Businesses sidestep AI governance policies as concerns mount
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Senior AI leaders say frameworks have not been updated to accommodate the technology's specific risks, according to an EY report. Enterprises are dealing with a widening gap between AI governance policies and their execution. Despite prominent, well-documented cybersecurity incidents that reflect the technology's risk profile, organizations continue to bypass existing protocols. CIOs must help their businesses create governance processes that are robust enough to manage risk without becoming a hurdle to operations. "Moving fast and applying appropriate governance are not mutually exclusive," Jackson said. "Governance is what gives organizations the confidence to move quickly without losing control." This approach requires embedding governance into the AI development and deployment lifecycle, with clear requirements for testing, approval, monitoring and escalation. CIOs should also establish an explicit process for exceptions, including who can authorize an expedited deployment and what additional controls or post-deployment reviews are required. The challenge becomes more acute as organizations deploy agentic AI. Among respondents using the tech, around one in four sa id accountability for maintaining or monitoring it post-deployment was undefined. CIOs therefore need to look beyond initial approval and establish ownership throughout an AI system's lifecycle. That includes...
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