Here’s what I keep hearing from enterprise customers.
They have the GPUs, they have executive sponsorship, and they have a compelling use case. But they’re still twelve, fourteen, sometimes sixteen weeks into their AI project, stitching together infrastructure and software stacks by hand. Their best people are debugging vendor compatibility instead of building the thing that’s supposed to transform their business.
That’s not an infrastructure problem. That’s an operations problem, and it’s now the single biggest drag on deploying AI at scale. That’s why this week at Cisco Live 2026 in Las Vegas, we’re introducing two major steps toward operationalizing enterprise AI:
Cisco Compatible Solutions for AI, a growing ecosystem of AI software and solutions vetted and tested on Cisco AI infrastructure.
Stack Automation by Quali, a new deployment automation platform developed with Cisco to help customers move from rack to application in hours instead of weeks.
Together they’re designed to help enterprises reduce the operational complexity that’s slowing AI adoption.
The operational era has begun
For the past two years, enterprise AI conversations centered on infrastructure acquisition: can you get GPUs deployed fast enough to match demand? But the challenge is no longer just buying hardware. It’s operationalizing AI at scale. That’s where the real work is happening.
AI now requires orchestrating accelerated compute, networking, storage, AI software frameworks, security tooling, observability, and industry-specific applications—and bringing all of it together into a production-ready system that runs reliably, consistently, and at scale.
That’s the foundation behind Cisco AI PODs, part of Cisco Secure AI Factory with NVIDIA: pre-validated architectures that bring together compute, networking, storage, security, and observability to reduce deployment complexity from the start.
But infrastructure alone doesn’t close the gap between deployment and business value. Organizations also need confidence that the software, development frameworks, and AI or agentic AI applications running on top of that infrastructure will work reliably in production.
That’s exactly what Cisco Compatible Solutions for AI is designed to address.
Closing the gap with Cisco Compatible Solutions for AI
Cisco Compatible Solutions for AI is a new differentiator for Developer solution partners in the Cisco 360 Partner Program. With this new model, customers can easily find and use AI applications across a growing and curated ecosystem of third-party AI software vendors spanning vertical industries like manufacturing, retail, and healthcare, as well as horizontal categories such as AI development and agentic platforms on Cisco AI infrastructure.
When an organization selects a Cisco Compatible Solution for AI, they’re not starting from scratch. They’re getting a pre-vetted solution that’s been tested for compatibility with Cisco AI infrastructure from core to edge.
Our work with SūmerSports is a strong example of how this is already playing out in industries where trust and speed directly impact outcomes. The goal is simple: help organizations close the gap between AI and business value by reducing the integration complexity that stalls enterprise AI adoption.
And we’ve taken it a step further.
From rack to app in hours with Stack Automation by Quali
This week, we’re introducing Stack Automation by Quali, a new deployment automation platform co-engineered with Quali, an agentic AI accelerator for infrastructure operations, and offered exclusively by Cisco.
Stack Automation by Quali embeds Cisco Validated Designs, automation intelligence, and repeatable blueprints directly into the deployment workflows. This helps organizations operationalize full-stack AI environments by automating infrastructure configuration, AI tooling, software layers, security, and observability from rack to application.
Instead of spending weeks manually assembling AI environments, organizations can deploy repeatable, governable, full-stack environments in hours. This includes:
- Physical infrastructure: compute, networking, storage configuration
- Infrastructure software: Cisco Validated Designs with our strategic partners
- AI development tooling: frameworks and blueprints available with NVIDIA AI Enterprise to accelerate application development
- Ready-to-deploy AI applications: drawing on Cisco Compatible Solutions for AI for industry-specific outcomes ready for production
- Security and observability: embedded in every layer
Over time, these capabilities will be available through Cisco Cloud Control, creating a single operational plane for deploying, managing, securing, observing, and automating AI environments through one login, one inventory, one assistant, and one agentic workspace.
That’s a fundamentally different way of operating.
What this looks like in the real world
Let me make this concrete.
A manufacturer wants to deploy computer vision on a production line. Today, that takes months of integration work before the model ever sees a camera feed. With a validated operational approach that combines infrastructure, AI tooling, security, and automation into a repeatable system, those deployments can happen in days.
Or take healthcare. A provider wants to accelerate diagnostic workflows with AI, but standing up infrastructure, integrating applications, and validating security and compliance is manual and slow. With an operational environment that spans the full stack, those critical systems can get up and running far more quickly and with the safeguards healthcare organizations require.
Retail introduces another challenge: running AI-powered customer experience applications across hundreds of locations can create configuration drift and operational instability. With repeatable deployment blueprints and automated workflows, organizations can deploy consistent environments across every site.
These aren’t future scenarios. They’re what Cisco Compatible Solutions for AI and Stack Automation by Quali are built to deliver right now.
Enterprise AI is entering its operational era
The organizations that move fastest won’t simply be the ones with the most GPUs. They’ll be the ones that can deploy, govern, secure, and scale AI reliably across real production environments. That’s the direction we at Cisco are building toward.
And this week at Cisco Live, we’re taking several leaps forward in making that possible.
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