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 a lack of understanding about the differences between generative AI and broader AI concepts. Many organizations mistakenly equate all AI with generative AI capabilities, not realizing that generative AI is just a subset of the larger AI discipline, which includes various techniques and practices.
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. In contrast, other AI technologies are actively employed in a wide range of applications, demonstrating that generative AI is not as widely implemented as it may seem.
What mistakes do organizations make with AI?
Organizations often make significant mistakes by applying static AI models without the necessary infrastructure to make them dynamic. This can lead to expensive delays and inefficiencies. Additionally, there is confusion between AI agents and static AI models, which can further complicate implementation efforts.
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