Solving Manual Mayhem in Telecom with Agentic AI

The day’s just begun, and ​a small mistake sets off a chain reaction. A missed click or mistyped command knocks a network offline and sends employees scrambling. As downtime drags on, customers become frustrated and team morale falls. ​​ ​

This isn’t a one-off crisis​; ​​52% of communications and media providers say downtime is ​often ​or ​very often​ the result of human behavior​—​and it takes the longest to find and fix.​

As customer expectations rise and operations become more complex, even seasoned teams struggle to keep pace.

The rising flood of data from our increasingly connected world adds to the challenge. Traditional tools are overloaded, making it hard to create meaningful visibility and insights.

The latest generation of AI offers a way forward: it contextualizes data to drive smarter decisions. And unlike past models, agentic AI doesn’t just assist—it acts.

Targeted AI for Telecom Challenges

As customer interest in next-gen services grows and network buildouts continue, communications and media companies need agentic AI to bring autonomy, adaptability, and real-time decision-making to the heart of their operations. AI is already addressing some of the most urgent industry concerns: fighting cyber attacks, maintaining uptime and reliable networks, and improving service levels.

• Network optimization with foresight: Agentic AI predicts issues before they occur—minimizing downtime, improving performance, and keeping services running smoothly.
• Adaptive security and fraud detection: Eighty-two percent (82%) of communications and media industry leaders say it is hard to maintain effective security hygiene and posture due to an expanding attack surface. AI agents can monitor real-time traffic patterns and adjust security protocols in response to emerging threats, working faster than humans can.
• Smarter, self-directed virtual assistants: Virtual agents powered by agentic AI go beyond scripted responses. They interpret intent, take proactive steps, and resolve issues autonomously to reduce the load on support teams and elevate customer experience.
• Personalized, real-time customer engagement: By analyzing context, preferences, and behavior, agentic AI delivers personalized offers and experiences at scale.
• End-to-end process automation: From fault detection to ticket resolution, agentic AI can orchestrate entire workflows—automating not just tasks, but decisions—with minimal human input.

Why Data Still Rules

AI agents need accurate, high-quality, and well-structured data to reason, plan, and act. Agentic AI will hit a wall if data is siloed, outdated, or inconsistent.

Clean, unified datasets are essential to surfacing meaningful insights and making intelligent decisions. Fifty-five percent (55%) of communications and media companies are already making data quality a priority.

Setting realistic expectations is also key to unlocking data’s full potential. Agentic AI can’t—and shouldn’t—replace human intelligence across the board. But when deployed strategically, with clear scope and reliable data, it can offload repetitive tasks, boost response times, and enhance decision-making.

Of course, no AI strategy is complete without security and governance at the core. AI agents often touch sensitive customer and network data. Without strong controls, communications and media companies risk data exposure, non-compliance, or unintended system behavior. Governance frameworks should evolve with AI capabilities.

Laying the Groundwork for Agentic AI

To create a resilient, AI-forward enterprise, communications and media companies should focus on these three building blocks:

1. Unified and contextual data: Splunk and Cisco combine deep infrastructure telemetry and market-leading data processing to unify fragmented machine data. This approach provides real-time, actionable insights across security, networks, and applications—turning data overload into a strategic advantage.
2. Agentic AI for autonomous, cross-domain action: Together, Splunk and Cisco will build a foundation for the future by infusing agentic AI capabilities—reasoning, adapting, and acting autonomously—into SOC, observability, and network assurance solutions. AI-native features will manage the full data lifecycle and provide built-in guardrails for security and compliance.
3. Interoperability to break down silos: Splunk’s commitment to open standards like OpenTelemetry, the Open Cybersecurity Schema Framework, and the Model Context Protocol will power seamless integration across hybrid environments and AI agents. Interoperability can power full-stack visibility, reduce blind spots, and support workflow automation to amplify human and AI productivity.

By building a foundation for AI and tapping into its benefits, communications and media companies will reduce stress on their workforce and quickly deliver more secure, personalized experiences to customers.

Ready to get your data house in order so you can fuel the future for agentic AI? Learn how in our Communications and Media industry brief.