The CIO AI and data: How to use artificial intelligence and machine learning to make your data useful

Unless you’ve had your head under a data centre, you’ve likely heard the industry continue to usher in the age of artificial intelligence (AI) and machine learning (ML), touting both as the new messiahs at the feet of which all CIOs should be kneeling.  But should the CIO really be worshiping AI and data?

We can start with what hasn’t happened. AI hasn’t become sentient and enslaved us just yet. It has matured though, with applications increasingly harnessing AI as it enters the mainstream.

As AI-enabled technologies continue to emerge, CIOs across the globe will forge their own understanding and view of AI and what it means to them. For me, AI allows technology to simulate something a human would typically do. ML, then, is when technology goes beyond simulating and begins to learn for itself.

Of course both AI and ML are only as good as the data they have access to. The more data, the more intelligence provided. The cleaner the data, the more precise the prediction. They can also help to make that same data incredibly useful.

AI can be used as a tool to collect additional information from the huge amounts of data every enterprise has and, used correctly, can assist organisations in analysing and automating data, allowing for incredibly intelligent business insights.

Show me the data: How organisations can make best use of their most precious asset

How can organisations make the best use of their data to drive business transformation; with insights from Simha Sadasiva, co-founder and CEO at Ushur

Digital transformation

AI has far too often been considered as a standalone component, not a company-wide tool. However, businesses that have had the most success from AI are those incorporating it in every aspect of their digital transformations.

Sales teams, for example, can leverage predictive modelling to predict which product will sell best, in what region, and when. Those dealing with customer, on the other hand, may use AI to analyse customer data and anticipate product issues before even the customer notices, offering an unprecedented level of proactive customer satisfaction.

AI has a place in every corner of a business and CIOs implementing new and improved applications would be wise to first ensure they are equipped to leverage their business intelligence.

Smooth operations

For a business’ IT suite to run well it’s no longer enough to have an eye on the here and now: CIOs also need to know what’s around the corner. From predicting if your infrastructure will go down, a specific web server will face an issue, or you’re likely to be targeted in a cyber attack, AI and ML can give businesses the best fighting chance to tackle these issues head on, instead of being caught in the dark.

Ransomware is an issue that organisations all over the world are having to face, and one that AI and ML can help with. What if you could monitor your user behavior in your organisation, establish a baseline of what ‘normal’ looks like, and then automatically be alerted by unusual behavior that strays from this? It would enable you to react almost instantaneously when an attack occurs and minimise overall downtime. Machine learning algorithms could then continuously improve the approach over time, allowing you to stay ahead of new threats.

How can a small company turn data into an advantage and grow their business?

VHR Global Technical Recruitment, a small recruitment firm, has used data to massively grow their business and increase their turnover

Human productivity

As powerful as AI and ML currently is, I’m (fairly) confident that we’re still a long way away from robots stealing our jobs. In fact, rather than replacing staff, AI is actually supporting employee productivity by freeing employees to focus on the work they need to do and remove as much else as possible. Quite simply, it’s empowering staff to better service their role, by improving workflows, search and discovery, and collaboration, to name a few.

One example of this is native language processing, by which listening devices can understand what a human is saying and interpret that to somebody else in their native tongue. For colleagues or customers communicating from one continent to the next, this application would make it seamless for one person in China to speak to another in Venezuela, regardless of their individual native languages.

Think of AI as another team member, albeit an extremely efficient employee that plays a role in every inch of your business and empowers all other staff to be the best they can be.

Start today

When discussing AI implementation with organisations, I’ve found that the biggest obstacle stopping them from achieving all of the above comes from being overwhelmed at where to begin — they want the insights, but don’t have the data strategies in place to fuel it. My advice is always the same: focus on the data you have now, and grow from there. Some intelligence is infinitely more useful than no intelligence, and your data deposit can only get bigger.

From self-healing infrastructures to self-aware security and anticipating the future, AI algorithms first need access to historical data. To provide this, the savvy CIO may first want to implement a cloud data management platform that knows exactly where all data throughout the business resides. With the right technical architecture in place, all your applications will benefit from your data repository and make intelligent decisions.

So, do you want to lead your business blind, or by torchlight? Do you want to lead your industry, or are you content with second place? I don’t need predictive intelligence to guess the answer.

Avon Puri is the CIO of Rubrik

Editor's Choice

Editor's Choice consists of the best articles written by third parties and selected by our editors. You can contact us at timothy.adler at stubbenedge.com