"The enterprise world is awash in hope and hype for artificial intelligence. Promises of new lines of business and breakthroughs in productivity and efficiency have made AI the latest must-have technology across every business sector. Despite exuberant headlines and executive promises, most enterprises are struggling to identify reliable AI use cases that deliver a measurable ROI, and the hype cycle is two to three years ahead of actual operational and business realities."
"According to IBM's The Enterprise in 2030 report, a head-turning 79% of C-suite executives expect AI to boost revenue within four years, but only about 25% can pinpoint where that revenue will come from. This disconnect fosters unrealistic expectations and creates pressure to deliver quickly on initiatives that are still experimental or immature. The way AI dominates the discussions at conferences is in contrast to its slower progress in the real world."
Enterprises face intense hype around AI but struggle to convert expectations into measurable returns. Many executives expect revenue gains yet cannot specify sources, creating pressure to deliver on immature pilots. Generative AI and machine learning offer promising capabilities, but operationalizing pilots into impactful implementations remains difficult. Implementation challenges, cost overruns, and underwhelming pilot results produce an AI hype hangover. The variability of AI ROI contrasts with prior waves like ERP and CRM, where returns were more consistent. Some firms achieve value in task automation, logistics, claims processing, and software development, but widespread predictable ROI remains elusive.
Read at InfoWorld
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