In today's tech landscape, few developments match the excitement of generative AI tools like ChatGPT. Executives, in particular, are deeply invested in understanding how these tools will shape the future of the workplace. According to Gartner, a significant 78% of executives believe that the benefits of this technology far outweigh any potential vulnerabilities.

However, it's evident that not all executives grasp the full extent of AI security risks or comprehend the potential costs associated with breaches. This lack of understanding extends to the availability of secure AI alternatives to popular language learning models (LLMs) like ChatGPT – alternatives that offer enterprises greater control over their data.

What Goes Into Secure AI System Development?

But what does it take to develop a secure AI system?

Before delving into the specifics of AI security, it's essential to consider an organization's broader cybersecurity responsibilities. Cybersecurity involves ensuring the detection of threats and safeguarding data against unauthorized access or use, whether from external hackers or internal breaches. Additionally, secure data must remain intact and free from damage, corruption, or misuse, necessitating secure systems for its collection, utilization, and storage.

Privacy is another critical aspect of data management, encompassing measures to preserve an individual's right to control how their data is used and shared. This entails respecting preferences for confidentiality and providing mechanisms for consent and clear privacy policies. 

Compliance with laws and internal policies further reinforces data protection efforts, ensuring that organizations meet legal requirements and avoid financial and reputational damage.

What Is a Secure AI Framework?

Considering the security implications of AI tools, it's clear that individual users may not always prioritize data security when utilizing platforms like ChatGPT for tasks such as brainstorming or presentations.

However, legal teams recognize the importance of balancing AI capability development with robust data handling practices to mitigate security risks effectively. The stakes are high, as the average cost of a data breach amounts to $4.5 million, encompassing both financial losses and damage to a brand's reputation.

Navigating the complexities of responsible AI safety requires a strategic approach, one exemplified by Coveo's "Secure By Design" mission. To learn more about building secure AI frameworks, watch our free, on-demand webinar.