The current frenzy surrounding generative AI, particularly large language models (LLMs), is diverting attention and resources away from advanced analytics, a proven tool for improving business decisions and processes. Companies are pouring resources into LLMs, neglecting the value of advanced analytics in predicting customer behavior, optimizing supply chains, and other critical business functions. This shift in resource allocation could undermine projects that deliver tangible value across organizations, despite the lack of convincing business cases for LLMs. Meanwhile, advanced analytics and LLMs have distinct capabilities, and leaders should recognize their complementary strengths, combining the predictive power of machine learning-based advanced analytics with LLMs’ natural language capabilities. By leveraging LLMs to tackle challenges in advanced analytics development and deployment, companies can tap into new opportunities for predictive and prescriptive applications.
AI Hype Overshadows Proven Analytics
Companies pouring resources into large language models risk neglecting advanced analytics and their proven value for improving business decisions and processes.
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