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7 risk management rules every CIO should follow

CIO

A PwC Global Risk Survey found that 75% of risk leaders claim that financial pressures limit their ability to invest in the advanced technology needed to assess and monitor risks. Yet failing to successfully address risk with an effective risk management program is courting disaster.

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3 steps to get your data AI ready

CIO

Give up on using traditional IT for AI The ultimate goal is to have AI-ready data, which means quality and consistent data with the right structures optimized to be effectively used in AI models and to produce the desired outcomes for a given application, says Beatriz Sanz Siz, global AI sector leader at EY.

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10 AI strategy questions every CIO must answer

CIO

And the Global AI Assessment (AIA) 2024 report from Kearney found that only 4% of the 1,000-plus executives it surveyed would qualify as leaders in AI and analytics. To counter such statistics, CIOs say they and their C-suite colleagues are devising more thoughtful strategies. Am I engaging with the business to answer questions?

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Digital transformation 2025: What’s in, what’s out

CIO

Regardless of the driver of transformation, your companys culture, leadership, and operating practices must continuously improve to meet the demands of a globally competitive, faster-paced, and technology-enabled world with increasing security and other operational risks.

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EU taps AI experts to develop compliance framework for AI regulations

CIO

They will oversee four working groups, each focusing on different aspects of AI governance — transparency and copyright, risk identification and assessment, technical risk mitigation, and internal risk management for general-purpose AI providers. The code will outline exactly how companies can comply with the broad set of regulations.

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New trade body wants to license training data for AI use

CIO

Seven companies that license music, images, videos, and other data used for training artificial intelligence systems have formed a trade association to promote responsible and ethical licensing of intellectual property. The situation could become even more complex for multinational companies.

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3 things to get right with data management for gen AI projects

CIO

According to Kari Briski, VP of AI models, software, and services at Nvidia, successfully implementing gen AI hinges on effective data management and evaluating how different models work together to serve a specific use case. Data management, when done poorly, results in both diminished returns and extra costs.