There’s a lot of talk about the ability of AI and machine learning to augment digital transformation journeys by creating better customer experiences and empowering employees to make decisions using data. However, IT and business leaders can sometimes face analysis paralysis when confronted with this topic because it means something different for every business – and it means shifting an entire company culture towards a new way of working. One key shift is making use of machine data.

Stock sales and trading play a huge role in the U.S. and global economy. Stock exchanges provide the backbone to the economic infrastructure of our nation, as they help companies to expand when they’re ready by offering the general public a chance to invest in company stock. However, investing in the stock market can be a gamble.

At a point in time, smart devices and robotics were common elements in the storyline of futuristic fictional novels. Today, those concepts are the modern norm across the technology industry. Similarly, in cybersecurity, pioneering professionals held on to seemingly far-fetched dreams where logs were easy to analyze, and false positives didn’t exist. While these challenges still exist, artificial intelligence (AI) is making these once far-fetched dreams the new norm in the security industry.

Artificial intelligence (AI) is used all around us and if you’ve used some sort of voice activated technology to make your life easier, then there was likely some element of AI involved. Some of the most notable examples include Siri, Amazon Alexa, Google Assistant and Tesla semi-autonomous vehicles. Individual consumers no longer have to fumble around in the dark to flip the light switch at home, manually search playlists for songs, or type in a password to get into smartphones.

Computers are making humans now. Sort of. In a recent discussion at Bulletproof, someone casually mentioned ‘thispersondoesnotexist.com’. It’s a fairly harmless experiment in which AI randomly generates an image of a person who does not exist, thus solving the mystery of the name. This has since prevented me from sleeping at night, not least because I have turned up on it more than once.

Machine learning (ML) technology has the potential to generate tremendous value for businesses. It is already proving itself in the market and powering a growing number of tools across virtually every industry. In order to discuss the current capabilities of ML, we must first examine how it relates to artificial intelligence (AI). Then, we can explore where ML software is today, its real-world applications, and how it’s transforming business.

Cybersecurity is a manpower constrained market – therefore, the opportunities for artificial intelligence (AI) automation are vast. Frequently, AI is used to make certain defensive aspects of cyber security more wide-reaching and effective. Combating spam and detecting malware are prime examples.

Artificial intelligence and its cousin machine learning are words that keep cropping up in almost every industry at the moment. Sometimes as buzzwords, sometimes with real innovation, but always with the outlook that both Ai and ML are going to be employed a lot more across a whole spectrum of businesses.

Gone are the times when endpoint protection was limited to installing an anti-virus and expecting a reasonable level of protection. With the introduction of Bring Your Own Device (BYOD) and increasing number of IoT devices, there are more endpoints than ever and so are the security threats associated with them.

Recently the Economist published two articles that discussed the increasing use of AI and employee monitoring in the workplace. Veriato is pleased that we were referenced in both of these articles. We feel they did a good job of presenting a balanced view of the benefits both AI and employee monitoring offer, as well as the potential downsides if they are not implemented and used wisely.