惯性聚合 高效追踪和阅读你感兴趣的博客、新闻、科技资讯
阅读原文 在惯性聚合中打开

推荐订阅源

V
V2EX
博客园 - 叶小钗
Last Week in AI
Last Week in AI
Google DeepMind News
Google DeepMind News
钛媒体:引领未来商业与生活新知
钛媒体:引领未来商业与生活新知
Microsoft Security Blog
Microsoft Security Blog
腾讯CDC
P
Proofpoint News Feed
大猫的无限游戏
大猫的无限游戏
The Cloudflare Blog
aimingoo的专栏
aimingoo的专栏
月光博客
月光博客
量子位
A
About on SuperTechFans
Engineering at Meta
Engineering at Meta
Apple Machine Learning Research
Apple Machine Learning Research
Jina AI
Jina AI
博客园 - Franky
OSCHINA 社区最新新闻
OSCHINA 社区最新新闻
人人都是产品经理
人人都是产品经理
D
DataBreaches.Net
博客园_首页
Cyber Security Advisories - MS-ISAC
Cyber Security Advisories - MS-ISAC
Stack Overflow Blog
Stack Overflow Blog

DEV Community

Authentication Security Deep Dive: From Brute Force to Salted Hashing (With Java Examples) Why AI Systems Don’t Fail — They Drift Spilling beans for how i learn for exam😁"Reinforcement Learning Cheat Sheet" I Replaced Chrome with Safari for AI Browser Automation. Here's What Broke (and What Finally Worked) How Python Borrows Other People's Work The $40 Architecture: Processing 1 Billion API Requests with 99.99% Uptime Vibe Coding: A Workflow Guide (From Zero to SaaS) Most webhook security guides protect the wrong side. The scary part is delivery. Headless CMS for TanStack Start: Build a Blog with Cosmic EU Age Verification App "Hacked in 2 Minutes" — What Actually Happened Comfy Cloud’s delete function does not actually remove files Running AI Models on GPU Cloud Servers: A Beginner Guide Event-driven media intelligence with AWS Step Functions and Bedrock I scored 500 AI prompts across 8 quality dimensions — here's what broke How to Call Google Gemini API from Next.js (Free Tier, No Backend Needed) The Portal Protocol: Reclaiming Human Connection in the Age of AI How to Fix Your Team's Scattered Knowledge Problem With a Self-Hosted Forum Intro to tc Cloud Functors: A Graph-First Mental Model for the Modern Cloud Designing Multi-Tenant Backends With Both Ownership and Team Access I Built a Neumorphic CSS Library with 77+ Components — Here's What I Learned PostgreSQL Performance Optimization: Why Connection Pooling Is Critical at Scale Cómo construí un SaaS multi-rubro para gestionar expensas en Argentina con FastAPI + Vue 3 🚀 I Built an Ethical Hacking Scanner Tool – Open Source Project I Replaced /usage and /context in Claude Code With a Single Statusline A Pythonic Way to Handle Emails (IMAP/SMTP) with Auto-Discovery and AI-Ready Design I Collected 8.9 Million Polymarket Price Points — Here's What I Found About How Markets Really Move EcoTrack AI — Carbon Footprint Tracker & Dashboard Everyone's Using AI. No One Agrees How. 5 self-hosted ebook managers worth trying in 2026 Building Your First AI Agent with LangChain: From Chatbot to Autonomous Assistant
Mass layoffs caused by AI
Oleg Dubovoi · 2026-06-05 · via DEV Community

Talk about AI causing layoffs started back in 2024.

At that time, many companies were under pressure because of the global economy. Budgets were tight, investors demanded better efficiency, and companies wanted to look "AI-driven" and modern. In this situation, layoffs were often explained as "AI optimization."

But did AI really automate all of this work? It's hard to say for sure. However, we can look at how AI is actually being adopted in companies.

According to McKinsey's The State of AI in 2025, only about 30-40% of companies managed to scale AI beyond small experiments and pilot projects.

From my own experience talking to AI enablement specialists, attending conferences, and doing research, the real level of AI adoption inside companies is often even lower than what companies publicly claim.

Having a ChatGPT subscription or an AI assistant that helps with emails does not mean AI is fully integrated into company workflows. The field is moving very fast, and standards keep changing. What was "best practice" a few months ago can already be outdated. As a result, adoption is uneven: some teams use AI agents heavily, while others don't even know what MCP or agent workflows are.

Recently, I wrote an article called "Will AI Replace Software Developers?", where I explained why AI will not simply replace developers. And I still believe that AI itself will not take your job.

However, there is an important point I didn't fully cover there. Your job might not be replaced by AI, but it can be reduced by management decisions.

Does AI make developers faster? Yes, it does. But some managers take a very simple view: if each developer produces more code, we can reduce the team size. The problem is that writing code is only a small part of software development. With AI, we do write more code. But we also spend more time on planning, testing, code review, validation, and system design discussions. Productivity increases, but it doesn't mean we need fewer people in a linear way.

Even if leadership understands this and avoids the AI hype, there is another issue: the cost of using AI.

Most companies already operate under tight budgets. Now they also need to pay for AI models, infrastructure, integrations, and trainings.

Many people forget that today's AI pricing is still partly supported by competition and heavy investment from providers. Even now, the monthly cost for advanced AI tools can become significant for large companies. This means companies are not only paying for growth, but also for maintaining their AI strategy.

That's why we still see layoffs in tech. Often, it's not because AI fully replaced people, but because companies need to reallocate budgets to expensive AI infrastructure and projects.

So when we hear about mass layoffs, it's important to understand: AI is rarely the only reason.

More often, it's a combination of:

  • global economic pressure
  • investor expectations
  • budget constraints
  • AI hype and unrealistic expectations
  • rising infrastructure and model costs

All of these together are shaping today's job market.

I don't believe AI will replace most professionals. But I do believe AI is already adding pressure to an already difficult market.

The good news is that these cycles don't last forever. The tech industry has gone through crises and corrections before. Over time, things stabilize, companies adapt, and the job market finds a new balance.

No one is safe from layoffs.

But your skills, reputation, network, and ability to adapt greatly increase your chances of quickly finding a new and even better opportunity. So keep learning, keep building your skills, stay active on LinkedIn, and stay aware of how the industry is changing.

In the long run, that is still the best protection against change.

For more thoughts, research, and practical insights on AI and software development, visit my personal blog: olegdubovoi.com.