When people think of artificial intelligence (AI), the things that pop into mind are typically along the lines of advanced robotics software that controls smart houses or self-driving (or flying) cars. AI application has skyrocketed in recent years, but it has many functions beyond what we saw in the Jetsons growing up. There are numerous facets to AI that include, but aren’t limited to, machine learning (ML), natural language processing (NLP), robotic process automation (RPA), and others. NLP especially has limitless applications and potential, particularly when discussing cyber risk and cyber risk management.
Historically, companies have used IT GRC software solutions to monitor and analyze threats and vulnerabilities. But as the world segues more and more into digital transformation and organizations become responsible for the enormous amounts of data they have to ingest, the fact of the matter is that GRC solutions are not enough anymore. Legacy GRC systems leave their data too siloed, and the process is too manual to show an overarching picture of enterprise risk management. In fact, 69% of companies are not confident in their current IT GRC stack and practices are enough to support their future needs. And 60% of all interest in NLP comes from business leaders, not traditional IT professionals. Leaders are always looking for ways to push boundaries of the norm and take their company to the next level, however, it is time that security leaders took the lead to augment their own teams’ abilities.
The Importance of Natural Language Processing (NLP) in Risk and Compliance Management
The ultimate objective of NLP is to read, decipher, and understand language in a manner that is valuable to the user of a system. When looking at risk management and compliance using NLP, we’re looking for the program to alert us to specific control instances and real-time threat susceptibilities. Legacy IT GRC platforms use manual efforts and controls almost exclusively.
Many Fortune 500 companies use spreadsheets to track and monitor risks and vulnerabilities, but this is incredibly time-consuming regarding person-hours spent on one task. By the time IT professionals reach the end of the spreadsheet, it can already be out of date. This leaves organizations vulnerable and consumes valuable resources that could be allocated elsewhere. In the era of COVID-19, with many companies downsizing their security budgets, this can be a massive blow to a cybersecurity program as resources become scarcer and employees gain an ever-growing list of responsibilities.
NLP gives organizations the ability to reduce and nearly eliminate manual intervention in assessments. With the consolidation of resources and the time employees can save and use towards other projects, NLP can also foster internal innovation. Even augmenting legacy GRC systems with NLP auditing systems can significantly increase efficiency. At CyberSaint, our CyberStrong platform uses NLP to make sense of all data coming out of the security tech stack, showing where and how compliance is met across standards. Our goal is to empower organizations to manage cybersecurity as a business function and not just using the bare minimum to meet compliance requirements. Instead, using an integrated risk management approach, companies can mature their cybersecurity programs to be proactive instead of reactive.
How AI Can Augment Current IT GRC Tech Stacks
As the world shifts into digital spaces, the regulations in those spaces become stricter, and mitigating the threat of outside forces tampering with the system becomes paramount. This means an increased workload for all parties involved in compliance and risk assessment. Hunting for threats manually is time-consuming and expensive, and with downsized security teams due to the pandemic, it becomes pressing to find an alternate way to manage these threats and risks.
With automated risk platforms, it’s possible to manage risks and increase program maturity over time dynamically. Software that can continuously prioritize threats and add more automation over time across compliance, risk, and audit can make a sizeable difference in downsized security teams. It becomes possible to track tangible, measured impacts and returns on investment with a balance between quantitative and qualitative data.
Gartner predicts that organizations are increasingly leveraging automation technologies like RPA, AI, and machine learning to improve process quality, speed of execution, and employee productivity. 86% of organizations are already implementing or have implemented RPA, and Gartner estimated that AI would be a priority for 30% of organizations by 2020.
Mitigating Cyber and IT Risk Using AI
Automation and its influence will only continue to touch every aspect of digital transformation initiatives. By adopting AI into current practices, companies can transform their risk assessment strategy from just compliance into a proactive risk management strategy that would be more efficient, effective, and mitigate threats they might face. Supplementing current systems with AI can also significantly reduce person-hours and overall costs of a cybersecurity program.
To learn more about how AI can augment downsized security teams, check out our webinar here. To bring automation into your legacy GRC system or if you’re looking for a GRC replacement, request a demo.
