1、THE STATE OF AGENTIC AI REPORTEXECUTIVE SUMMARY1 Note:Adoption levels reflected in this research may appear high relative to the broader market.This survey intentionally sampled technical practitioners(developers,DevOps engineers,and technical leaders)across all industries,i.e.,the professionals mos
2、t likely to be working with emerging technologies.These findings reflect the leading edge of enterprise adoption rather than the broader market average.Key Takeaways Rapid adoption,early maturity:60%of organizations already have AI agents in production1,and 94%view building agents as a strategic pri
3、ority,but most deployments remain internal and focused on productivity and operational efficiency.Security and complexity are the top barriers:40%of respondents cite security as the#1 challenge in scaling agentic AI,with 45%struggling to ensure tools are secure and enterprise-ready.Technical complex
4、ity compounds the challenge.One in three organizations(33%)report orchestration difficulties as multi-model and multi-cloud environments proliferate(79%of organizations run agents across two or more environments).MCP shows promise but isnt enterprise-ready:85%of teams are familiar with the Model Con
5、text Protocol,yet most report significant security,configuration,and manageability issues that prevent production-scale deployment.Containerization remains foundational:94%use containers for agent development or production,and 98%follow the same cloud-native workflows as traditional software,establi
6、shing containers as the proven substrate for agentic AI infrastructure.Long-term outlook:Rather than a“year of the agents,”the data points to a decade-long transformation.Organizations are laying the governance and trust foundations now for scalable,enterprise-grade agent ecosystems.AI agent adoptio
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