AI, Demographics, and the Future of Work: What McKinsey’s “Dependency and Depopulation” Report Gets Right (and What It Misses)
McKinsey’s Dependency and Depopulation report lays out the stark realities of what happens when fewer workers are supporting more retirees, when economic productivity slows, and when public finances stretch thin under the weight of aging populations.
The report pulls no punches on the numbers:
By 2050, Japan’s workforce will decline by 24%, and South Korea’s by 35%. The US will face similar challenges.
OECD nations will need to double productivity growth rates just to keep their economies stable.
Aging populations could slash global GDP growth by 1.5 to 2 percentage points per year—potentially costing the world $40 trillion by 2050.
These are not theoretical projections—they are already playing out in real time. Countries like Germany, China, and the U.S. are already experiencing labor shortages that will only intensify.
But here’s where McKinsey falls short: They don’t talk about AI & Automation. At least, not in the way they should.
If we’re serious about solving this demographic crisis, AI is not just an efficiency tool—it’s an economic necessity. Yet McKinsey barely scratches the surface on how AI could reshape workforce structures, redistribute economic benefits, and create entirely new forms of wealth transfer between generations.
So, let’s do what McKinsey didn’t—let’s connect the dots.
What McKinsey Gets Right: The Demographic Crisis is Real and Immediate
McKinsey’s argument is solid: shrinking labor forces threaten economic stability, and if nothing changes, living standards will decline.
This is already happening:
Germany is on track to lose 7 million workers by 2050. The country will need to either increase immigration dramatically or turn to AI and automation to keep its manufacturing sector afloat.
China’s population declined in 2022 for the first time in 60 years. Its working-age population peaked years ago, and by 2040, the country will have more retirees than workers.
The U.S. Social Security trust fund is projected to run out by 2035, meaning younger generations will be left footing the bill for an aging population.
McKinsey is right to highlight the urgency of the crisis, but their analysis overlooks the most scalable solution: AI-driven productivity growth.
What McKinsey Misses: AI is the Only Path to Productivity Growth at Scale
McKinsey talks a lot about the need for higher productivity, but what they don’t say explicitly is that AI is the only way to reach those productivity levels in a shrinking workforce.
1. AI is Already Offsetting Labor Shortages—But We Need More Investment
The numbers don’t lie:
Automation could replace up to 30% of work tasks by 2030, allowing businesses to maintain output with fewer workers.
AI-driven robotics in manufacturing have already boosted productivity by 25%, offsetting labor shortages in high-cost economies.
AI-powered diagnostics in healthcare are increasing doctor efficiency by 40%, helping compensate for physician shortages in aging populations.
Yet, despite these advances, AI adoption in key sectors remains slower than necessary.
Only 25% of businesses globally have fully integrated AI into their operations. This isn’t surprising, given the newness and adoption curve of these emerging technologies but it is expected to grow exponentially.
Companies invest 70% more in AI infrastructure than in workforce training, meaning many workers aren’t being equipped to work alongside AI.
If McKinsey is worried about slowing productivity, their focus should be on accelerating AI adoption in industries that can’t afford workforce losses—healthcare, manufacturing, and logistics.
2. AI is Not Just Replacing Jobs—It’s Creating Entirely New Categories of Work
One of the most common criticisms of AI-driven automation is that it will eliminate jobs—and while that’s true for some industries, AI will also create far more jobs than it replaces.
The World Economic Forum’s Future of Jobs Report projects a net gain of 78 million new jobs by 2030 due to AI and automation.
Where will these jobs come from?
Machine learning engineers, AI trainers, and automation specialists—demand for these roles is growing at 71% per year.
Cybersecurity and AI ethics professionals—AI-driven cybersecurity spending is projected to hit $290 billion by 2030, requiring a whole new workforce to manage risks.
Green economy jobs—AI is enabling the creation of 14 million jobs in sustainable energy and climate tech.
Yet, McKinsey fails to connect these AI-driven job trends to the broader demographic issue.
If labor forces are shrinking, AI-created jobs must be prioritized in workforce planning—something that isn’t happening fast enough.
3. AI Must be Used to Redistribute Productivity Gains—Or Inequality Will Explode
Here’s where McKinsey really drops the ball: AI’s impact on wealth concentration and economic inequality.
Despite productivity gains of 4% per year, real wages have only risen by 1% in major economies.
The top 10% of earners have captured 70% of economic growth from automation.
Younger workers earn 20% less than Baby Boomers did at the same age—despite higher education levels.
The AI-driven productivity boom will either lift wages or further entrench economic disparity.
If McKinsey is concerned about economic resilience, they should be looking at how AI-driven wealth transfer policies could help stabilize labor markets. Below is how this redistribution might look.
Policy and Business Solutions That Could Change the Game:
✔ AI-driven productivity growth must be tied to wage increases. Otherwise, we’ll see a scenario where AI benefits corporations but leaves workers behind.
✔ AI should be used to test Universal Basic Income (UBI) and tax policy innovations. AI-powered simulations could model how wealth redistribution policies could stabilize economies without stifling innovation. (We could write a whole article on this ——-And we did)
✔ Governments and businesses need to massively invest in AI upskilling initiatives. 50% of all workers will require retraining by 2025, and we’re already behind schedule.
✔ AI-driven automation must be designed to complement workers, not just replace them. Policies should incentivize AI-enhanced work rather than fully automated systems that eliminate jobs.
AI Won’t Save the Economy—Unless We Make It Work for Everyone
McKinsey’s Dependency and Depopulation report correctly warns of slowing productivity and economic stagnation—but ignores the single biggest factor that could change that trajectory: AI.
The future of work is not just about workforce numbers—it’s about how AI is integrated into labor markets, wages, and economic planning.
AI already is reshaping the economy. The real question is: Who gets to benefit?
AI could transform demographic decline from a crisis into an opportunity—but only if we design policies that ensure AI-driven wealth is distributed fairly.
We can either use AI to build a sustainable economy that works for everyone—or let it accelerate inequality while economic pressure mounts.
Governments, businesses, and individuals must act now to ensure AI benefits all generations—not just the ones who control it.