enterprise-ai knowledge-management ai-adoption ai-systems

Familiarity is the enemy: On why Enterprise systems have failed for 60 years

felixbarbalet.com

April 24, 2026

33 min read

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Summary

Enterprise knowledge systems have struggled for sixty years due to issues related to familiarity. A senior executive at a global enterprise indicated that this familiarity was a key reason for not adopting a new AI product.

Key Takeaways

Enterprise knowledge management systems have failed for over sixty years due to buyers prioritizing familiarity over innovation.
A senior executive stated that purchasing from a small innovative company is perceived as risky compared to established firms, which are viewed as an "insurance policy."
The enterprise software industry has incurred over a quarter of a trillion dollars in write-offs and productivity losses due to ineffective knowledge management solutions.
The technology used to transform information assets is crucial to realizing their value, yet buyers continue to select solutions based on familiarity rather than effectiveness.

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Coverage & discussions

Hacker News · felixbarbalet.com

Familiarity is the enemy: On why Enterprise systems have failed for 60 years ↗

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Community Sentiment

Mixed

Positives

The discussion highlights that LLMs can effectively work with various programming languages, emphasizing the importance of token efficiency and structural regularity over mere familiarity.
The emphasis on stability and clarity in libraries suggests that well-defined programming environments can significantly enhance AI model performance and reduce token wastage during training.

Concerns

Concerns are raised about the lack of reliable enterprise software solutions over the past sixty years, indicating a persistent gap in effective AI applications in this domain.
The sentiment that enterprises prefer established companies for support rather than innovative solutions suggests a stagnation in the adoption of potentially superior AI technologies.