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Mass layoffs caused by AI

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…

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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 What was "best practice" a few months ago can already be outdated.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.

1. Sofort-Triage & Abwehrmaßnahmen

SOC Incident Playbook: Vulnerability Remediation & Verification
Syntax validiert (0 Fehler)
title: Detect Exploitation - Mass layoffs caused by AI
id: 20468a9a-aa68-4d75-8f21-91fa2c3777c7
status: experimental
description: Automatisch generierte SIEM-Erkennungsregel basierend auf CTI Intelligence
references:
  - https://tsecurity.de/
author: iShareStuff CTI Automated Detection Engine
date: 2026-09-25
logsource:
  category: network_connection
  product: any
detection:
  selection:
      CommandLine|contains:
        - 'exploit'
  condition: selection
falsepositives:
  - Legitime administrative Zugriffe oder Penetrationstests
level: high
tags:
  - attack.initial_access
Syntax validiert (0 Fehler)
rule CTI_Threat_Indicator {
    meta:
        author = "iShareStuff CTI Automated Detection Engine"
        date = "2026-09-25"
        description = "YARA Signature for "
    strings:
        $str = "Mass layoffs caused by AI" ascii wide
    condition:
        any of them
}
Syntax validiert (0 Fehler)
index=security sourcetype IN ("cisco:asa", "pan:traffic", "zeek_conn", "suricata", "WinEventLog:Security")
("Mass layoffs caused by AI")
| stats count earliest(_time) as first_seen latest(_time) as last_seen by src_ip, dest_ip, dest_host, signature
| eval first_seen=strftime(first_seen, "%Y-%m-%d %H:%M:%S"), last_seen=strftime(last_seen, "%Y-%m-%d %H:%M:%S")
| sort - count
Syntax validiert (0 Fehler)
message: "*Mass layoffs caused by AI*"
Syntax validiert (0 Fehler)
CommonSecurityLog
| where Message has "Mass layoffs caused by AI"
| summarize EventCount = count(), FirstSeen = min(TimeGenerated), LastSeen = max(TimeGenerated) by SourceIP, DestinationIP, DestinationPort, Activity
| extend DetectionRule = "iShareStuff-CTI-Compiled"
| sort by EventCount desc

2. Cyber Threat Intelligence & Forensik

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MITRE ATT&CK Matrix Navigator 14 Taktiken
Reconnaissance
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Resource Development
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Initial Access
Execution
Persistence
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Privilege Escalation
Defense Evasion
Credential Access
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Discovery
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Lateral Movement
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Collection
-
Command and Control
Exfiltration
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Impact
tsecurity.de Cognitive Threat RAG
Fokus-Vektor:

Kognitive Analyse für identifizierte Bedrohung: Erhöhte Bedrohungslage im Bereich Mass layoffs caused by AI.... Basierend auf 368k Vektor-Korrelationen werden sofortige Isolationsmaßnahmen für betroffene Endpunkte empfohlen.

🛡️ Angriffsfläche & Exposure

Netzwerk/Remote-Zugriff ohne Vorauthentifizierung möglich.

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  • 1. Perimeter-Inspektion: Relevante Portfreigaben und exponierte Endpunkte unverzüglich scannen.
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