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AI still doesn't work well, businesses are faking it, and a reckoning is coming

AI still doesn't work very well in business, reckoning soon

theregister.com

March 17, 2026

8 min read

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47/100

Summary

Many businesses are struggling to effectively integrate AI into their operations, leading to concerns about potential issues arising from AI-generated code and content. Experts emphasize the need to reduce hype around AI and take time to identify appropriate use cases and reference architectures.

Key Takeaways

Businesses are struggling to effectively integrate AI into their operations, with many pretending to have solutions despite lacking a clear playbook.
AI-generated code can appear correct yet still be fundamentally flawed, as demonstrated by an AI attempt to rewrite SQLite that resulted in code performing 2,000 times worse than the original.
Current metrics used to evaluate coding success, such as lines of code and pull requests, do not accurately reflect engineering quality or team performance, necessitating new measurement standards.
The founders of Codestrap emphasize the need for organizations to experiment and iterate with AI, as it still does not work well in practice.

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Community Sentiment

Negative

Positives

The rapid advancement of AI tools, which were mere toys two years ago, indicates a significant potential for future improvements, even if current implementations are flawed.

Concerns

The performance of AI systems is severely lacking, as evidenced by a database that is 2,000 times worse than its predecessor, raising concerns about viability and investment.
AI-generated designs have led to significant errors in real-world applications, causing project delays and highlighting the tool's unreliability in critical decision-making.
Trust in AI remains low due to a history of unmet expectations and false promises, making businesses hesitant to fully embrace its capabilities.