Agentic AI In Practice: Lessons From Real Deployments
Search CIO, Monday, April 6th, 2026
Martin Bufi of Info-Tech shares lessons from real deployments, including why multi-agent architecture and code-driven approaches are critical to scale.
AI expert Martin Bufi suggests the following best practices for agentic AI deployment:
> Start with the workflow, not the agent. Organizations must standardize and clearly define processes before attempting automation.
> Agentic AI is typically multi-agent, not single agent. Real-world implementations rely on orchestrated systems of agents working sequentially or in parallel.
> Production requires strong governance and evaluation. Guardrails, access controls, observability and continuous evaluation are essential.
> Balance performance with cost. Not every step in a workflow will require the most powerful models.
> Customization is unavoidable. Off-the-shelf agents rarely work without code-driven development.
> Measurable outcomes depend on KPIs. CIOs must define clear business metrics upfront.
> Adoption is shifting toward dedicated teams. Organizations are increasingly building specialized teams and treating agentic AI as an ongoing lifecycle.