Avoid training AI models at all costs (and they are costly)

AI is becoming integral to various business functions, but the traditional approach of training or fine-tuning AI models may not be the most effective or feasible for most enterprises due to high costs, complexity, and security risks. Box CTO Ben Kus and AI expert Meena Ganesh advocate for retrieval augmented generation (RAG) combined with AI agents as a smarter and more secure alternative. This approach enables AI systems to use existing models to access relevant data securely, minimizing the need for ongoing model management and reducing the risk of data leakage. RAG allows enterprises to efficiently harness AI for context retrieval and workflow automation without the resource-intensive demands of model training or fine-tuning. While custom training might be necessary for certain edge cases, for the majority of businesses, leveraging AI agents through RAG is a more practical and scalable solution.

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