AI and Machine Learning: Why These Trends Will Dominate 2017
As 2016 draws to a close, the cybersecurity industry is buzzing with predictions about what the new year will bring. Among the most prominent forecasts is the continued rise of AI and machine learning trends, which have captured significant attention over the past two years. Experts agree that these technologies will not only persist but evolve, demanding sophisticated Big Data capabilities and reshaping how organizations defend against cyber threats.
The Growing Role of AI and Machine Learning in Cybersecurity
According to Sian John, Chief Strategist of EMEA at Symantec, the expansion of AI and machine learning will unlock powerful insights for businesses. She emphasizes that this growth will foster increased collaboration between humans and machines. From a security standpoint, this means impacts on endpoints and cloud mechanisms. Enterprises will need to invest in solutions capable of collecting and analyzing data from countless endpoints and attack sensors across diverse organizations and geographies.
Similarly, Staffan Truve, CTO of Recorded Future, argues that the scale and complexity of cyber threats are pushing human analysts to their limits. He predicts that the next generation of cyber threats will require a combined effort from AI-equipped machines and human experts. Truve draws a parallel to weather forecasting, where improved sensors and advanced algorithms have enhanced prediction accuracy. In cybersecurity, web intelligence offers new sensing capabilities that, combined with novel algorithms, can predict future threats.
Machine Learning: Hype vs. Reality
However, not everyone is convinced that the buzz around AI and machine learning trends translates into genuine innovation. Adrian Sanabria, senior analyst at 451 Research, warns that these terms have become buzzwords, pressuring companies to claim they are leveraging them—whether they need to or not. He points out that many security and IT vendors have used machine learning algorithms for years, with Amazon employing the technology for book recommendations in the late 1990s.
Sanabria highlights both positive and negative aspects. On the upside, machine learning helps defenders gain an edge in preventing malware infections. On the downside, it may not be as effective in addressing the information overload that plagues defenders. The quality of input data is crucial, and much of the data fed into security analytics engines—such as threat intelligence, vulnerability scans, and logs—is often low quality, raw, or unfiltered. As the old adage goes, “garbage in, garbage out.”
How AI and Machine Learning Trends Will Shape the Battlefield
On the defensive side, the McAfee Labs 2017 Threats Predictions Report from Intel Security suggests that AI and machine learning will be instrumental in teaching machines to operate on the front lines of a global battle. Eric Peterson, director of threat research at Intel Security, notes that when expertly applied, machine learning can solve complex business problems. Regression algorithms predict values, clustering algorithms reveal data structures, and anomaly detection identifies abnormal data points.
Peterson describes machine learning tools as “force multipliers” for security professionals. He warns against assuming that cybercriminals are not also adopting these powerful tools. This arms race means that organizations must stay ahead by embracing AI and machine learning trends proactively.
The Human Element: Collaboration Over Replacement
Despite the emphasis on automation, experts stress that AI and machine learning are not about replacing humans. Instead, they augment human capabilities. For instance, at Microsoft’s Future Decoded conference, the Cortana digital agent demonstrated how AI can assist in online helpdesk tasks—a far cry from the high-stakes environment of a security operations center. Nevertheless, the trend toward human-machine collaboration is undeniable.
As we move into 2017, the conversation around AI and machine learning will intensify. However, the actual impact on businesses and legacy IT systems may be slower to materialize. Organizations must navigate the hype, invest wisely, and focus on quality data to truly benefit from these transformative technologies.
For more insights on cybersecurity trends, check out our guide to cybersecurity predictions for 2017 and learn about ransomware protection tips to stay safe.
