Cisco positions the AITECH learning path as a bridge from “traditional knowledge-based work” to innovation-driven roles augmented by AI, explicitly targeting professionals who need to design technical solutions, automate tasks, and lead teams using modern AI tools and methodologies. The curriculum spans AI-assisted code generation, AI-driven data analysis, model customization (including RAG), and workflow automation wrapped in governance and security best practices.
Why this certification matters now
The timing of AITECH aligns with the reality facing most IT organizations: AI is already creeping into operations, security, networking, and collaboration, but skills lag badly. Cisco explicitly describes AITECH as meant to “close the AI skills gap” and prepare technical staff to confidently embed AI into daily operations and drive adoption inside their organizations.
Instead of creating yet another “AI expert” badge, Cisco is acknowledging that:
- AI is becoming a first-class consumer of infrastructure resources, from GPUs to storage to high-bandwidth networking.
- Network and infrastructure teams need to understand AI workflows well enough to support and optimize them, not just keep the pipes up.
- Everyday technical tasks—writing code, troubleshooting, analyzing logs, creating reports—can be materially improved by AI if practitioners know how to use it safely and effectively.
In that context, AITECH is less about learning isolated AI theory and more about hardening the applied AI skills that will define the next generation of infrastructure roles. For enterprises staring down a flood of AI projects, having a common competency baseline around prompt engineering, ethics, data practices, and automation is increasingly nonnegotiable.
At Cisco Live, I caught up with Par Merat, vice president of learning at Cisco, and we talked about this certification and the thought process behind it.
“We are focused on reskilling engineers around AI and how that can help them with their current jobs while preparing for the future,” Merat said. “This looks at every aspect of running a network—from initial design to day-to-day operations to troubleshooting and optimization.”
