AI won’t put employees out of work
Humans who embrace AI will secure their roles
It’s been a rough stretch for the software engineer who listens to podcasts.
Last month, Meta CEO Mark Zuckerberg dropped a bomb on The Joe Rogan Experience, claiming that by 2025, artificial intelligence (AI) could function as a “mid-level engineer” capable of writing code. Not to be outdone, Salesforce CEO Marc Benioff followed up on The Twenty Minute VC by stating that his company’s business plan included not hiring more software engineers because AI tools drive enough productivity gains.
When it comes to AI and employees, this kind of rhetoric feels like an industry-wide obituary. If the CEOs of trillion-dollar tech companies believe AI will replace engineers, what chance does a mere mortal coder have?
A recent report from AI software delivery platform Harness added fuel to the fire when it found that nearly 90% of 500 engineering leaders and developers said they worry that AI tools will eventually replace them despite findings to the contrary.
Simply put, this panic is overblown.
AI won’t replace good employees. It will expose mediocre ones
Yes, AI is powerful. It can generate boilerplate code, assist in debugging, and suggest architectural improvements. But that’s not enough to replace good engineers. What AI does is expose mediocre ones.
The software industry has become bloated with developers who rely on copy-pasting snippets of code rather than truly understanding the logic behind them. AI now makes it easier to identify who thinks in code versus who stitches it together.
Let’s be clear, organizations are still in great need of engineers who think in code.
The same critical thinking, creative, and strategic mindsets apply to roles beyond software. There are many other areas of expertise where AI can help employees increase efficiency so that they can focus on more impactful work. Here are just a handful:
- Consulting: AI can analyze massive datasets and suggest optimizations, but it lacks the human insight to navigate business politics, stakeholder dynamics, and real-world execution.
- Finance: AI can predict market trends and automate risk assessments, but it won’t replace financial advisors who provide tailored strategies based on human behavior and business nuances.
- Marketing: AI can generate ad copy, create visuals, and analyze engagement. But it can’t craft a brand story that resonates emotionally or strategize multi-channel campaigns that drive real ROI.
- Design: AI can create logos, layouts, and even entire websites. But true innovation still comes from human creativity; knowing when to break the rules, not just follow patterns.
CEOs love AI hype, but the reality is a lot more complicated
Tech CEOs love to make sweeping predictions. They have to; it excites investors, rallies shareholders, and keeps their companies at the forefront of the AI gold rush.
But the reality?
AI, and companywide AI adoption, is still in its early stages and needs a lot of human oversight.
In a ServiceNow AI Maturity Index survey of nearly 4,500 respondents from 21 countries, it was found that companies, on average, are spending about 9% of revenue on technology, with 15% of that going to AI.
Meanwhile, recent research from McKinsey notes that while almost all companies invest in AI, “just 1% believe they are at maturity.”
What does this mean for the immediate future?
A tool that confidently auto-generates incorrect code isn’t replacing engineers. In fact, it could actually be creating more work for them.
Think about some really important factors that AI doesn’t yet grasp:
- Business logic and strategy
- System architecture
- Critical thinking behind real-world decision making
The engineers who will remain relevant? They’ll be at the top of their game.
AI is a productivity enhancer, not a job killer. And the people who actually build things know it.
The future: fewer routine roles, more strategic experts
If anything, AI will force a long-overdue correction in many industries. Companies won’t need as many professionals doing repetitive, execution-based work.
This looks like:
- Advisors who leverage AI-driven data analysis but use human insight to turn ideas into action.
- Engineers who don’t just write code but architect scalable, intelligent systems that AI alone can’t dream up.
- Marketers who know how to use AI to automate the grunt work so they can then focus on creative, big-picture storytelling and strategic planning.
- Designers who use AI to streamline processes but apply human artistry to create experiences that feel fresh and unexpected.
The era of “anyone can be a software engineer after a 12-week boot camp” is fading. So, too, are the days of “fake it until you make it.”
The employees who survive this shift will be the ones who fully embrace AI, refine their expertise, and do what machines can’t: think critically, solve ambiguous problems, and create things that not only work but continue disrupting entire industries.