Cisco AI Research: AgenticOps Scaling Quickly in the Enterprise

Cisco’s Omdia-backed survey shows rapid shift toward AI-led NetOps, with strong enterprise demand for explainability, observability and integrated platforms.

Rhea-AI Summary

Cisco (CSCO) released new Omdia research on how enterprises are adopting agentic AI in network operations (AgenticOps).

The survey of 1,000 IT and NetOps leaders at organizations with 500+ employees finds 95% say existing, non‑agentic AIOps tools fall short, while 51% already run agentic AI acting in production. On average, organizations generate about 4,100 monitoring alerts daily, more than half network related, and would need roughly 100 IT specialists to clear the network-alert backlog manually.

The report shows 80% are comfortable granting AI a high or fully autonomous NetOps role, including 24% with no human oversight, and 84% expect an AI‑led operating model within 12 months. At the same time, 86% view a single integrated platform as the best path to scale agentic AI, 69% require detailed explainability for agent-driven actions, and 36% see full observability as the minimum standard.

Key Figures

Survey respondents: 1,000 IT and network operations leaders Existing AIOps tools falling short: 95% Daily alerts and events: about 4,100 per organization +5 more

Survey respondents

1,000 IT and network operations leaders

Independent Omdia study; organizations with 500 or more employees

Existing AIOps tools falling short

95%

Respondents reporting one or more significant shortfalls

Daily alerts and events

about 4,100 per organization

Average daily volume reported in the study

Agentic AI in production

51%

Organizations reporting agentic AI acts in production today

Expected AI-led operating model

84%

Respondents expecting this within twelve months

Integrated platform preference

86%

Respondents identifying a single integrated platform as the most effective path forward

Explainability requirement

69%

Respondents requiring detailed explainability for agent-driven actions

Additional network traffic from agent tasks

up to 450% more

Cisco testing; total network traffic generated by agent tasks

Key Terms

aiops, telemetry, observability

3 terms

aiops technical

"existing, non-agentic AIOps tools fall short"

AIOps (Artificial Intelligence for IT Operations) uses machine learning and data analysis to monitor, detect, and resolve problems in an organization’s technology systems automatically. It matters to investors because it can cut downtime and operating costs, speed up fixes, and make digital products more reliable—similar to an autopilot that notices and corrects issues before they disrupt service, which can protect revenue and reduce operational risk.

telemetry technical

"aggregated direct-to-AI network telemetry"

Telemetry is the automatic collection and transmission of measurements from remote devices, systems, or patients to a central system for monitoring and analysis—like a car sending engine, speed and location data back to a dashboard. For investors it matters because telemetry provides real-time evidence of product performance, safety and user behavior, helping assess revenue potential, operational risk, regulatory compliance and whether a product is meeting market demand.

observability technical

"full observability, including detailed tracing"

Observability is a company’s ability to see and understand what its software systems are doing by collecting and analyzing signals like logs, metrics and traces. For investors it matters because strong observability reduces the risk of downtime, hidden bugs or security issues, supports faster fixes and efficient scaling, and therefore can protect revenue, lower costs and signal disciplined operations — like having clear gauges and alarms on a complex machine.

AI-generated analysis. How Rhea-AI works. Not financial advice.

See more from StockTitan in Google Search and AI answers. Adds StockTitan as a preferred source · opens Google

Add on Google Not now

New Cisco and Omdia research shows 95% of enterprises say their existing AIOps tools can't keep up, and more than half have already moved to AgenticOps 

News Summary

• The alert math no longer works. At current volumes, the average organization would need roughly 100 IT specialists to clear its daily network alert backlog by hand.
• Enterprises have moved past advisory AI. Over half now run agentic AI systems that act in production today.
• Comfort with autonomy is already high. Four in five are comfortable granting agents a high or fully autonomous role, including nearly a quarter who would proceed with no human in the loop.
• Trust is the condition, and it requires one place to see it all. Over two-thirds require detailed explainability for agent-driven actions, and 86% say a single integrated platform, not another point tool, is the most effective path forward.

SAN JOSE, Calif., Sept. 23, 2026 /PRNewswire/ -- Cisco (NASDAQ: CSCO) today announced the release of The Impact of Agentic AI on Network Operations, new research examining the state of network operations (NetOps), AI adoption, and attitudes toward AI autonomy and trust. Findings show that amid rising complexity, organizations are moving quickly toward agent-driven operations: AgenticOps. More than four of every five respondents expect to reach an AI-led operating model within 12 months, with more than three-quarters willing to grant agentic AI significant autonomy in NetOps, including nearly a quarter that are comfortable with fully autonomous operation and no human oversight.

Conducted independently by Omdia, the study surveyed 1,000 IT and network operations leaders at organizations with 500 or more employees. The findings indicate that organizations have moved from AI in an advisory role to AgenticOps for agent-powered network operations in which operators set direction and guardrails while AI agents sense, reason, and act across domains. It comes as NetOps teams face rising performance expectations and increasingly dynamic environments, with AI workloads adding new traffic patterns, performance requirements, and operational complexity.

"Agentic AI represents a fundamental paradigm shift: moving from running operations to orchestrating intent," said Joe Vaccaro, SVP/GM, Network Platform & Assurance at Cisco. "Agentic AI for NetOps requires trust built on visibility into every decision, explainable context behind every recommendation, and guardrails that ensure deterministic outcomes. Organizations that master this balance will keep operators firmly in command while enabling agentic systems that act with confidence, validate outcomes, and continuously prove operational trust."

Key Takeaways from The Impact of Agentic AI on Network Operations Report

The findings show that agent-driven AI has taken on operational responsibility in NetOps. This shift is occurring as the average organization generates about 4,100 monitoring alerts and events each day; more than half of them are network related. At this volume, manually clearing the daily network-alert backlog would require roughly 100 IT specialists. Organizations also report that nearly half of network alerts are closed without investigation, and an almost identical number of respondents report investigation time is spent pursuing false positives. As adoption advances, requirements for built-in trust are shaping how organizations implement and scale AI.

• Operational complexity is placing pressure on traditional NetOps models. Organizations report managing high alert volumes, continuous change, fragmented tooling, and issues that span multiple domains. Against this backdrop, a vast majority (95%) say their existing, non-agentic AIOps tools fall short in one or more significant areas.
  • 92% report that performance issues commonly span multiple domains, requiring correlation across ten or more tools for resolution.
  • 57% say their current change processes can't match the speed required today.
• AI adoption creates new demands on the network. That operational complexity is compounded as AI adoption grows and agents operate at software speed, generating unpredictable traffic patterns and greater data exchange.
  • AI traffic is on a trajectory to double every six months, according to a Cisco analysis of aggregated direct-to-AI network telemetry.
  • When traffic generated by agentic AI is included, Cisco testing found that tasks performed by agents can generate up to 450% more total network traffic.
• Organizations are turning to an agent-driven network. Many organizations are allowing AI agents to take on more responsibility in NetOps, including making production changes such as rerouting traffic, adjusting wireless parameters, isolating suspicious endpoints, and resolving incidents end to end without prior human approval.
  • 75% have already deployed AI for NetOps.
  • 51% run agentic AI that acts  in production today.
  • 80% are comfortable granting AI a high or fully autonomous role in NetOps, including 24% who are comfortable with AI acting with no human oversight.
  • 82% are comfortable allowing AI to make at least some production network changes without prior human approval.
  • 84% expect an AI-led operating model within twelve months.
• Organizations will scale agentic AI on the condition of visibility and trust. Organizations are open to greater agent-driven operations in NetOps, but their willingness to scale it depends on transparency, visibility, and controls.
  • 86% say a single integrated platform is the most effective path forward.
  • 69% require detailed explainability for agent-driven actions.
  • 36% say full observability, including detailed tracing, summarized rationale, and post-action audits, is the minimum acceptable standard.

"The striking takeaway is not simply that AI adoption in NetOps is growing, but how quickly organizations are preparing for AI-led operations," said Jim Frey, Chief Analyst, Network and IT Operations, from Omdia. "The findings point to a broader shift from the advisory model of AIOps to agent-powered operations, AgenticOps, that can take action. As that shift accelerates, integrated visibility, strong governance, and measurable outcomes will be critical to expanding autonomy while maintaining operational control."

"Our team isn't growing, but complexity keeps increasing with significant momentum," said Mark Rodrigue, Senior Network Engineer at Room & Board. "Deep reasoning in the Cisco AI Assistant is one example of AgenticOps for us. Questions that used to mean a manual hunt-and-click exercise across dashboards and multiple data sources now come back in minutes, with the executive summary first and the supporting evidence underneath. That's a force multiplier! It shows its work, so I can follow the logic and see the full evidence chain behind every recommendation. That's the trust it takes to deploy agents at scale."

Background

• The Impact of Agentic AI on Network Operations report is based on data from an independent global survey of 1,000 IT and network operations leaders, conducted by Omdia.
• Survey respondents were decision-makers at organizations with 500 or more employees across North America, Western Europe, and Asia-Pacific.

Additional Resources

• Download The Impact of Agentic AI on Network Operations report
• Blog: NetOps is already deploying agentic autonomy – trust will decide how far it goes

About Cisco
Cisco (NASDAQ: CSCO) is the worldwide technology leader that is revolutionizing the way organizations connect and protect in the AI era. For more than 40 years, Cisco has securely connected the world. With its industry leading AI-powered solutions and services, Cisco enables its customers, partners and communities to unlock innovation, enhance productivity and strengthen digital resilience. With purpose at its core, Cisco remains committed to creating a more connected and inclusive future for all. Discover more on The Newsroom and follow us on X at @Cisco.

Cisco and the Cisco logo are trademarks or registered trademarks of Cisco and/or its affiliates in the U.S. and other countries. A listing of Cisco's trademarks can be found at www.cisco.com/go/trademarks. Third-party trademarks mentioned are the property of their respective owners. The use of the word partner does not imply a partnership relationship between Cisco and any other company.

View original content to download multimedia:https://www.prnewswire.com/news-releases/cisco-ai-research-agenticops-scaling-quickly-in-the-enterprise-302887642.html

SOURCE Cisco Systems, Inc.

FAQ

AI-generated questions and answers. How Rhea-AI works. Not financial advice.

What is meant by AgenticOps in this Cisco research?

AgenticOps refers to agent-powered network operations in which human operators set intent, direction, and guardrails while AI agents sense, reason, and act across domains. The research describes this as a shift from AI in an advisory role to AI systems that take operational actions in NetOps.

How was the Agentic AI study conducted?

The report is based on an independent global survey by Omdia of 1,000 IT and network operations leaders. Respondents were decision-makers at organizations with 500 or more employees across North America, Western Europe, and Asia-Pacific.

What operational challenges are NetOps teams reporting?

Organizations report high alert volumes, continuous change, fragmented tooling, and issues spanning multiple domains. For example, 92% say performance issues commonly span multiple domains and require correlation across ten or more tools, and 57% say current change processes cannot match today’s required speed.

How is AI traffic affecting network complexity?

The research notes that AI adoption adds new traffic patterns and performance requirements. Cisco analysis of aggregated direct-to-AI network telemetry indicates AI traffic is on a trajectory to double every six months, and Cisco testing found that tasks performed by agents can generate up to 450% more total network traffic when agentic AI traffic is included.

What conditions do enterprises place on scaling agent-driven operations?

Enterprises tie greater agent-driven NetOps to transparency, visibility, and control. 86% say a single integrated platform is the most effective path, 69% require detailed explainability for agent-driven actions, and 36% state that full observability, including tracing, summarized rationale, and post-action audits, is the minimum acceptable standard.