Digital Trends

AI adoption brings revenue boosts, but data readiness lags – CIO Dive

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Nearly two-thirds of businesses plan to increase their efforts in the next two years, an Accenture survey found.
Generative AI hype began to subside this year as executives struggled to identify and measure adoption benefits. But some analysts and technology leaders blame the lag on poor strategy. 
Successful generative AI adoption “requires organizations to have a strong digital core, data strategy and a well-defined roadmap to change the way they operate,” Arundhati Chakraborty, group chief executive of Accenture Operations, said in the release. 
From a technical perspective, enterprises grapple with gaps in AI readiness related to infrastructure and data ecosystems. On the people side of the equation, enterprises contend with skill gaps that exacerbate technical roadblocks and threaten the success of initiatives. A lack of clarity and understanding of where gaps lie is also plaguing enterprises. 
Organizations will likely abandon nearly one-third of generative AI projects after the proof of concept stage by the end of 2025, according to Gartner research, which pointed to rising costs and unclear business value as key factors.
CIOs are working to avoid missteps by leaning on frameworks, tying use cases to success metrics from the onset and setting a pace of adoption that complements business appetite and readiness level.
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As vendors fuel a sense of urgency on AI adoption, CIOs turn to risk mitigation frameworks to clear the smoke.
The act took effect Thursday, but enforcement deadlines are spread out through 2027. The act could have a similar global influence to GDPR.
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As vendors fuel a sense of urgency on AI adoption, CIOs turn to risk mitigation frameworks to clear the smoke.
The act took effect Thursday, but enforcement deadlines are spread out through 2027. The act could have a similar global influence to GDPR.
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