In the first quarter of 2026, companies named AI as the top reason for layoffs for the second consecutive month — not because AI actually replaced those jobs, but because saying “we’re restructuring due to AI” sounds more defensible than “we’re cutting costs to impress investors.”

This is AI washing in its most naked form.

The most common forms:

  1. Rebranding existing automation as “AI” — A chatbot that’s a rules-based decision tree with if/else branches is not AI. A recommendation engine that’s collaborative filtering from 2005 is not AI. But in 2026, calling these things “AI-powered” is still completely legal in most jurisdictions.

  2. Blaming layoffs on AI when they have nothing to do with AI — Sam Altman (OpenAI CEO) explicitly called this out in May 2026: “Some companies are AI washing by blaming unrelated layoffs on the technology.”

  3. The “AI Integration” press release — Every company in 2026 has an “AI integration strategy.” Most of them are adding an LLM API call to an existing product and calling it transformed.

How to Detect AI Washing:

Ask: What specific model? Generic “our AI system” is a red flag. Real AI implementations can name their models.

Ask: What was the output before and after? If a company claims AI transformed their customer service, ask for the before/after resolution rates, not just the marketing claim.

Ask: Who made the AI decisions? CIP (Chief AI Officer) titles without AI/ML background. AI task forces without an ML engineer.

Thailand’s digital economy push involves significant government investment in AI infrastructure. If Thai enterprises adopt AI washing as a path to subsidies rather than genuine transformation, the country risks building its digital economy on quicksand.

AI is genuinely transformative — but not at the pace or in the ways most marketing departments claim. Recognizing AI washing isn’t cynicism. It’s pattern recognition.