Generative AI has revolutionized the way we work, but it also poses a significant threat to organizational knowledge. As AI-generated content becomes increasingly prevalent, the accuracy and quality of knowledge are being compromised. This decay in knowledge is not just limited to one sector or type of AI application, but affects various industries such as healthcare, research, and human resources.
The problems with generative AI can be broken down into three main challenges: verification, validation, and entropy. Verification involves disentangling valid information from AI-generated content that may contain hallucinations or errors. Validation requires humans to add value to AI-generated outputs, ensuring they meet quality standards. Entropy refers to the gradual decline of systems into disorder as knowledge is passed through AI.
To address these challenges, leaders must develop a clear strategy to deal with the knowledge and process implications of generative AI. Four steps can be taken:
1. Keep track of the provenance of unstructured data.
2. Restrict the use of generative AI.
3. Define what value is being added.
4. Understand the implications for the entire process.
By taking these steps, leaders can preserve the integrity of content and ensure that knowledge remains valuable and useful within their business processes.
Source: https://hbr.org/2026/06/dont-let-ai-slop-muck-up-your-companys-processes