AI and the promise it holds for GRC

Artificial intelligence (AI) has the potential to revolutionze the GRC landscape, transforming the scope and functionality of risk management solutions.

The use of computers to gather, store, and analyze data has become commonplace in today’s business world. Comprehensive pipeline and big data analysis will become vital risk management tools, while AI will aid in the automation of a variety of tasks to ensure high efficiency in operations and decision making. However, many companies still use structured and unstructured data in isolated operations. Traditionally, GRC technology has been used to ensure compliance and prevent fraud and errors in organizations. By analyzing the data, GRC tools can help identify areas for improvement and offer helpful insights to business problems. But what if we could automate this process? What if we could use artificial intelligence to take these tasks out of the hands of employees partially or even completely?

“Artificial intelligence and GRC is a very current topic. Many experts and researchers are writing about it and trying to push it. However, the cases are still limited in practice. There is a vision of data-driven GRC and AI-based actions based on it.” — Besfort Kuqi, CEO,?Swiss GRC AG

As the world becomes more interconnected every day, artificial intelligence helps companies avoid these structures by acting as a catalyst for forced integration between disparate structures. Moreover, AI offers a holistic view of all departments, empowering collaborative thinking and drawing attention to evidence-based decision making by breaking down these barriers. In a world where enterprise risks are growing every day, it is important to reduce wastage of time and AI provides a faster way to identify, sort and analyze risks as they develop. GRC software powered by artificial intelligence provides a big picture in which companies can work inside: from compliance to IT security, legal functions, analytics and audits, creating a powerful mechanism for companies to better protect themselves with the help of AI.

Potential and limitations of incorporating AI in GRC solutions

One of the most valuable aspects of artificial intelligence is its ability to automate tasks that would normally take humans hours. AI is essentially a type of technology that can learn from, and then mimic human behavior. In other words, it is a computerized technology that simulates human intelligence and behavioral patterns. Consequently, it is designed to think, feel, and behave like humans. To do this, AI has to mimic the neural networks of the human brain. This way, it can process information more like a human would and make decisions more like a human would. Interestingly, AI systems have been around for decades now, but recently they have made some major breakthroughs in software design and hardware capabilities. These new AI technologies are able to go beyond just understanding natural language and computer programs to being able to actually learn for themselves how to behave in various situations.

The potential power that AI could bring to GRC is tremendous. Imagine being able to analyze large data sets in seconds or minutes instead of hours or days. This increased speed would have huge impacts on many companies in finance, medicine, law enforcement, education, marketing, and more. It would allow them to identify problems faster and provide information in real time when possible.?However, this all hinges on one factor: whether or not AI can be trusted with sensitive data. Like any machine learning program, an AI system will learn from its environment based on what it is told by its human masters. If it is taught to prioritize efficiency over accuracy when crunching numbers, then its conclusions will reflect that bias.

Although AI has been present as a buzzword for a while now, its power is enormous only if it is used responsibly. In theory, the idea of artificial intelligence is captivating. If we could automate processes and free up employees to focus on other tasks, we could potentially see increased productivity and better outcomes. While this concept sounds great in theory, it is yet important to be aware of the limitations and shortcomings of AI and GRC technology as well. For starters, there are some inherent risks that come with using AI for GRC purposes. The first risk is the possibility of not having enough data for AI to make sense of what is happening in your company. This means that if you do not have enough data inputted into the AI software or database already, it may not be able to provide all the necessary insights required by your organization. Another risk is that an algorithm can never take into account every possible factor, which means there is always a chance that something could slip through the cracks and go unnoticed. While these risks do exist and should be acknowledged, they do not pose as much of a threat as they might seem at first glance. In fact, these risks exist regardless of whether you are using human intelligence or machine intelligence for GRC.

Disrupting the world of risk management with AI-based GRC technology

GRC technology has traditionally been used to ensure compliance and prevent fraud and errors in organizations. However, this method is often too costly for smaller businesses. By analyzing the data, GRC tools can help identify areas for improvement and offer helpful insights to business problems. The problem with this type of analysis is that it requires human input. HR professionals, accountants, CEOs — all of these people are needed to make sense of the data generated by GRC software. This means that there is still a need for humans in the process, which is problematic when you consider the cost involved in hiring these professionals. If we could automate this process, we would save companies both time and money, and it would likely offer better insights into their company’s data than any human could provide on their own.

There is no mistaking that artificial intelligence has the potential to disrupt the world of risk management. Predictive analytics, machine learning, and cognitive computing are all relatively new technologies that could present valuable use cases to transform the GRC landscape and make a huge impact. For example, if someone has to manually update a spreadsheet with data from a disparate system, AI can update it automatically. Another way AI helps GRC is by identifying risks before they happen. By analyzing data from different sources, AI can identify trends or potential problems before they happen, alerting companies and helping them to avoid losses.

Data collection is a significant part of GRC technology. The analysis of data can be used to identify problems and patterns that may not have been noticed before. For example, let’s say we’re using GRC technology to help with customer support. Once we identify areas for improvement, we might then create a rule that will flag issues in the future. By correcting these issues before they happen, we can create a better customer experience and improve the company as a whole. AI can be used to automate tasks like data collection, data analysis, and risk assessment. It can also be used to make decisions about certain processes, like triggering an alarm when a vulnerability is discovered or making decisions based on the results of predictive analytics models. Machine learning is one aspect of AI that’s could be used in GRC technology. Machine learning learns from patterns in data, which means it gets smarter over time. Its algorithms are great because they can use past data to predict what will happen in the future. For example, if you need your system to predict bugs in your software, you could use machine learning algorithms to analyze past bugs and their causes. From there, it would learn what triggers bugs and can identify which areas need improvements before they become problems for your team. Another important potential benefit of AI in GRC is predictive maintenance. Companies spend a lot of time and money ensuring that their equipment is in working order. But imagine if your computer systems were always running at peak performance, reducing the risk of costly downtime? Predictive maintenance can be a huge benefit to an organization, especially when you consider all the different ways it could be applied. Imagine being able to proactively identify any issues with equipment or personnel? You could then have the opportunity to take corrective measures before they become a problem. In theory, this should help reduce cost and ensure efficiency within an organization.

The state of artificial intelligence in GRC today is still in its infancy, with much room for future growth

Current GRC processes and tools force analysts to look at disparate manual processes and tools to find insights, hence inefficiencies that prevent companies from meeting compliance requirements. There are a number of complex business processes supporting business operations that are tightly coupled to multiple IT systems, some of which may still be performed manually. As a result, analyzing, reporting and making sense of large manually collected datasets to obtain relevant information is not only time consuming but also error prone. Today, most organizations are looking to improve their GRC initiatives with better technology. Artificial intelligence has the potential to provide the most innovative solution. However, AI is not perfect and it is important to consider the limitations of these solutions. The use of artificial intelligence in GRC is not without challenges. The technology has to be trained, and that takes time and money. However, AI’s ability to sense and react to threats before they happen will help companies reduce the risk of data breaches, cyberattacks and other risks. Organizations should provide employees with comprehensive training on how the technology works so they can better prepare for potential pitfalls. Employees who understand how artificial intelligence operates can help devise strategies around how it may impact their job duties and responsibilities. Ultimately, the experience of designing and deploying AI in GRC will be a true test of creativity and innovation for GRC professionals.