There has been a lot of focus on AI recently with Elon Musk and Bill Gates taking very different views. From a perspective of cybersecurity, AI is now essential. It’s essential because of the sheer amount of data that can now be collected and stored – indeed we now talk about data lakes.

Analysing and collecting this data for intelligence requires not only machine learning but increasingly significant AI capabilities. This is why NTT spends significant amounts on R&D with the focus for us to provide quality in context intelligence.

But why is this important? The accuracy of turning huge amounts of data into intelligence is essential in cybersecurity with our focus on having 95 to 98% accuracy in the alerts and information we provide in our automated threat defense service. We bridge the small gap with our dedicated threat intelligence team and analysts. As threats continue to evolve in not only sophistication and frequency, they are also leveraging AI and machine learning to evade and attack our infrastructure and critical systems.

Our focus is to proactively protect an organization and this requires a shift to Security Orchestration, Automation and Response (SOAR). We are at a tipping point in our services and understanding, which allows us to proactively protect an organization because we know the context of the threat and the target. Our resilient cyber defense architecture is focused on prediction by leveraging complex threat intelligence gathered through our Global Threat Intelligence Centers.

We also collaborate with the wider threat intelligence community which supports our proprietary global threat intelligence platform. A platform that allows us to feed our managed security services and our clients within context threat intelligence and not data noise. Our continued focus with our strategic technology partners allows us to take proactive action across our clients’ infrastructure.

With a complex and hostile threat landscape, combined with a skills shortage, we have to take full advantage of AI and machine learning but we must also embrace the automation of our responses.