Role of Governance, Risk and Compliance in Safe AI Implementation

Specialists can develop relevant AI policies and procedures to protect organizations against potential legal pitfalls

Mikhail Dunaev, Chief AI office, ComplyControl

June 7, 2024

3 Min Read
Shelves full of books and folders
Getty Images

AI use in many business areas is growing and the pace of generative AI development is not slowing down. 

According to recent market research data, the global generative AI Market is anticipated to register a compound annual growth rate of 37.8% from 2024 to 2032 and to reach $66 billion in eight years. 

Recent reports show that the rapid growth of generative AI and its implementation in various companies have significantly increased the demand for technical AI specialists. However, not only are technical specialists in demand but business leaders also prefer to hire other employees with AI experience. 

However, introducing AI into businesses may imply potential risks leading to significant financial and reputational damage, including data leakage. Governance, risk and compliance (GRC) specialists can be crucial in mitigating these threats. 

Role of GRC Specialists 

GRC specialists hold a critical position regarding potential dangers arising from using generative AI. Implementing their risk-neutralizing methods may secure the adoption of generative AI. It ensures that generative AI does not disrupt the organization's operations or breach its security. 

GRC specialists are adept at developing relevant AI policies and procedures, helping ensure organizations are well prepared to handle any situation threatening the company, including generative AI pitfalls. 

Related:Building customer loyalty through data maturity

GRC professionals can also guarantee an organization's compliance with all the regulatory requirements related to using generative AI to avoid potential legal penalties.

According to research, GRC specialists' risk management practices should include not only neutralizing threats and minimizing costs but also being drivers of generative AI integration and adaptation to business processes. 

Generative AI Challenges to GRC

One of the main challenges is the explainability of AI algorithms. The complex nature of generative AI, especially deep learning models, often makes it difficult to interpret its internal workings. This might challenge both GRC professionals and other employees. To foster trust in these systems among staff and stakeholders, GRS professionals should be able to explain their processes and make them transparent. 

Another difficulty follows from the complex nature of AI and results in potential failures in AI logic. As AI systems are trained on vast amounts of data and learn from it, there is a risk they could make decisions or take actions that were not intended or foreseen by human designers. Such inconsistency may lead to unexpected and potentially serious consequences. The role of GRC professionals is to control this situation and prevent it. 

Related:Microsoft Highlights Responsible AI Efforts in New Report

Moreover, there's a potential danger of losing confidential data on which the AI is trained. Balancing between protecting data and benefiting from generative AI is a weighty problem. Any breach or misuse of this data, especially when it comes to sensitive or secret one could have long-term consequences, including financial losses, reputational damage and penalties.

Importance of Collaboration in GRC

An important aspect of a GRC expert's role involves assessing the risks of generative AI implementation. However, generative AI adoption includes the participation of the whole team. GRC professionals are responsible for communication between departments. 

For example, they must seek to integrate their work into the processes of their company's IT department. This collaboration guarantees the generative AI initiatives align with the organization's broader technological infrastructure and strategy.

Given the industry's dramatic generative AI changes, professionals must stay updated and educate the rest part of the team. This could involve attending relevant workshops and webinars or pursuing further education on AI-leveraging practices. 

GRC professionals should also train other employees on the potential ethical issues and dangers associated with using generative AI. This is key to ensuring all the company team members understand the implications of generative AI and benefit from its use.

About the Author

Mikhail Dunaev

Chief AI office, ComplyControl, ComplyControl

Mikhail Dunaev is chief AI officer at ComplyControl, a UK company that specializes in cutting-edge technology solutions for banks. Dunaev is an experienced technical lead and software developer in the fintech sector. He joined the ComplyControl team in 2023 and oversees product management, machine learning engineering and the development of AI-driven features and technology stacks.

Keep up with the ever-evolving AI landscape
Unlock exclusive AI content by subscribing to our newsletter!!

You May Also Like