This article presents a practical decision-making framework to help teams determine when deploying a Large Language Model (LLM) is appropriate.
It highlights that while LLMs are powerful, they are not always the right solution especially for tasks where simpler rule-based systems, search engines, or domain-specific ML models may be more efficient and cost-effective. The piece targets project managers and AI strategists, encouraging a value-over-hype approach.
It includes a comparison table of decision factors such as latency, cost, hallucination risk, and accuracy sensitivity, guiding responsible Gen AI adoption.
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