AI and the importance of data management

Abstract of data in binary code - AI and data management
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Ask people what technologies will power the future of business, and you’ll get similar answers: AI, machine learning, blockchain – the list goes on.

It’s absolutely true that these technologies will transform how businesses operate. While some innovations (quantum computing for example) will take a while before they are here, others have arrived and are already making a big impact.

About the author

Jack Watts is EMEA Leader of Artificial Intelligence for NetApp.

AI of course has captured the public’s imagination for some time, and businesses are currently grappling with how it can be integrated into their organization. In fact, AI has become so prolific, the EU has recently set a series of new rules (known as the AI Regulations) that seek to regulate how businesses use the technology.

This is the first legal framework of its kind – both at a European and global level – and will apply both to EU countries, and those working with them. Challenging the common view of Silicon Valley which feels emerging technology should be left alone, the regulations will ban certain uses of AI, and curtail others.

The rules stipulate that AI needs to be tested, and a certificate gained before it can be placed on the market, according to its risk level. Ultimately, it’s about making sure AI is transparent and secure – which will hopefully bolster public trust.

But I’m not going to get into the specifics of whether these regulations are effective or not. The point is that AI adoption has grown to the point where law bodies feel they need to intervene. The technology is now a common part of our lives – and businesses that haven’t fully embraced it are starting to fall behind.

The importance of data management

Embracing AI takes more than investment in the latest shiny toy. Businesses need to completely reimagine their IT infrastructure and address challenges from data management to ensuring efficiency across workloads.

There are many different types of AI technology, but the one thing they all have in common is the consumption of vast amounts of data. AI works by processing data, spotting hidden patterns, then predicting future events or making autonomous decisions based on those insights. Simply put, data is the lifeblood of AI. And anything that compromises the quality of data will have a detrimental effect on the technology’s outcomes. And one of the most common bottlenecks we see is poor data management.

To get the most out of AI, data needs to be properly managed – whether it be structured or unstructured. Data needs to be available anytime, anyplace. But doing so in a secure and yet connected way – especially during an age when IT estates are larger than ever – is a real challenge.

The move to the cloud

For many, cloud computing is the key to overcoming this hurdle. By storing data in the cloud, businesses can eliminate silos, and make data available no matter where employees are located.

Cloud adoption has been on the increase for years, but the pandemic has really been a turning point. Gartner reports a 23.1% YoY increase in worldwide end-user spending on public cloud services, which will see global cloud spend rise to $332.3 billion. This huge increase is likely due to businesses speeding up their transformation programs and realizing just how critical cloud is.

Research conducted by us also gives an interesting picture. We found 87% of employees believe storing data in the cloud is easier than other storage methods – showing that when it comes to organizational benefits, convenience is king. This is despite almost one in two employees (47%) saying they are not using all of the cloud services at their disposal, and 74% do not believe their business is maximizing the opportunities that cloud services can offer.

Our own data suggests that businesses using cloud could reduce their digital wastage by up to 60%. This frees up IT budgets to invest in cloud services to automate manual processes and harness the power of their organizational data – again empowering businesses to utilize AI.

A post-COVID world

Whichever way you look at it, cloud and data management are essential to AI adoption – as well as being a vital first step on the road to digital transformation. COVID has motivated many to start that journey. And those that haven’t are quickly realizing they are starting to fall behind.

It’s fascinating seeing AI go from a science fiction pipedream to something so tangible it needs to be regulated. Although businesses will need to tweak their use of AI based on the EU AI Regulation – and any other regulations that are set – the base tenets of the technology will always remain the same: reimagine your infrastructure, embrace cloud, and put in place best practices in data management to ensure you fully unlock its’ potential.

Jack Watts is EMEA Leader of Artificial Intelligence for NetApp.