Generative AI Causes Costly Mistakes for Enterprise Buyers
Confusion surrounding generative AI exists in the market, leading enterprises into unnecessary expense and delays, according to Gartner's Erick Brethenoux.
What is the confusion surrounding generative AI?
The confusion stems from misunderstandings about the broader category of AI compared to generative AI, as well as the differences between AI agents and static AI models. This lack of clarity can lead organizations to make costly mistakes in applying the technology to their business needs.
How prevalent is generative AI in production use cases?
Generative AI is currently used in only about 5% of production use cases, despite dominating media discussions. Other AI technologies continue to play a significant role in various applications, emphasizing that generative AI is just one aspect of a much larger field.
What are the differences between AI agents and static AI models?
AI agents are active software entities that perform tasks independently, while static AI models are passive and created by algorithms and data. Understanding this difference is crucial, as confusing the two can lead to ineffective implementations and costly mistakes in operationalizing AI solutions.
Generative AI Causes Costly Mistakes for Enterprise Buyers
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