A new survey has found that artificial intelligence (AI) is already powering mission critical activities in many organizations, but that digital infrastructure has not yet caught up.
According to the 2023 Global Tech Trends Survey Equinix survey, 42 percent of IT leaders globally believe their existing IT infrastructure is not fully prepared for the demands of artificial intelligence (AI) technology, despite its widespread adoption across industries.
“Tech leaders globally are expediting AI’s integration into their organizations, and it is increasingly becoming a critical capability to enable intelligent and autonomous systems that power a modern business. Those who fail to maximise its use could fall behind,” said Kaladhar Voruganti, Senior Technologist at Equinix.
The survey confirmed AI uptake is on the rise across all industry sectors, with 85 percent of the 2,900 IT decision-makers polled worldwide seeking to benefit from the advantages of AI and already using or planning to use it across multiple key functions. EMEA organisations are most likely to be using AI, or planning to do so, in IT operations (82 percent), followed by cyber security (79 percent), and customer experience (75 percent).
IT leaders in EMEA had the most uncertainty about the ability of their infrastructure to accommodate the needs of AI (49 percent), compared to leaders in Asia-Pacific (44 percent) and the Americas (32 percent).
“Successful development of accurate AI models depends upon secure and high-speed access to both internal and external data sources that can be spread across multiple clouds and data brokers,” added Voruganti. “For example, as enterprises embark on creating their own private generative AI solutions, they may want to process their confidential data at a private and secure location with high-speed access to external data sources and AI models. Furthermore, we are entering an era where more data is being generated at the edge. Hence, AI processing has to move to the edge for performance, privacy and cost reasons. In order to satisfy the above requirements, tech leaders can implement hybrid solutions where AI model training and model inference can occur at different locations. Ultimately, to create scalable AI solutions, businesses must consider whether their IT frameworks can accommodate the required data ingestion, sharing, storage and processing of massive and diverse data sets, while keeping sustainability in mind.”
