Hitting the peak of inflated expectations is prompt engineering, according to Gartner. While most large language models like OpenAI’s GPT-4 are pre-filled with massive amounts of information, “prompt engineering,” a way of training the algorithm, allows genAI to be tailored for specific industry or even organizational use.
GenAI interest wanes as ROI becomes the focus
Excitement around foundation models, such as Google Gemini, Anthropic Claude, Amazon Bedrock, and OpenAI GPT-4, is waning among enterprises as companies instead seek concrete returns on investment (ROI). These days, companies are more often than not deploying genAI only for use cases that drive ROI, according to Arun Chandrasekaran, a Gartner distinguished vice president analyst.
“Generative AI is sliding through the trough of disillusionment due to mismatch between high expectations vs. reality, enterprise challenges in maturing their data engineering and AI governance, as well as intangible ROI of many genAI initiatives,” Chandrasekaran said.
