We’re witnessing the most rapid job displacement in human history, and the development community is dangerously unprepared for what’s coming next.
At the Technology Salon NYC – UNGA Edition a participant wondered: “When someone quits, should we hire another? Or do you feel you can use AI enough now that you don’t need to replace him?”
This isn’t hypothetical anymore. AI is eliminating jobs, and companies are growing their profits. One participant noted that “a LMIC company doubled in size with 800 fewer people thanks to AI.” The traditional technology adoption curve—where innovation destroys some jobs while creating others—is being compressed into a timeframe that leaves little room for adaptation.
The Entry-Level Employment Apocalypse
The data is brutal for new graduates entering the workforce. SignalFire found that Big Tech companies reduced the hiring of new graduates by 25% in 2024 compared to 2023, while there was a 50% decline in new role starts by people with less than one year of post-graduate work experience between 2019 and 2024.
This isn’t just about tech companies. Entry-level jobs, disproportionately filled by young workers, are especially at risk, with nearly 50 million U.S. jobs affected. The pattern is clear: employment for workers aged 22 to 25 in the most AI-exposed sectors dropped 6% during the study period, while employment for older workers in the same jobs grew.
Development professionals are dismiss this as temporary growing pains. They’re wrong. Entry-level job postings have dropped 15% year over year, and the average age of technical hires has increased by three years since 2021, reflecting companies’ reluctance to invest in training junior talent.
Why This Time Is Different
Every technological revolution has displaced workers, but AI operates at unprecedented speed and scale. During the Salon discussion, one participant noted that “AI has created an environment where the marginal value of knowledge is approaching zero.” This isn’t hyperbole—it’s the new reality.
Unlike previous innovations, AI doesn’t just automate manual tasks.
AI could impact nearly 50 million US jobs in the coming years, with 40% of employers expecting to reduce their workforce where AI can automate tasks. The World Economic Forum projects that while AI and information processing technology will create 11 million jobs, they will simultaneously displace 9 million others.
But here’s what makes this different: the speed. Between late 2022 and July 2025, entry-level employment in software engineering and customer service declined by roughly 20%. We’re not talking about decades of gradual change—this is happening in real-time.
The False Promise of New AI Jobs
Yes, AI is creating new roles. AI/Machine Learning Engineer roles are experiencing 13.1% quarterly growth and 41.8% yearly growth, and prompt engineers earn an average base salary around $123,274 annually. But there’s a catch that should alarm everyone in the development sector.
77% of AI jobs require master’s degrees, and 18% require doctoral degrees. These aren’t jobs for the masses—they’re for the highly educated elite. Meanwhile, 49% of Gen Z job seekers believe AI has reduced the value of their college education.
Even more troubling, many of these “new” AI jobs are already being automated away. As one expert noted, we told people to “become a prompt engineer,” but then “AI is way better at designing prompts for other AIs than any human.” Job postings for prompt engineers are now minimal, despite the role being touted as the job of 2024 just months ago.
The Global South Left Behind
The Salon discussion highlighted a critical concern I share: the Global South being systematically excluded from AI opportunities. One participant observed that only 4% of the entire training data currently is from the global South, and out of 7,000 languages that exist, only 700 of them are on the Internet right now.
This digital divide will become an employment chasm.
While salary expectations are shifting, with remaining hires expected to take on roles supported by AI for less money, many regions lack the infrastructure and education systems to even compete for these diminished opportunities.
The economic implications are staggering.
As one participant shared, half of his company’s AI-driven savings become “pure profits,” while the other half goes to “Google and OpenAI for all of the compute.” None of this economic activity benefits the low and middle-income countries where displaced workers live.
Reframing Work for the AI Age
We need radical changes, and we need them now. Here are four urgent priorities for development organizations:
1. Abandon Traditional Career Ladders
The linear progression from entry-level to senior roles is dead. Development organizations must create apprenticeship models that pair new graduates directly with AI-augmented senior staff. Instead of hiring three junior researchers, hire one experienced analyst with AI tools and two community liaisons focused on relationship-building and cultural context—areas where AI fails.
2. Reimagine Education Immediately
As one Salon participant noted, “if we’re teaching young people the same way that we have taught them, the world is fundamentally different.” Development programs must shift to project-based learning where students solve real-world problems using AI collaboration. Teach prompt engineering not as a career but as basic literacy, like using a spreadsheet.
3. Address the Economic Extraction
We need “literal tax policy changes” to prevent AI from simply extracting value from developing economies without providing compensation. Development organizations should advocate for AI taxes that fund universal basic services in affected communities. When your organization automates away local jobs, you have a moral obligation to support those communities.
4. Develop Human-AI Partnership Models
The future isn’t humans versus AI—it’s humans with AI versus humans without AI. Map every role in your organization: what tasks can AI handle, what requires human judgment, and what needs cultural context? Then restructure positions around these realities rather than pretending AI doesn’t exist.
The Reality We Face
The traditional response—”retrain for new jobs”—falls apart when AI automates the retraining faster than humans can complete it. As one AI expert warned, if all jobs will be automated, then there is no plan B. You cannot retrain.
This is about being realistic. Technology, overall, is projected to be the most disruptive force in the labour market, and the development sector must confront this reality instead of hoping it will somehow pass us by.
Right now, we’re failing to even acknowledge the scope of the challenge, let alone address it.
We need to fundamentally redefine what work means, what it’s for, and how we distribute the benefits of technological progress. The alternative is a future where a small AI-enabled elite prospers while everyone else struggles for relevance.