A naukri.com initiative
Datarobot
4w
347
Image Credit: Datarobot
How to avoid hidden costs when scaling agentic AI
- Agentic AI systems offer significant potential in enterprise innovation, but hidden costs can present challenges when scaling.
- The complexity and hidden traps in building and scaling agentic AI systems lead to high costs.
- Simple single-agent use cases can lead to challenges such as increased API usage, infrastructure complexity, and latency issues.
- Scaling to multi-agent architectures can exponentially increase costs due to added complexity and orchestration requirements.
- Agentic AI costs are distributed across various components and decisions within the system.
- Hidden cost traps include manual iteration without cost awareness, overprovisioned infrastructure, and rigid architectures.
- To combat hidden costs, organizations should embed cost-awareness throughout the lifecycle of agentic AI systems.
- Optimizing system components during development helps in finding the right balance between cost, accuracy, and latency.
- Infrastructure-aware orchestration and dynamic workload management can help in efficiently utilizing resources.
- Using AI gateways can provide flexibility for system updates, policy enforcement, and compliance without major architectural changes.
Read Full Article
20 Likes
For uninterrupted reading, download the app