AI Isn’t Coming. It’s Already Here

Let's be honest-we've all been talking about AI like it's something off in the distance. A thing we'll prepare for "someday." But that moment? It's already passed.

AI isn't coming. It's here. Right now.

Not tucked away in a lab. Not limited to data scientists. But embedded into how people are actually getting work done across every function, every department, every industry.

And here's the kicker: the network most enterprises are running today? It wasn't built for this. Not even close.

The shift that already happened

Everywhere I look, I see AI going mainstream. Not in some flashy, sci-fi kind of way, but in practical, everyday workflows. Sales teams using copilots to write proposals. Marketers generating entire campaigns with a prompt. Security teams leaning on models to detect threats faster than any human could.

It's not hype. It's not someday. It's here.

AI is fundamentally altering how networks operate, driving new traffic patterns, latency demands, and workload behaviors.

Let me walk you through a few examples that really bring this to life.

LLMs in the cloud and SLMs at the edge to get work done

Right now, people across your company are using AI-powered tools to summarize emails, analyze data, write reports, and even build code. Most of those tools rely on large language models (LLMs) in the cloud, which means their devices are constantly talking back and forth with AI application programming interfaces (APIs).

But there's a shift underway. As GPU costs drop and infrastructure at the edge improves, we're starting to see a move toward small language models (SLMs) running right in the branch or campus-closer to the user, where the data is.

Why does this matter for the network? Because suddenly there are two completely different traffic patterns to deal with:

• Heavy north-south traffic from the user to the cloud
• New east-west traffic flows from local AI workloads spinning up on the edge

Both types of traffic need low latency and high performance to feel seamless to users.

Real-time video analytics

Cameras are no longer just recording video. They're analyzing it in real time. Whether it's detecting intruders, analyzing foot traffic, or tracking safety compliance, the AI-based analysis is happening live, often at the edge.

That process of recording and analyzing generates a ton of high-bandwidth traffic, and it can't all be shipped to the cloud. To avoid security risks and allow for rapid response, data needs to be processed locally with speed and precision. Traditional networks just weren't designed for that kind of load at the access layer.

Live transcription and translation during meetings

Now, let's say you're on a Webex call and the meeting is being transcribed and translated in real time. Seems simple, right? But behind the scenes, your device is sending and receiving a constant stream of audio and data to an AI engine. Just one lagging translation engine can throw a meeting off course: misinterpreting key phrases, dropping sentences, and leaving participants confused. Responses slow down, clarity fades, and the conversation quickly loses momentum.

All of which means high-performance networking suddenly becomes the difference between a smooth user experience and a rough one.

AI agents spawning AI agents

This one blows my mind a little. We've entered the era of "agentic AI," where a single AI agent doesn't just do something for you by itself-it can recruit other agents to help.

Ask your AI assistant to "launch a marketing campaign." It spins up one agent to pull CRM data to create a strategy, another to write copy, another to generate visuals, and yet another to launch and track the content across channels.

Each of these agents is communicating with systems, data sources, and each other at high velocity and often without human involvement. And the related network traffic patterns? They're completely different from anything a traditional network was built to handle. We're no longer optimizing for people clicking around. We're optimizing for AI talking to AI.

AI-augmented access control

Authentication is no longer just about passwords. Many organizations are turning to AI-powered facial recognition, voice biometrics, and behavioral analysis. These technologies can offer faster, more secure access, but only if your network can support them.

Say an employee is working remotely and trying to log in to a secure dashboard using voice biometrics. They speak the passphrase, but the system hesitates-just long enough to time out. They try again. Still no luck. Now they're locked out, the clock's ticking on a deadline, and they're stuck waiting for IT to sort it out.

All of this because the network couldn't prioritize the traffic fast enough for real-time authentication. It's a small delay with a big impact-and a clear sign that the infrastructure might not be ready for AI-driven security.

What this means for the network

If you're thinking, "Wow, none of this sounds like what we built our network for," you're not wrong.

AI is rewriting the rules and bringing with it:

• Unpredictable traffic patterns
• Huge spikes in east-west and north-south flows
• Tight latency requirements
• An explosion of short-lived, dynamic workloads
• Agent-to-agent traffic that most IT tools aren't even tracking yet

The bottom line? The old model-where networks were designed for people using apps-doesn't cut it anymore.

Now, your network has to support machines talking to machines-at machine speed.

If AI has already changed your network, what are you doing to keep up?

This isn't about preparing for AI. That window's closed.

This is about realizing that AI is already changing the behavior of your infrastructure. Whether your architecture evolves to support that reality will determine if you keep pace or fall behind.

Because AI isn't coming.

It's already here.

To keep up, your operations need more than old-school methods. You need smart, autonomous agents that make everything run smoother and faster. It's not just an upgrade-it's how you stay ahead.

Curious how Cisco is leading the shift to AgenticOps?

Read the Showcase from Enterprise Strategy Group.