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CIOs see AI prompting new IT hiring, even as boards push for job cuts

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While AI may enable some workforce reductions, DiLorenzo doesn’t see huge AI-driven cuts in IT budgets and teams in the near future. Even as many organizations infuse AI into software development and tech support teams, most enterprise leaders DiLorenzo speaks with see a slowdown in hiring new developers and IT support staff, rather than layoffs for current staff, he says.

“The encouragement that I give is that people who know AI will replace those that don’t,” he adds. “Whether it’s a functional or a technical job, it’s an important skill set to have. If a software developer is not using AI development tools, it’s going to be a challenge.”

Job cuts already happening

But in the weeks leading up to the release of the Deloitte report, Meta, Salesforce, Microsoft, Dell, and Intel collectively announced more than 24,000 job cuts related to AI, and Amazon CEO Andy Jassy predicted future job losses at his own company — and across the work world — as AI creates efficiency gains. It’s unclear how many of the layoffs were in IT departments, but about 800 of 2,000 jobs lost at Microsoft in May were software engineers.



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The new frontier of medical malpractice

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Although the beginnings of modern artificial intelligence (AI) can be traced
as far back as 1956, modern generative AI, the most famous example of which is
arguably ChatGPT, only began emerging in 2019. For better or worse, the steady
rise of generative AI has increasingly impacted the medical field. At this time, AI has begun to advance in a way that creates
potential liability…



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Pharmaceutical Innovation Rises as Global Funding Surges and AI Reshapes Clinical Research – geneonline.com

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Pharmaceutical Innovation Rises as Global Funding Surges and AI Reshapes Clinical Research  geneonline.com



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Radiomics-Based Artificial Intelligence and Machine Learning Approach for the Diagnosis and Prognosis of Idiopathic Pulmonary Fibrosis: A Systematic Review – Cureus

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Radiomics-Based Artificial Intelligence and Machine Learning Approach for the Diagnosis and Prognosis of Idiopathic Pulmonary Fibrosis: A Systematic Review  Cureus



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