At least half of generative AI projects are expected to exceed budgeted costs because of poor architectural choices and insufficient operational know-how. Most organizations attempting to build custom models are expected to abandon efforts due to costs, complexity, and technical debt created during deployments. No evaluated generative AI technologies are considered to have reached the plateau of productivity, meaning they have not yet stabilized through multiple generations and delivered verifiable real-world benefits. Domain-specific generative AI models are expected to produce better results and fewer hallucinations in healthcare, finance, and law, but they require significant compute, specialized expertise, and ongoing maintenance. Generative-AI-enabled applications are evolving quickly and show adoption by over half of the target market, though intellectual property concerns and inaccurate outputs remain issues.
"Gartner thinks at least half of all generative AI projects "will overrun their budgeted costs due to poor architectural choices and lack of operational know-how," and most organizations that try to build custom models "will abandon their efforts due to costs, complexity and technical debt in their deployments.""
"To reach the plateau, tech ascends the Peak of Inflated Expectations, falls into the Trough of Disillusionment, and slowly climbs a Slope of Enlightenment. Gartner labels Domain-specific GenAI models - models built from scratch or fine-tuned on domain data - as likely to produce superior results and fewer hallucinations compared to the output of general-purpose models in fields such as healthcare, finance, law and other industries."
"But the firm advises building these models "requires significant compute resources, specialized expertise and ongoing maintenance," and rates their maturity as "adolescent" and placed it just before the Peak of Inflated Expectations and at least two to five years from becoming mature enough for mainstream use."
"Just one of the technologies Gartner considered is climbing the slope: Generative-AI-enabled applications such as coding assistants, graphics and video creation, and summarizing content. The firm worries that intellectual property concerns and the tendency to create inaccurate output continue to plague these tools but feels rapid evolution of underlying models means these applications are quite mature - as shown by over half the target market having adopted such applications."
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