate workforce by 30,000, citing bureaucracy reductions.
Workforce reduction isn’t new. It’s been part of the corporate experience since the East India Company. But cutting is the easy part. It’s an equation. What happens when you’re also asked to completely transform your ways of working at the same time?
Take Robin. The CMO of a major telco. Her board elects to reduce marketing spend by 30% through AI. So she assembles a stable of upper-right quadrant solutions. Writer for copy. Firefly for content. Claude for research. What happens is wild unevenness. A few moving faster. A few resisting. Most feeling just a little lost. This scenario is the norm. Even when AI transformation is a priority, only 14% of employees are offered AI training, with 5% being AI fluent (Google/Ipsos).
Recently McKinsey asserted the critical layer for AI transformation sits two and three levels below the CEO, the SVPs and VPs who own end-to-end business processes. What McKinsey is missing is that the Robins of the world are former brand leaders. Supply chain experts. Manufacturing savants. Few, if any, of them have the level of AI fluency necessary to stitch together solutions while redefining Ted’s technical copywriter job. McKinsey’s own data says only 17% of “N2/3” leadership has the necessary technical skills, recommending a mass upskilling to address the gap.
The lived experience necessary for this transformation sits with the directors and managers. The people high enough to understand how the system works, but close enough to functionally know how the individual roles fit together. Gallup’s research shows teams are 9 times more likely to see a positive impact from AI when it is led by a manager. Not mandated. Led. AI-led transformation is non-linear and demands that a manager move from managing a flow to redesigning it.
When the role shifts from managing-up and managing-down, leaders need to embrace an orchestrator mindset. They need to combine their knowledge and experience to exercise the one thing we keep being told AI can’t replace. Judgment. What does my team actually do? What is the purpose of everyone’s role? What should it be when the historical constraints have melted away and I have a human-AI hybrid system?