Cisco Systems, Inc. is a global networking and cybersecurity company that designs and sells networking hardware, software, and services for enterprises, service providers, and public sector organizations. It increasingly embeds AI/ML across networking operations, security, and observability to automate detection, remediation, and performance optimization.
Think of this as a control tower that uses AI to watch over all your IT systems, predict issues, and help fix them automatically before they impact customers.
This is about using smart software that learns from patterns in network traffic and user behavior to spot hackers and suspicious activity much faster than human teams or rule-based tools can, and then automatically block or contain threats before they spread.
This is like an AI control tower for your IT systems that constantly watches logs, metrics, and alerts, spots issues before humans notice them, and suggests or triggers fixes automatically.
This is like an always-on AI control tower for your IT systems that watches all your apps, servers, and cloud services, spots issues before users notice, and tells your teams exactly what to fix and why.
Mist AI is like an intelligent autopilot for corporate WiâFi and wired networks. It watches everything happening on your network, spots problems before people complain, and automatically fixes or guides IT on what to do.
Think of AIOps platforms as a 24/7 AI control tower for your IT systems. They watch logs, metrics, and alerts from all your tools, spot patterns humans would miss, and automatically fix or route problems before they become outages.
This is like giving your security team an AI co-pilot that watches everything in your environment in real time, spots attacker behavior (including AI-generated attacks) faster than humans can, and automatically helps block and contain those attacks before they spread.
This is like giving your companyâs security cameras and fire alarms a brain that learns. Instead of waiting for a fixed list of âbad thingsâ to happen, machine learning watches all activity on your network, learns what ânormalâ looks like, and then flags and blocks suspicious behavior in real timeâoften before humans would even notice.
This is a research survey that acts like a âbuyers guide plus textbookâ for using AI to catch hackers. It reviews how different machineâlearning and deepâlearning techniques can watch network and system traffic, learn what normal looks like, and automatically flag or block suspicious behavior in real time.
Think of AIOps as an AI control tower watching all your IT systems 24/7. It reads all the logs, alerts, tickets, and metrics, spots patterns humans miss, and then either recommends or automatically takes actions to keep systems healthy and prevent outages.
Imagine your mobile network like a huge city of traffic lights. Today, most lights stay on even when no cars are passing. AI for greener 5G makes the âtraffic lightsâ of the network smart: they dim, sleep, or reroute traffic automatically so energy isnât wasted when thereâs little or no data traffic, while still keeping the roads (connections) flowing smoothly.
Think of the mobile network as a huge city full of roads (radio links) and traffic (data). AI in 5G/6G is like a smart traffic control system that constantly watches congestion, predicts where it will build up, and automatically opens new lanes, changes traffic lights, and reroutes cars so everything flows faster and more reliably without humans having to tweak every detail.
Think of a huge telecom network like a busy, complex city traffic system. Today, human engineers are the traffic cops, constantly tweaking lights and routes to keep everything moving. AIânative autonomous network management is like upgrading to a smart city where sensors and AI automatically detect jams, reroute cars, repair issues, and optimize flows in real time, with humans supervising instead of micromanaging every intersection.
Imagine your telecom network as a huge, complex city with roads, traffic lights, and repair crews. AI here is like a smart traffic control center that watches everything in real time, predicts where traffic jams and accidents will happen, and automatically sends crews or reroutes cars before customers even notice a problem.
Think of a city where every bus, traffic light, and parking space can talk to each other in real time, and an AI âtraffic conductorâ continuously listens and adjusts things so people and goods move faster and more safely with less waste.
Think of this as an autopilot for telecom networks. Instead of engineers constantly watching dashboards and tweaking settings by hand, AI continuously watches the network, predicts problems before they happen, and automatically adjusts things to keep calls, video, and data flowing smoothly.
This is like giving your IT department a smart assistant that constantly watches all your servers, apps, and networks, learns what ânormalâ looks like, and alerts you early when something strange is happeningâbefore it becomes a major outage.
Imagine your entire IT environmentâservers, networks, apps, cloud servicesâconstantly watched by a smart assistant that never sleeps. It reads all the logs, alerts, tickets, and performance data, spots early warning signs, figures out whatâs really important, suggests fixes, and in many cases can trigger automated responses before users even notice a problem.
Think of this as a citywide âcontrol towerâ that watches whatâs happeningâtraffic, utilities, emergency calls, citizen requestsâand then uses AI to suggest faster, cheaper, safer ways to run city services.