Addressing Data Privacy Concerns with AI and LLMs in the Enterprise

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With the significant strides in artificial intelligence (AI) technology, large language models (LLMs) usage promises exciting possibilities for businesses worldwide. While AI is poised to be the future of innovation and efficiency in the corporate realm, there are valid concerns about data privacy and security. In this blog, we will delve deeper into industry concerns about AI and data privacy and how companies like Productbot AI strive to ensure your data remains secure.

Data privacy with AI and LLMs

Industry Concerns

Big Data and Intellectual Property

An overarching point of contention lies in how AI uses corporate data. For AI systems to perform effectively, they require vast training data. The larger the data set and parameters used in creating the LLM, the better the ability to answer more questions. The LLM model is created from large training sets, but the real power of AI is unleashed when a company’s internal data sets are utilized to augment AI responses. Naturally, it sparks fear about the possible misuse of intellectual property. Big AI tech companies promise to safeguard this data, but the reality of upholding this promise is an issue riddled with uncertainty and concern.

Access Controls on Internal Data

Another principal concern is the lack of dedicated tools or access control systems to manage who can access these data sets once they are handed to the AI. Are there iron-clad assurances that these models wouldn’t be paraded around, compromising corporate data and inadvertently giving competing organizations a head start?

Addressing Data Privacy Concerns with AI Head-on

Understanding the gravity of these issues is pivotal to grasping what is at stake and discovering how companies such as Productbot AI are changing the narrative. Productbot AI embraces a customer-centric approach that recognizes the importance of data privacy and security, ensuring they are never overlooked. The Productbot AI enterprise deployment is designed to secure and control business data at the AI layer and with stringent SOC 2 Type 1 compliance.

Your Data, Your Models

Our company’s policy is clear — we do not train on business data or conversations. This approach shields customer businesses’ critical data from being used as fodder for AI learning.

Moreover, Productbot AI has made substantial strides to allow enterprises to utilize any large language model, even running hosted LLMs that connect to the Productbot AI enterprise deployment.

Dedicated Compliance

Sharp focus is on compliance, and Productbot AI’s framework is constructed around the SOC 2 Type 1 guidelines, ensuring effective measures are in place to maintain high levels of data security and privacy. Learn more about our SOC2 in our Trust Portal.

Hosted AI or Managed AI Instances

Whether you opt for hosting LLama 2 in your cloud provider or using the Productbot-managed AI solution, the assurance of data security remains constant. This dedicated focus on preserving client data’s sanctity, control over the AI, and security means that you can choose how you want your AI system without worrying about data privacy or security.

Llama2 Meta AI

Final Thoughts

Data privacy concerns in AI continue to be hotly contested. But with companies like Productbot AI championing data privacy and security, there is increasing confidence that AI can be harnessed without compromising data privacy. While we push the boundaries of AI and LLMs, never forget the importance of securing your data and creating a winning formula that safeguards your corporate interests while leveraging the potential and promise of AI technology. The journey towards a fully secure, AI-driven enterprise ecosystem may be long, but with assured steps, we’re getting there.

Addressing Data Privacy Concerns with AI and LLMs in the Enterprise

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