AI and machine learning: Data centres need to differentiate themselves to survive

05Mar

The interest in adding Artificial Intelligence (AI) and machine learning (ML) to business models is fast gaining momentum as organisations look to find patterns within their data that can deliver greater business and customer intelligence, and predict future trends.

As Gartner highlights, the number of enterprises implementing AI tripled in the past couple of years. In this article, Peter Ruffley, Chairman at Zizo, discusses how we can best use AI and what its role is within the data centre.

The promise of AI

At present, the IT industry is doing itself no favours by promising the earth with emerging technologies, without having the ability fully to deliver them; see Hadoop’s story with big data as an example – look where that is now. There is also a growing need to dispel some of the myths surrounding the capabilities of AI and data-led applications, which often sit within the C-suite, that investment will give them the equivalent of the ship’s computer from Star Trek, or the answer to the question ‘how can I grow the business?’ As part of any AI strategy, it’s imperative that businesses, from the board down, have a true understanding of where the real value of AI lies.

If there are a clear business need and an outcome in mind, then AI can be the right tool. But it won’t do everything for you – the bulk of the work still has to be done somewhere, either in the machine learning or data preparation phase.

Read the full article in the March issue of PBSI