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As the trend of adopting AI and machine-learning in business becomes more prevalent, it will also impact the lives of employees in the workplace. While businesses are looking to AI and machine-learning as the holy grail for increasing profit and enhancing employee efficiency, there can be challenges with integration. However, despite the challenges, the benefits of adopting AI far outweigh the concerns – especially when it comes to employee advancement. At the core of every business decision, it's critical executives understand how new technologies not only benefits their business methods, but also how they impact their employees' workload. Here are three ways AI can benefit employees professionally.

Sponsored by MightyRecruiter, the all-in-one recruiting software that provides the tools you need to find the candidates you want. Artificial intelligence (AI) and machine learning are changing the face of recruiting, making it easier and quicker for recruiters and hiring managers to identify appropriate applicants, even for the most complicated roles. That's a good thing, since polls suggest that 2017 is going to be a very busy year for recruiters. Fifty-six percent of companies indicate that their hiring volumes will increase this year, but only 35 percent of businesses anticipate adding recruiting staff to manage the extra workload. That means efficiency in the form of AI and machine learning is going to be become even more important, as recruiters and hiring managers hustle to fill more vacant positions than ever in a 40-hour work week.

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Over the last several years, millennials have been upending the consumer market as companies scramble to find the best way to attract the world's first group of digital natives, a wily lot who thrive on innovation, automation and all of the latest tech gadgets.

A proactive and dynamic response to digital identity security is now critical. Latest figures from fraud prevention organisation Cifas show there has been a sharp rise in identity fraudsters applying for loans, online retail, telecoms and insurance products. Simon Dukes, chief executive of Cifas, says: "We have seen identity fraud attempts increase year-on-year, now reaching epidemic levels, with identities being stolen at a rate of almost 500 a day." Proving your identity has always been essential, but none more so than across the digital landscape. It's not surprising that artificial intelligence (AI) and machine-learning are being rapidly developed as an aid to identity authentication.

The term Artificial Intelligence (AI) has been around for a while. A quick search on the web reveals that the field of modern AI was born in the year 1950, when Alan Turing published a paper on thinking machines. Here we are, almost seven decades later, still in the advent of this emerging technology. Over the last few years, Google CEO, Sundar Pitchai has been speaking about the increasing role of AI in software and it seems like this year might be the inflection point for the field. In May 2017, Pichai explained how at Google, it is an "AI-first" approach for several of its products.

In the last two years, the number of machine-learning (ML) startups has skyrocketed, and companies (in truth or in hype) increasingly predicate their value proposition on artificial intelligence (AI). Although ML and AI in healthcare and finance have garnered a tremendous amount of venture investment and press, other areas, such as marketing and business intelligence, have the potential to more quickly impact profitability, and are less fettered by regulation. As of last year, there wasn't serious consensus or research into current and future AI marketing trends, so we decided to poll and interview over 50 ML and AI marketing executives. The goal: to determine the industries and applications with the most promise. The full ML-in-marketing survey, conducted over three months, sheds light on various noteworthy trends and patterns; below, after defining some terms, I've highlighted three major findings.

In the last two years, the number of machine-learning (ML) startups has skyrocketed, and companies (in truth or in hype) increasingly predicate their value proposition on artificial intelligence (AI). Although ML and AI in healthcare and finance have garnered a tremendous amount of venture investment and press, other areas, such as marketing and business intelligence, have the potential to more quickly impact profitability, and are less fettered by regulation. As of last year, there wasn't serious consensus or research into current and future AI marketing trends, so we decided to poll and interview over 50 ML and AI marketing executives. The goal: to determine the industries and applications with the most promise. The full ML-in-marketing survey, conducted over three months, sheds light on various noteworthy trends and patterns; below, after defining some terms, I've highlighted three major findings.