Flexibility Over Lock-In: The Enterprise Shift in Agent Strategy

Why It Matters

The findings show that scaling agentic workloads requires interoperable, container‑based infrastructures, making flexibility and security essential competitive advantages for enterprises.

Key Takeaways

• 61% use both cloud and on‑prem models.
• 76% fear vendor lock‑in.
• 94% rely on containers for agents.
• 48% cite operational complexity as biggest challenge.
• Agents often involve four to six models.

Pulse Analysis

Enterprises are embracing a multi‑model, multi‑cloud reality for AI agents, driven by the need for performance, customization, and compliance. The Docker survey reveals that 61% of organizations blend cloud‑hosted and on‑premise models while 79% operate agents across two or more environments. This architectural diversity unlocks control but multiplies orchestration overhead, with nearly half of respondents flagging operational complexity as their primary obstacle.

Vendor lock‑in emerges as a strategic pain point, with 76% of respondents expressing active concerns. Companies are countering supply‑chain fragility by diversifying workloads across models, tools, and clouds, prioritizing data privacy and governance over pure cost savings. The push for open, portable standards reflects a broader industry shift toward interoperable infrastructures that can sustain trust and reduce dependency on single vendors.

Containers have become the backbone of this evolving ecosystem. A striking 94% of surveyed teams leverage containerization for both development and production of agents, extending familiar cloud‑native practices such as CI/CD and microservices to AI workloads. Docker Compose is gaining traction as an orchestration layer, signaling a move toward standardized, container‑based coordination. As agentic AI matures, organizations that embed container principles— isolation, portability, and simplicity—will achieve scalable, secure deployments while mitigating lock‑in risks.