The gap is widening, but few are talking about the real story.
In today's attention economy, your value isn't determined by your credentials or years of experience—it's increasingly defined by whether you have access to intelligence-augmenting technology.
What CEOs won't admit publicly: They're already planning significant workforce reductions as agentic AI capabilities mature. The quarterly calls may talk about "augmentation" and "collaboration," but the internal memos tell a different story.
Think about it:
A marketing department that once needed 10 strategists now needs 3 with AI
A software team that required 20 developers now functions with 7
A legal department that employed 15 paralegals now operates with 4
Meanwhile, states were warned about this coming wave. Policy experts and economists sounded alarms years ago, yet minimal preparation has been made for the social safety nets that will soon be strained to breaking point.
These aren't just statistics—they're teachers in underfunded schools, office workers in mid-sized companies, researchers and skilled professionals whose roles have been deemed "AI-optimizable" in confidential wiki’s and strategy documents.
I spoke with a former operations manager last week who told me: "The company first brought in AI tools to 'help us work more efficiently.' Six months later, our team of 12 was down to 5. The CEO's public statement? 'We're investing in our people through technology.'"
This isn't about resistance to change. It's about honesty, preparation, and social responsibility.
The question isn't whether AI will transform work—it's who will bear the costs of that transformation. Right now, it looks like workers will lose jobs, states will shoulder exploding unemployment and social service demands, while shareholders capture all the gains.
We can't wait for markets to solve this crisis. We need actionable policy solutions
NOW:
AI Transition Funds: Require companies implementing AI to contribute to retraining programs proportional to workforce reductions
AI Literacy Infrastructure: Invest in accessible training centers in underserved communities
Progressive AI Taxation: Tax automation-driven productivity gains to fund universal basic services
Public AI Commons: Create government-sponsored AI tools accessible to small businesses and independent workers
Algorithmic Impact Assessments: Mandate transparency about AI deployment and its workforce effects
Along with the AI Design Corps, I'm establishing a coalition of business leaders, policymakers, and educators to draft model legislation addressing the intelligence divide. We'll be presenting recommendations to state legislative committees next quarter.
Will you join us in building these solutions? Whether you're a technologist, policy expert, educator, or concerned citizen, we need your voice.
Reply with "I'm in" if you'd like details on our first virtual roundtable.
What are you seeing in your industry? Are executives being honest about their AI replacement plans? And what solutions do you believe would make a difference?
