Today, business owners for enterprises of all sizes are struggling to find the next generation of solutions that will unlock the hidden patterns and value from their data. Many organizations are turning to artificial intelligence (AI), machine learning (ML) and deep learning (DL) to provide higher levels of value and increased accuracy from a broader range of data than ever before.
They are looking to AI to provide the basis for the next generation of transformative business applications that span hundreds of use cases across a variety of industry verticals. Especially, when it comes to multi-cloud environments, AI helps in organising processes and facilitates automation.
But in the absence of right algorithms, software, server hardware or data for AI, the journey to AI is not rosy. In a nutshell, businesses are grappling to get the right infrastructure in place for AI.
According to IDC, most of the businesses today are in production mode with AI and deep learning applications but at some point, they have hit the ‘infrastructure wall’, which connotes they have moved to different infrastructure not once but many times.
About 77% businesses ran into one or more limitations with their on-premise AI infrastructure and about 90% of organisations ran into such limitations while using cloud for cognitive.
Lack of interoperability in the datacentre, server virtualization difficulties, performance limits, inefficient storage, difficult to manage and scale are some of the prominent cloud infrastructure limitations with AI apps.
Owing to these challenges, although AI applications and deep learning have been around for a few years but couldn’t permeate thoroughly. As per IDC, 22.8% of businesses are on third-generation infrastructure for AI applications, 37.6% are on second-generation infrastructure and 39.6% are on first-generation servers.
As AI penetrates deeper into every workload and more and more applications get trained, using deep learning techniques, we are going to see a jump in data and algorithms. But to address this mammoth amount of data and algorithms, we require to pace up our infrastructure capabilities to run effectively and efficiently.
Becoming an AI powered business is easier, but we need to understand how we could unlock the value of our data in new ways and accelerate our journey to AI.