The AI Revolution We Didn't See Coming: Why Network Automation Is About to Change Forever
Summarizing Itential's AI orchestration vision from AutoCon3
"When this whole AI thing started, I was like, no, there is no way AI is ever going to touch a network," admitted Peter Sprygada, the creator of Ansible for networking. "I've run networks. I've run very large networks... there was no way AI was ever going to touch a network."
Then something interesting happened.
Speaking as someone who's spent 15 years in network automation and whose work many in the audience have cursed when Ansible playbooks take "an hour and a half to run," Sprygada brought a perspective that was both surprising and sobering: AI isn't just coming to network automation—it's going to revolutionize it entirely.
The Moment Everything Changed
The turning point wasn't ChatGPT or any consumer AI tool. It was the introduction of Model Context Protocol (MCP) in November 2024. For those unfamiliar with MCP, it's a framework that allows AI systems to interact with external tools and data sources in a structured, controlled way.
"The technology is moving extremely fast," Sprygada noted, "but it's having a very profound impact on how we can start to think about orchestration and automation."
This isn't about AI replacing network engineers or making configuration changes autonomously. It's about AI enhancing orchestration frameworks in ways that were previously impossible.
The Itential MCP Server: AI Meets Orchestration
Continuing Autocon's tradition as his platform for tool releases (last year brought Torero), Sprygada announced the Itential MCP server—an open-source tool designed to bring AI capabilities to orchestration and automation platforms.
The concept enables "genetic orchestration"—AI-enhanced workflows that can adapt and respond intelligently while maintaining the security, governance, and control that production networks require.
But Sprygada was quick to add a crucial warning.
The Security Imperative
"If it's not done in a way that we can actually bring security, governance, auditing, logging, control, it has about the equivalent of doing IPv6 on your control plane," he cautioned.
This isn't hyperbole. Unleashing AI on network infrastructure without proper controls could be catastrophic. The difference between AI-enhanced automation and AI chaos lies entirely in the framework surrounding it.
The key insight: AI must be introduced through orchestration platforms that provide:
Security boundaries and access controls
Comprehensive auditing and logging
Governance frameworks for AI decision-making
Rollback and safety mechanisms
Controlled integration points
Beyond the Hype: Adding Real Value
Sprygada's approach to AI mirrors his philosophy with Ansible a decade ago: "We have to add value with this technology. We shouldn't do it just to do it."
The question isn't whether AI can automate network tasks—it's whether AI can enhance human capabilities in ways that make operations faster, safer, and more reliable.
His vision involves AI integration at multiple levels:
Northbound: Working with observability tools to analyze and respond to network conditions
Southbound: Leveraging LLM technology to enhance configuration and troubleshooting workflows
Orchestration layer: Enabling AI to participate in workflow decisions while maintaining human oversight
The Revolution, Not Evolution
Perhaps Sprygada's most striking claim was that this change will be revolutionary, not evolutionary.
"It cannot be small incremental steps. It really is going to be a revolution. It is going to change the way that we approach things."
This suggests that organizations treating AI as just another tool in the automation toolkit may be fundamentally misunderstanding its potential impact. Instead, AI-native orchestration represents a new paradigm for network operations.
The Competitive Advantage
Sprygada believes organizations that embrace AI-native network operations will see "significant increases in their ability to be agile, responsive, and build scalable infrastructure."
This isn't just about efficiency gains—it's about capabilities that become possible only when AI is deeply integrated into operational frameworks. Think of it as the difference between using calculators to do math faster versus using computers to solve problems that were previously impossible.
The Call to Action
Despite his initial skepticism, Sprygada ended with an urgent call to action: "AI isn't going anywhere, and we need to accept that. AI is going to have a profound impact on network automation."
His recommendation? Get involved now. Not because the exact future is clear—he admits his predictions will probably be wrong in three weeks—but because understanding the technology is imperative for anyone serious about network automation's future.
"Organizations that really truly start to embrace AI and bring it into their network operational frameworks are ones that are going to see significant increases in their ability to be agile, responsive, and build scalable infrastructure."
Why This Matters
What makes Sprygada's perspective compelling isn't just his technical credentials—it's his demonstrated ability to see inflection points in network automation. His work on Ansible helped define how we approach network automation today.
If he's right about AI representing a similar inflection point, then network automation is about to undergo its most significant transformation since the shift from manual CLI configuration to programmatic interfaces.
The question isn't whether AI will impact network automation—it's whether organizations will lead that transformation or be transformed by it.
The revolution, it seems, has already begun. The only question is whether you're ready to be part of it.
Watch the full presentation: Accelerating Sponsor: Itential
