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The decline of AI

Dec 16, 2025
The narrative around AI's decline may be misleading, according to the hosts. They challenge growth charts, emphasizing that enterprise coding revenue remains strong despite consumer tool churn. Discussions cover unrealistic growth expectations and the significance of data verification. The shift in marketing strategy away from chasing tools towards focusing on KPIs is highlighted, along with insights into AI data accuracy and the role of data labeling in model training. Skepticism about outputs and maintaining rigorous standards in AI implementation are strongly advised.
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INSIGHT

Red Charts Can Be Misleading

  • Red growth charts can mislead because their data sources are often inaccurate or incomplete.
  • Neil Patel argues that apparent declines ignore enterprise gains like Anthropic's rising revenue.
INSIGHT

Hypergrowth Skews Expectations

  • Exceptional ARR ramps (hundreds of millions in months) are rare and distort expectations.
  • Eric Siu warns that people expect unrealistic hyper-growth as the new normal.
INSIGHT

Churn And Margin Realities

  • Many AI businesses face churn and margin pressure, especially in data-labeling services.
  • Neil Patel and Eric Siu note large spend on infrastructure and labelers during the current AI 'gold rush'.
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