Artificial Intelligence hot air creating real risks for enterprises
The hype around artificial intelligence (AI) in cybersecurity has reached a fever pitch.
Just look at the news and you’ll see stories about how AI will transform cybersecurity practices—making threat detection faster and more accurate than ever before. Marketing materials from next-generation vendors claim that their AI-powered tools are ‘truly innovative’ solutions that can protect your business from the rising number of cyberattacks.
The hype appears to be working. Three out of four IT decision makers believe that AI is the silver bullet to solving their cybersecurity challenges—as revealed in our recent survey conducted with OnePoll. Respondents from the US were most likely to believe this, in comparison to their European counterparts—82% compared to 67% in the UK and 66% in Germany. IT decision makers are optimistic about AI, and its sidekick machine learning (ML), with 79% of respondents saying they would help their organization detect and respond to threats faster and 77% believing they will help solve a skills shortage.
When you consider the increase in the number of data breaches enterprises face, and the fact that hackers are only becoming more complex and targeted in their tactics, you can understand why businesses are wanting to believe there is a silver bullet solution for their ongoing battle against cyber crime.
While it would be nice to believe that this silver bullet exists, it’s simply not true. The claims are misleading, and the hype could be putting businesses at greater risk.
No one-size-fits-all solution
As we have seen, things in the digital world don’t have an easy solution. Change comes rapidly, and the playing field can shift in a matter of minutes. So, it wouldn’t be wise to rely on a single technology to build a robust defense against cyberattacks. It’s worrying to see that the hype around AI and ML is causing so many IT decision makers—particularly in the US—to consider putting all their eggs in the AI basket.
However, it’s also concerning to see such a gap in the responses from US IT decision makers and those in Europe. Could it be that all the hype is causing European IT decision makers to tune out and turn a blind eye to the benefits that ML has in cybersecurity?
This could be a problem. ML is invaluable in today’s cybersecurity practices, particularly malware detection. ML refers primarily to a technology built into a company’s protective solution that has been fed large amounts of correctly labeled clean and malicious samples to learn the difference between the good and the bad. With this training, ML is able to analyze and identify most of the potential threats to users and act proactively to mitigate them.
But it needs to be just one part of your overall cybersecurity strategy.
Time to face facts
During our research, we also asked our respondents whether they felt their company understood the difference between AI and ML. Just 53% of IT decision makers said their company fully understands the differences between the two.
The terminology used in today’s media and marketing materials when talking about AI and ML is often misleading. In many cases, ML is wrongly interchanged with AI. Put simply, AI happens when machines conduct tasks without pre-programming or training—this doesn’t exist yet.
ML, in comparison, relies on training computers to use algorithms to find patterns in vast amounts of data and identify data based on rules and information they already have. ML is nothing new. It’s been present in cybersecurity since the 1990s. The majority of IT decision makers have already implemented ML in their cybersecurity strategies, with 89% of German respondents, 87% of US respondents, and 78% of UK respondents saying their endpoint protection product uses ML to protect their organization from malicious attacks.
In today’s business environment, where the threat landscape is only becoming trickier to navigate, the industry needs to be making things much clearer for IT decision makers. Businesses cannot afford to be confused—the cost is too high. There needs to be greater clarity because, right now, the hype is muddling the message for those making key decisions on how best to secure their company’s networks and data.
It’s time to turn down the heat on the AI hype. You need to fully understand the challenges your business specifically faces; only then can you consider the solutions that will best meet your specific needs. ML will help—but it’s not the sole answer. It’s simply not mature enough to be the only layer standing between your business and cyberattackers. Multi-layered solutions, combined with talented and skilled people, will be the only way to stay a step ahead.
Want to find out more? Read ESET’s white paper, ”Is the AI hype putting business at risk?”
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