Your first job shapes who you become as a professional. Those early experiences build the foundation of skills, judgment, and self-knowledge that you carry for your entire career. They teach you what you're naturally good at, what drains your energy, and what excites you at work.
My first job was all 5 AM wake-ups and market research. Every morning, I'd read through dozens of reports and news articles, then send out a summary email before the opening bell. The rest of my day was spent building comparison tables—endless spreadsheets filled with production numbers, debt ratios, and commodity prices.
At the time, it felt like grunt work. But those tedious tasks were actually building something invaluable: my apprenticeship in thinking. Learning to spot patterns in data. Understanding what questions mattered. Developing judgment about what information was signal versus noise.
Today, ChatGPT could knock out my entire first-year workload—and that's a massive problem.
The Learning Pathway is Disappearing
Recent research from Stanford and Harvard shows that this typical early career experience is at risk of being destroyed. AI isn't just changing work randomly—it's systematically targeting entry-level positions that have historically served as professional training grounds.
The studies show that:
Younger workers (aged 22-25) experienced a 13% decline in job opportunities in AI-heavy fields like customer service and software development.
Meanwhile, senior workers in the same companies and occupations saw stable or even growing employment.
Why AI Targets Entry-Level Jobs
The simple answer is that AI excels at routine tasks, while it struggles with complex judgment.
Entry-level roles are often very predictable, rule-based tasks such as basic customer service, initial code reviews, data entry, and first-draft content creation. These roles follow clear rules and procedures - exactly AI’s sweet spot.
Senior roles are different. They demand nuanced decision-making, strategic thinking, managing human dynamics, and building trust—skills AI cannot replicate and often augments.
Essentially, AI is replacing the "training ground" where new professionals traditionally learned to work, while making experienced workers more powerful
Why Should You Care?
This creates a problem that goes far beyond individual career paths. While companies see obvious cost savings from AI adoption, the long-term consequences could be devastating.
If AI handles the practice-level work, how will the next generation develop expertise?
When I started my career, it was not the tasks itself that taught me to think—it was wrestling with getting the tasks done correctly. The learning happened in the struggle, not the summary. Knowledge comes from trying new approaches, eliminating what doesn't work, and evolving fast.
We can't bring back grunt work—AI owns that now. But we can redesign how we work with AI to keep the learning alive through faster feedback loops.
The Solution: Active Dialogue with AI
Think of AI as your thinking partner, not your replacement. Instead of Artificial Intelligence think Assistance Intelligence- AI that doesn't just give answers, but teaches you how it got there.
The secret is active dialogue. When working with AI, provide the context and interrogate it:”Walk me through your analysis step-by-step”. “What patterns do you see?”, "What assumptions are baked in?" ,"How does this change if we flip this variable?".
This creates accelerated learning:
Critical thinking develops through questioning AI outputs
Pattern recognition sharpens by analyzing more scenarios
Decision-making skills compound through higher-volume practice
Your Next Move
We're at a crossroads. We can let AI hollow out the apprenticeship system and deal with the talent crisis in a decade. Or we can redesign how people develop expertise alongside AI.
Look at your entry-level roles. Are you using AI to eliminate learning opportunities or amplify them?
Those 5 AM market reports taught me to think not because of what I read, but because of how I wrestled with making sense of it all. That struggle—the process of developing judgment through practice—can't be automated away.
The companies that get this right will have the only advantage that matters: people who can think. The future belongs to companies that make their people more capable, not companies that make them unnecessary.