Generative AI is a subset of artificial intelligence (AI) that can create new content, including text, images, music, and more, by learning patterns from a training dataset. Unlike traditional AI, which focuses on specific tasks and follows pre-defined rules, generative AI can invent new content and respond creatively to inputs. It is considered the next generation of AI, capable of generating original and creative outputs. OpenAI’s GPT-4 is an example of generative AI, trained on a vast dataset to produce human-like text. The key difference between traditional AI and generative AI is that the former analyzes data and makes predictions, while the latter generates new data based on its training set.

Here are the challenges and opportunities the risk management industry faces in combating the adverse effect of Generative AI in businesses today”

  • Only 9% of companies are adequately prepared to manage the risks associated with generative AI (GenAI), indicating a significant lack of readiness in the business world.
  • A staggering 93% of companies recognize the existence of risks linked to using generative AI, demonstrating a broad awareness of the potential dangers associated with this technology.
  • Despite this awareness, just 17% of risk and compliance leaders have formally trained their organizations on the specific risks of generative AI, highlighting a lack of structured education and awareness efforts.
  • The field of generative AI is rapidly growing, creating new business risks, which implies that companies must adapt and enhance their risk management strategies accordingly.
  • Companies’ primary concerns regarding generative AI pertain to data privacy and cyber issues, employee decision-making based on inaccurate information, employee misuse and ethical risks, and copyright and intellectual property risks.
  • The top four risks currently affecting organizations are talent shortages and layoffs, recession risk, ransomware and security breaches, and state-sponsored cyberattacks, suggesting that generative AI risks are part of a broader landscape of organizational threats.
  • A majority (63%) of companies have not simulated their worst-case risk scenario, indicating a lack of preparedness for extreme or unexpected events.
  • Only 5% of companies feel fully prepared to assess, manage, and recover from unknown and unpredictable risk events, underlining the need for improved risk management strategies in this domain.
  • Additionally, just 23% of organizations are very confident in the accuracy, quality, and actionability of their risk management data, while only 5% are very confident in their ability to extract, aggregate, and report on risk insights, emphasizing the need for more robust risk management systems.

In response to these challenges, organizations are increasingly investing in addressing emerging risks, hiring chief risk officers, and boosting funding for risk management technology, indicating a growing recognition of the importance of mitigating GenAI threats and improving overall risk.