This white paper explains why decentralized AI-agent adoption creates security, compliance, cost, and governance problems for enterprises. Local execution makes it difficult to control tools, monitor behavior, prevent shadow AI, maintain consistent workflows, or limit access to sensitive data. Citing a PwC survey, the paper identifies cybersecurity, implementation cost, workforce adaptation, trust, human oversight, legal concerns, and data issues as leading obstacles to realizing value from AI agents. It recommends centralized cloud development environments built from reusable templates and governed by organizational policies. Ephemeral workspaces, Terraform-based provisioning, role-based access controls, centralized SSH management, and comprehensive logging improve reproducibility and red

Join for free to read