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The article focuses on the operational hurdles of scaling agentic AI, specifically highlighting that successful adoption requires reengineering business models and workforce strategies rather than just technological upgrades. Key barriers identified include data fragmentation, governance challenges, and integration costs, which prevent most organizations from moving beyond experimental phases to orchestrated multi-agent deployments. This analysis is central to understanding the practical implementation of autonomous AI systems in enterprise environments.

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Businesses must reinvent their processes and workforce to scale agentic AI adoption

ZDNetAugust 24, 20264 min read

Only 15% of US-based organizations have reached scaled, orchestrated, multi-agent adoption, according to the latest Deloitte research.

J. David Ake/Getty Images Follow ZDNET: Add us as a preferred source on Google. Only 15% of organizations have reached scaled multi-agentic orchestration. Most business leaders are reevaluating their business models in light of advances in agentic AI. Scaling agentic AI must begin with sufficient resources to transform the workforce. Most US-based companies are under pressure and working hard to shift from experimenting with AI agents to deploying them in production, according to the latest research from Deloitte. A survey of…

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