AI in GRC: from agitation to advantage
AI in GRC: from agitation to advantage

The Rise of Artificial Intelligence (AI) in GRC: Trends and Use Cases

Vivian Susko |

Emerging developments in AI, Machine Learning, Natural Language Processing, Automation, and More – Where Does it All Fit Inside the World of GRC? 

AI-driven technology has been making headlines for breakthroughs as well as breakdowns lately (like ChatGPT’s March breach).  But while reasonable hesitation still surrounds some of its newer use cases, the specific benefits of its other (more established) applications – like within governance, risk, and compliance space – far outpace the risk.

Not only can AI-driven technology and automation help organizations build a stronger cyber risk management program with limited resources, but it also makes risk monitoring and management more adaptive, agile, proactive, and scalable. What’s more, global data from IBM reveals that 35% of companies already report using AI in their business while 42% are exploring it. So, to put it plainly, AI will come across your desk in one form or another – you may as well understand how to leverage it as a tool rather than adding it as another risk factor. 

Let’s dive into some of the top use cases of AI-driven GRC technology – and stay tuned for a look at the continuation of this discussion at Interact 2023 with GRC Analyst & Pundit Michael Rasmussen.

Artificial Intelligence (AI) in the GRC space

AI-enabled GRC technology delivers a game-changing competitive advantage by allowing organizations to instantly reveal and quantify risk, collaborate cross-functionally, increase efficiency, and create unrivaled, actionable, business intelligence that ultimately drive performance and shareholder value.

Some of the most common use cases where AI-enabled GRC technology is applied in the GRC space include: 

  • Building a proactive risk management program
  • Automatically analyzing deviations in compliance
  • Defining control frameworks
  • Automating traditionally manual processes like data collection or risk assessments
  • Streamlining policy management & so much more!

Let’s dive into a few in detail!

Automation, Automation, Automation

One of the main advantages of AI-driven tools is automation. Whereas traditionally manual processes (like incident management, reporting, etc.) can create a heavy workload, consume valuable time, and are often more error-prone, automation corrects these weak spots and boosts efficiency within teams. For example, AI driven GRC technology solutions can be leveraged to automate:

  1. Data Gathering and Collection: A GRC solution powered by AI can be utilized to automatically gather and process vast amounts of data from several sources. NLP capabilities can be applied to extract relevant information and structure it in an easily understandable format.
  2. Risk Assessments: AI engines allow for automated risk assessments and can easily predict potential risks. Furthermore, ML capabilities can be leveraged to identify risk mitigation strategies in time.
  3. Monitoring: GRC technology driven by AI can automate the monitoring of regulatory compliance by continuously analyzing regulatory changes in standards, laws and regulations of relevance to the organization.
  4. Reporting and Analytics: AI capabilities can identify risks and make predictions, allowing proactive actions to be taken in order to prevent or mitigate potential issues both within the organization or across its entire value chain. 

AI-enabled GRC solutions with Machine Learning (ML) and Natural Language Processing (NLP) capabilities can also help process large volumes of data in minutes, detect risks, and offer valuable data that not only can transform decision-making from reactive to resilient.

Leveraging ML & NLP Capabilities

Increased regulatory demands continue to be a challenge for organizations across the globe – especially considering the speed and complexity in globally connected organizations. [Watch the latest episode of Mitratech’s Morning Coffee: Global & Extended Regulatory Environments for more on how regulatory compliance is more interconnected than ever before.] Here’s the main takeaway: what might seem local, almost certainly translates to a global scale.

GRC technology tools can be a critical ally in this regard and can help in various ways. ML capabilities can now help analyze the content in regulations and easily understand where there might be gaps in the organization’s existing frameworks. 

Furthermore, compliance teams can automate the way they analyze standards, laws and regulations in the context of their control frameworks and use NLP to interpret organizational policies and documents.

Deploying the right GRC technology within an organization simplifies the management of complex risk and compliance data. And as the scope and sophistication of cyber attacks continues to rise, AI-driven solutions will prove invaluable allies.