Home Technology The digital infrastructure of businesses is not yet ready for AI

The digital infrastructure of businesses is not yet ready for AI

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The digital infrastructure of businesses is not yet ready for AI

Building the infrastructure to support AI is a priority for IT leaders
(photo: CC0 Public Domain)

More than four out of 10 surveyed global IT leaders (42%) and 56% of their colleagues in Bulgaria believe that their existing IT infrastructure is not fully prepared for the demands of artificial intelligence (AI) technology, despite its widespread application in industries, according to an Equinix study.

Significant breakthroughs in AI over the past year have led to rapid adoption of the technology in both the business-to-business and business-to-end-user sectors, notes the Equinix 2023 Global Tech Trends Survey report, which examines IT leaders’ responses to the advancement of AI in their organizations.

Artificial intelligence is increasingly becoming a critical factor that enables the implementation of intelligent and autonomous systems in business. “Those who fail to take full advantage of it can be left behind,” said Kaladhar Voruganti, senior technologist at Equinix.

The study confirms that the penetration of AI is growing across all sectors, with 85% of the 2,900 IT decision-making professionals surveyed worldwide, and 61% of those in Bulgaria, wanting to take advantage of AI and already using or plan to use it in multiple key functions.

Organizations are most likely to use AI or plan to do so in IT operations (85%), followed by cybersecurity (81%) and customer experience (79%). In Bulgaria, the top 3 functions in which to apply AI are IT operations (61%), cyber security (57%) and e-commerce (56%).

“Successful development of accurate AI models depends on secure and high-speed access to both internal and external data sources, which can be spread across multiple clouds and data intermediaries,” says Voruganti. “For example, as organizations embark on building their own proprietary generative AI solutions, they may want to process their confidential data in a private and secure location with high-speed access to external data sources and AI models.”

In addition, he said, we are entering an era in which more data is generated at the edge. Therefore, AI processing should happen there with productivity, privacy and cost optimization in mind.

To meet the above requirements, technical leaders can implement hybrid solutions where AI model training and model inference can be done in different locations. Ultimately, to create scalable AI solutions, organizations must assess whether their IT infrastructures can handle the volume of data required, sharing, storing, and processing massive and diverse data sets while keeping sustainability in mind.

IT leaders in EMEA feel the most uncertainty about their infrastructure’s ability to meet the needs of AI (49%), compared to leaders in Asia Pacific (44%) and the Americas (32%).

In addition to digital infrastructure renewal, the study also highlights the need for education and collaboration for IT teams to optimize the deployment of this infrastructure. 37% of those growing their IT teams are looking for expertise in AI and machine learning.

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