With the public release of ChatGPT and Microsoft's $10-billion investment into OpenAI, artificial intelligence (AI) is quickly gaining mainstream acceptance. For enterprise networking professionals, this means there is a very real possibility that AI traffic will affect their networks in major ways, both positive and negative. As AI becomes a core feature in mission-critical software, how should network teams and networking professionals adjust to stay ahead of the trend? Andrew Coward, GM of Software Defined Networking at IBM, argues that the enterprise has already lost control of its networks. The shift to the cloud has left the traditional enterprise network stranded, and AI and automation are required if enterprises hope to regain control.

Keysight Technologies' business Ixia has incorporated machine learning technologies into its network monitoring platform. The new technologies will help the platform, called Hawkeye, to help enterprises reduce network outage times and improve network uptime by detecting, identifying, and resolving network anomalies. The company cites statistics from Gartner, which predicts that more than 50% of new enterprise applications will incorporate machine learning or other intelligence models. Ixia also notes that as the volume and velocity of raw network and application data continues to increase, network operations teams are faced with a flood of alerts. These teams need to reduce alert fatigue and increase their ability to troubleshoot network and application issues.