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Agentic AI is rapidly gaining traction in North American enterprises, offering autonomous reasoning and action capabilities. While adoption is broad, a split is emerging in implementation strategies: North American companies lean towards full autonomy, while European firms emphasize governance and data stewardship. Early adopters are already reporting significant returns, with a median ROI of $175 million from their AI investments.

IT operations are proving to be fertile ground for agentic AI, particularly in areas like cloud visibility and cost optimization. However, a “cost-human conundrum” poses a challenge. Continued reliance on human intervention and substantial implementation costs remain key concerns for many organizations. Furthermore, a divide exists in perceptions of AI reliability. Those directly working with the models tend to be more aware of potential shortcomings compared to executives.

The industry forecasts a swift move towards diminished human oversight. As AI capabilities improve, IT departments are predicted to evolve into orchestrators of these autonomous systems. Successful transition to agentic AI hinges on a balanced approach that combines automation with human augmentation, strategic investment in employee upskilling, and a relentless focus on ensuring the quality of data underpinning these AI models.