EDITOR ’ S COMMENT
While an understanding of data science and maths is useful for successful AI deployment in a business , it really depends on whether you ’ re building or customising something yourself .
SAMANTHA HUMPHRIES , HEAD OF SECURITY STRATEGY EMEA , EXABEAM
AI offers huge practical benefits – both in terms of a vastly improved customer experience and as a support mechanism for the entire workforce . However , concerns around Artificial Intelligence ( AI ) and automation have become so widespread that it ’ s created a sort of moral panic around the term . Needless to say , these concerns are for the most part unfounded . There have been some amazing advancements in AI that mean a more tailored experience for consumers . At its core , AI provides a toolset that can predict problems , identify solutions and then put these into motion . From a cybersecurity perspective , being able to respond to potential issues faster and more accurately is so important . Ultimately , this translates to better protection for consumers , their data and the services they rely on .
The power and potential of AI may seem scary , but by helping operational staff to do a better job , more accurately and more efficiently , the technology is providing huge value across all industries . When it comes to explaining Machine Learning to endusers , simplicity but accuracy are key . In the words of Einstein : “ If you can ’ t explain it simply , you don ’ t understand it well enough .” And it ’ s true ; vendors are often good at explaining the benefits of Machine Learning tangibly – and there are many – but not the process behind it , and hence it ’ s often seen as a buzzword . Machine Learning can seem scary from the outset , because ‘ how does it know ?’ It knows because it ’ s been trained , and it ’ s been trained by humans . We feed it information , and then it can make decisions based on that information faster than we ever could . From this , it can spot anomalies quicker , which means it can alert a human or another machine to go and do something about that problem .
While an understanding of data science and maths is useful for successful AI deployment in a business , it really depends on whether you ’ re building or customising something yourself . A lot of products with built-in Machine Learning and AI will function out of the box pretty well . It can take a couple of weeks to normalise , but in a lot of cases , you can leave AI to get on with it . We ’ ve seen success many
times , even within the first few days of deployment , where our technology is already picking up abnormalities that would not have been seen through any other mechanism . If you have a good vendor , they should also have a simple and digestible way that allows you to tweak the sensitivity of the interface . For us at Exabeam , for example , we can help to tailor the AI based on the customers ’ needs and what ’ s important in their IT environment . You don ’ t necessarily need a doctorate from Cambridge to deploy AI and automation technology to your business in a meaningful way .
Ultimately , AI is there to support you , and it will pave the way for more interesting , Value Add positions . AI brings speed and accuracy , which will give individuals time back in a notoriously under-resourced industry . We do not need to fear AI and Machine Learning . We should be celebrating the rewards and the opportunities it will open up for us . •
Machine Learning can seem scary from the outset , because ‘ how does it know ?’
INTELLIGENT TECH CHANNELS
INTELLIGENT TECH CHANNELS Issue 37
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