Thanks to ChatGPT and other similar applications, artificial intelligence (AI) and its potential uses are the focus of many conversations these days. Naturally, there is a lot of confusion over what exactly AI is and how it can benefit us in our jobs. As a third-party risk manager, it's essential for you to stay up to date with the latest developments in AI and machine learning (ML) – and understand how to use these technologies to enhance your risk management processes while avoiding their potential pitfalls.
This post defines AI-related terms, shares ways that AI can benefit third-party risk management (TPRM) programs, and recommends resources for learning how to use AI to be a more effective in your job role.
Artificial intelligence (AI) is a field of computer science focused on creating machines that can perform tasks typically requiring human intelligence. AI systems use algorithms and large datasets to process information, recognize patterns, and make informed predictions or recommendations. The benefits of AI include task automation, improved problem-solving, enhanced decision-making and more.
Machine learning (ML) is a subset of AI that enables computers to learn from data and improve their performance over time without being explicitly programmed. It's like teaching a computer to self-sufficiently recognize patterns and make predictions based on examples it has seen before.
Machine learning can be categorized into various types, including supervised learning, unsupervised learning, and reinforcement learning. Each type has specific risk management applications and use cases, including:
As a risk manager, being knowledgeable about AI and machine learning will enable you to harness the potential of these technologies, identify potential risks associated with their implementation, and make informed decisions on how to leverage them effectively and responsibly in your third-party risk management strategies.
Here are just a few of the ways you can leverage AI in your third-party risk management program:
How Will AI Impact Your TPRM Program?
Read our 16-page report to discover how AI can lower third-party risk management costs, add scale, and enable faster decision making.
Learning about AI and machine learning may seem intimidating, but there are several accessible and practical ways to get started. Here are six recommendations to help you expand your knowledge in this area:
Many platforms offer beginner-friendly online courses and tutorials on AI and machine learning. Look for courses designed specifically for non-technical professionals. These courses often provide a high-level overview of the concepts, applications and potential risks associated with AI and machine learning. Some popular platforms for online learning include:
Look out for workshops, seminars or webinars conducted by industry experts or organizations that focus on AI and machine learning for non-technical audiences. These events often provide practical insights and real-world examples that can help you understand the relevance and implications of AI in risk management. One such source is The Future of AI and Its Impact on Your Organization (gartner.com).
There are plenty of books and articles written for non-technical readers that explain AI and machine learning in simple terms. Look for books or articles published in business or risk management journals. These resources can provide a solid foundation and help you grasp the broader implications of AI in your field.
Engage in discussions with colleagues or teams who have expertise in AI and machine learning. By collaborating with them, you can gain insights into how these technologies are being used in practical applications and understand potential challenges and solutions from a risk management perspective.
Attend conferences, panel discussions, and industry events that focus on AI, machine learning, and third-party risk management. These events provide networking opportunities, and you can learn from professionals who have implemented AI solutions in their organizations. Listening to case studies and success stories can help you understand the benefits and limitations of these technologies.
One of the most significant concerns surrounding AI and machine learning is data privacy and security. Businesses that utilize AI need to comply with strict data protection regulations like the General Data Protection Regulation (GDPR) in the European Union or similar laws in other regions. Companies must ensure that they collect, store and process data responsibly and with user consent. With new laws and guidelines continuously being proposed and implemented, it is crucial to refer to the latest regulations and developments in specific regions and industries.
Remember that you don't need to become a technical expert in AI and machine learning. As a third-party risk manager, your goal is to have a working understanding of these technologies, their implications, and how they can enhance your third-party risk management strategies. Focus on learning the foundational concepts, understanding relevant applications, and staying informed about the evolving landscape of AI in your industry. Over time, you can build on this knowledge and collaborate with technical experts to make informed decisions and recommendations in your role.
For more on how your organization can take advantage of AI and ML technologies to improve your TPRM program, read How to Harness the Power of AI in Third-Party Risk Management, or request a demo for a strategy session today.
Prevalent continues to set the pace in third-party risk management with customer-focused enhancements that simplify the...
06/12/2024
The European Union today approved sweeping AI regulations, set to go into effect in 2026. Here...
03/13/2024
World governments and standards bodies have started to respond to AI technologies with new compliance regulations...
01/04/2024