In our recent survey of over 65 data scientists, we set out to understand the perceived value of AI development and uncover the moments when users experience that crucial ‘aha’ feeling with AI/ML platforms. Knowing when users recognize value within the development lifecycle helps us shape better tools and support.

A key takeaway? With the majority of organizations planning to bring AI workloads on-premises within the next few years, security and privacy are top of mind for data scientists when running AI/ML workloads locally.

Here's what we found:

• 81% of organizations have firm or potential plans to bring AI workloads on-premises within the next 1-3 years.

• Over 70% of respondents rated security and privacy as very important when it comes to the ability to run AI/ML workloads locally.

Stay tuned for Part 2 of our survey insights, where we’ll dive into what data scientists are looking for in terms of collaboration and scalability. Beyond just easy deployment and experiment creation, they’re seeking platforms that foster teamwork, offer seamless integration, and maintain top-notch security—key factors for driving impactful AI/ML development.