Bottom Line: Attacking endpoints with AI, bots, and machine learning is gaining momentum with cybercriminals today with no signs of slowing down into 2020, making endpoint security a must-have cybersecurity goal for next year. Cyberattacks are growing more complex and difficult to prevent now and will accelerate in the future, making endpoint security a top goal in 2020. Cybercriminals are using structured and unstructured machine learning algorithms to hack organizations' endpoints with increasing frequency. Endpoint attacks and their levels of complexity will accelerate as cybercriminals gain greater mastery of these techniques. In response, endpoint protection providers are adopting machine learning-based detection and response technologies, providing more cloud-native solutions that can scale across a broader range of endpoints, and designing in greater persistence and resilience for each endpoint.

Today's enterprises are faced with unique, modern-day issues. Many are focused on adopting more cloud-based services and reducing infrastructure footprint, all while the number of devices accessing the environment grows. This, in turn, requires security teams to create different levels of access, policies, and controls for users. Plus, as these businesses expand some unexpected security issues may arise, such as alert volume, lack of visibility, complicated management, and longer threat dwell times. To strike a balance between business objectives and a healthy security posture, IT teams can implement some of the tactics we recommended in our Effective Endpoint Security Strategy 101 blog, such as virtual private networks (VPNs), proper employee security training, and machine learning (ML) and artificial intelligence (AI) technology for predictive analysis.

Computing and cybersecurity aren't changing -- they've already changed. End users have transformed the way IT works, and this means the widely accepted definition of endpoints has morphed. End users want to be connected to everything, which means virtually everything is (or can be) an endpoint today. This has opened new possibilities for how we do business, but it has also created more opportunities for bad guys to infiltrate your system. To adapt to the way our modern, hyperconnected world operates, organizations must adopt a new endpoint security strategy built around artificial intelligence (AI) and machine learning.

Cybersecurity skills are on the decline. We've reported before on the cybersecurity staffing crisis plaguing enterprises around the world, but recent reports suggest that the problem is only getting worse. Yet at the same time, with the IoT revolution and the rise of Bring Your Own Devices (BYOD) workplace cultures across America, the number of endpoints enterprises need to secure are only increasing.Between 70% and 95% of security breaches originate at endpoints. So how can enterprises bridge this widening gap between increasing needs and decreasing human talent? Some cybersecurity experts looking to machine learning, a distinct subset of artificial intelligence technology, as a way to redress the balance.