Exploring the Challenges and Opportunities of Generative AI in Enterprise Risk Management

Generative AI tools like OpenAI’s ChatGPT and Google Bard have gained widespread availability, sparking concern among enterprise risk executives during the second quarter of 2023. This growing apprehension can be attributed to the exponential growth in public awareness and usage of generative AI tools, as well as the vast array of potential use cases and associated risks that come with them, according to a recent survey by Gartner.

During the survey, Gartner polled 249 senior enterprise risk executives to provide leaders with insights into emerging risks. Generative AI emerged as the second most frequently mentioned risk in the survey, reflecting the urgency to address the risks and regulatory challenges associated with these tools. The report offers an in-depth analysis of various emerging risks, including their potential impact, time frame, level of attention, and perceived opportunities.

In addressing enterprise risks related to generative AI, Gartner experts emphasize three crucial aspects: intellectual property, data privacy, and cybersecurity. Intellectual property concerns revolve around the possibility of sensitive information entered into generative AI tools becoming part of the training set, inadvertently infringing on others’ intellectual property rights. Educating corporate leadership about the importance of caution and transparency in the use of these tools is essential for mitigating such risks.

Data privacy is another critical consideration, as generative AI tools may inadvertently share user information with third parties without prior notice, potentially violating privacy laws. Regulations surrounding data privacy have already been implemented in several jurisdictions worldwide, with proposed regulations emerging in countries like the USA, Canada, India, and the UK.

Furthermore, the threat of cybersecurity breaches looms over enterprises utilizing generative AI. Hackers are constantly exploring novel ways to exploit new technologies, and generative AI is no exception. There have already been instances of malware and ransomware code being generated by these tools, as well as “prompt injections” attacks that trick the AI into divulging sensitive information. As a result, advanced phishing attacks are becoming more prevalent, posing significant challenges to enterprise cybersecurity.


What are the key risks associated with generative AI?
The key risks associated with generative AI include intellectual property infringement, data privacy violations, and cybersecurity breaches.

How can generative AI infringe on intellectual property?
Generative AI tools can inadvertently incorporate sensitive or confidential information into their outputs, potentially infringing on the intellectual property rights of others.

How does generative AI impact data privacy?
Generative AI tools may share user information with third parties without prior notice, violating privacy laws in various jurisdictions.

What are the cybersecurity risks associated with generative AI?
Hackers can exploit generative AI tools by tricking them into producing malicious code or extracting sensitive information through “prompt injections” attacks, leading to an increase in advanced phishing attacks.

(Source: Gartner)

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