The past decade has seen an explosion of cloud-based services and applications, remote working options, smart factories, digital and VR content, mobility options, telemedicine, and significant advances in generative AI. Most recently, we are now seeing the commercial production of humanoid robots, designed with the intention of making life easier for people and helping companies overcome the lack of appropriately trained workers for complex yet repetitive tasks. This technological evolution has resulted in increasing dependency on low-latency, resilient, and redundant connectivity as well as the need for a range of interconnection options. These factors have become essential to ensuring functionality, compliance, and performance in the context of AI. These factors are, in turn, dependent on the existence of flourishing digital ecosystems for which the existence of strong data center and carrier neutral Internet Exchanges (IXs) are indispensable.
Data is the essence of AI. That means that, for successful AI implementation, all data sources be they data lakes / warehouses or live data from IoT devices, production infrastructure, customer networks, etc. must flow unhindered to the location of the AI model for training and on to the location of the AI agent for inference purposes. The whole process can be handled in the cloud or in a hybrid environment, or it can be outsourced to cloud-based AI-as-a-Service operators; the question is how to build an infrastructure capable of supporting this next phase of enterprise technological transformation.