The cybersecurity skills shortage is well documented, but the gap seems to be widening. The 2019 Cybersecurity Workforce study produced by nonprofit (ISC)² looked at the cybersecurity workforce in 11 markets. The report found that while 2.8 million people currently work in cybersecurity roles, an additional 4 million were needed -- a third more than the previous year -- due to a "global surge in hiring demand." As companies battle a growing array of external and internal threats, artificial intelligence (AI), machine learning (ML), and automation are playing increasingly large roles in plugging that workforce gap. But to what degree can machines support and enhance cybersecurity teams, and do they -- or will they -- negate the need for human personnel? These questions permeate most industries, but the cost of cybercrime to companies, governments, and individuals is rising precipitously. Studies indicate that the impact of cyberattacks could hit a heady $6 trillion by 2021. And the costs are not only financial. As companies harness and harvest data from billions of individuals, countless high-profile data breaches have made privacy a top concern. Reputations -- and in some cases people's lives -- are on the line. Against that backdrop, the market for software to protect against cyberattacks is also growing.

At some point last year, Google's constant requests to prove I'm human began to feel increasingly aggressive. More and more, the simple, slightly too-cute button saying "I'm not a robot" was followed by demands to prove it -- by selecting all the traffic lights, crosswalks, and storefronts in an image grid. Soon the traffic lights were buried in distant foliage, the crosswalks warped and half around a corner, the storefront signage blurry and in Korean. There's something uniquely dispiriting about being asked to identify a fire hydrant and struggling at it. These tests are called CAPTCHA, an acronym for Completely Automated Public Turing test to tell Computers and Humans Apart, and they've reached this sort of inscrutability plateau before. In the early 2000s, simple images of text were enough to stump most spambots.

Last summer at the Black Hat cybersecurity conference, the DARPA Cyber Grand Challenge pitted automated systems against one another, trying to find weaknesses in the others' code and exploit them. "This is a great example of how easily machines can find and exploit new vulnerabilities, something we'll likely see increase and become more sophisticated over time," said David Gibson, vice president of strategy and market development at Varonis Systems. His company hasn't seen any examples of hackers leveraging artificial intelligence technology or machine learning, but nobody adopts new technologies faster than the sin and hacking industries, he said. "So it's safe to assume that hackers are already using AI for their evil purposes," he said. "It has never been easier for white hats and black hats to obtain and learn the tools of the machine learning trade," said Don Maclean, chief cybersecurity technologist at DLT Solutions.

Last summer at the Black Hat cybersecurity conference, the DARPA Cyber Grand Challenge pitted automated systems against one another, trying to find weaknesses in the others' code and exploit them. "This is a great example of how easily machines can find and exploit new vulnerabilities, something we'll likely see increase and become more sophisticated over time," said David Gibson, vice president of strategy and market development at Varonis Systems. His company hasn't seen any examples of hackers leveraging artificial intelligence technology or machine learning, but nobody adopts new technologies faster than the sin and hacking industries, he said. "So it's safe to assume that hackers are already using AI for their evil purposes," he said. "It has never been easier for white hats and black hats to obtain and learn the tools of the machine learning trade," said Don Maclean, chief cybersecurity technologist at DLT Solutions.

Last summer at the Black Hat cybersecurity conference, the DARPA Cyber Grand Challenge pitted automated systems against one another, trying to find weaknesses in the others' code and exploit them. "This is a great example of how easily machines can find and exploit new vulnerabilities, something we'll likely see increase and become more sophisticated over time," said David Gibson, vice president of strategy and market development at Varonis Systems. His company hasn't seen any examples of hackers leveraging artificial intelligence technology or machine learning, but nobody adopts new technologies faster than the sin and hacking industries, he said. "So it's safe to assume that hackers are already using AI for their evil purposes," he said. "It has never been easier for white hats and black hats to obtain and learn the tools of the machine learning trade," said Don Maclean, chief cybersecurity technologist at DLT Solutions.

Last summer at the Black Hat cybersecurity conference, the DARPA Cyber Grand Challenge pitted automated systems against one another, trying to find weaknesses in the others' code and exploit them. "This is a great example of how easily machines can find and exploit new vulnerabilities, something we'll likely see increase and become more sophisticated over time," said David Gibson, vice president of strategy and market development at Varonis Systems. His company hasn't seen any examples of hackers leveraging artificial intelligence technology or machine learning, but nobody adopts new technologies faster than the sin and hacking industries, he said. "So it's safe to assume that hackers are already using AI for their evil purposes," he said. "It has never been easier for white hats and black hats to obtain and learn the tools of the machine learning trade," said Don Maclean, chief cybersecurity technologist at DLT Solutions.

Humans have so far failed to keep up with the scale and sophistication of cyber attacks -- so security companies are now starting to put their faith in artificial intelligence to protect networks from hackers. From Apple to Twitter, tech companies are snapping up artificial intelligence start-ups and using the technology to do everything from predicting customer behaviour to interacting with users via virtual personal assistants. For security companies, the growth of more sophisticated artificial intelligence promises the opportunity to catch up with hackers, who experts say have the upper hand. For example, as the industry struggles to find qualified engineers, many companies are turning to artificial intelligence to supplement their workforces. Tomer Weingarten, chief executive at security software provider SentinelOne, says cyber security is one of artificial intelligence's most promising applications. "It can look at all the behaviours and interactions that happen on a given machine, the malware [cyber attack software], what happens when someone is attacking you, to learn what'badness' looks like, how an attacker behaves and what they will do once they try to compromise the device," he says.