For over two decades, corporations compensated for inefficiency by adding layers of coordination instead of fixing the system. When something didn’t work, they didn’t redesign it — they hired someone to “manage” it.
Soon, entire ecosystems of meta-work emerged — jobs that existed to describe, oversee, or justify other jobs. They multiplied inside large organisations — roles that filled reporting gaps, not production gaps.
As anthropologist David Graeber famously wrote: “A bullshit job is one that, even the person doing it, secretly believes need not exist.”
These positions kept the corporate machine comfortable — absorbing graduates, padding hierarchies, and maintaining the illusion of growth.
These roles didn’t produce value — they performed it. Their output was visibility: reports, alignment sessions, status meetings, dashboards, updates.
But when AI arrived, it became the ultimate performance review. Anything that didn’t create measurable value became a candidate for deletion.
The great correction
When AI arrived, it didn’t have the patience for this theatre. Algorithms don’t need “alignment calls. They only need inputs and clear parameters.
AI didn’t just automate repetitive work — it audited the entire white-collar economy.
It isn’t just replacing labour — it’s revealing how much of it never created value in the first place.
It exposed:
- How much of “knowledge work” was actually administrative overhead?
- How many middle layers existed to repackage data and PowerPoints?
- How many decisions could be made faster, cheaper, and more accurately by algorithms?
Suddenly, entire strata of “pseudo-productive” roles were wiped out, and the pendulum swung from overemployment to over-efficiency.
What’s left now is a leaner economy — one that prizes execution, creativity, and synthesis over attendance, meetings, and memos.
Also Read: Levelling the playing field: How AI can transform SME hiring
The new problem: The missing middle
The irony? This over-correction might have been a step too far.
Automation isn’t just transforming industries — it’s compressing the career ladder. Across every sector, entry-level roles once considered “training grounds” are disappearing.
Many of those “bullshit jobs” accidentally functioned as incubators. Junior staff learned how organisations worked, how decisions were made, and how to navigate pressure.
Customer service? Now handled by AI chatbots. Data entry and basic analysis? Automated by APIs. Assistant and junior admin functions? Replaced by workflow software.
What looks like efficiency today creates an invisible problem tomorrow: A generation entering the workforce without ever learning how to work.
A leadership gap in the making
For decades, career development followed a predictable rhythm:
Learn by doing -> Manage a small process -> Lead a team.
But when the doing gets automated, the learning disappears. Graduates who might have started as analysts, assistants, or coordinators now face a jump directly into mid-level roles without the muscle memory of execution.
This creates a silent bottleneck:
- Fewer people trained in operations -> fewer competent managers.
- More theoretical graduates -> less real-world decision-making skill.
- An over-supply of “strategy talent” but an under-supply of “execution talent.”
That’s how an economy ends up with brilliant resumes but brittle organisations.
Also Read: AI bubble fears trigger market rotation: What it means for crypto and tech stocks
The opportunity: Build value, not vanity
This is where the real entrepreneurs and builders step in. The correction creates room to rebuild the work ecosystem around true value creation.
It’s not about bringing the old jobs back — it’s about building smarter ladders. If the bottom rungs are gone, we need new scaffolding:
- Apprenticeship ecosystems: partnerships between companies, startups, and governments to provide project-based learning.
- Fractional roles: part-time or remote junior assignments across multiple SMEs, giving broad exposure fast.
- AI-assisted training: using automation not as a replacement, but as a coach — teaching new workers how systems think and operate.
These are the new entry points into experience.
What businesses can do
For companies, this isn’t just a social issue — it’s a strategic one. Without a functioning entry pipeline, your future management pool shrinks.
Forward-thinking firms are already experimenting with:
- “Shadow roles” where junior hires train alongside AI systems.
- Cross-border internships connecting young professionals in emerging markets to remote SMEs abroad.
- Skill micro-certifications that replace old job titles with verifiable execution capability.
This is where companies can make a difference, building the frameworks that connect ambition to apprenticeship, learning to leadership.
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