On the Challenges of Deploying Privacy-Preserving Synthetic Data in the Enterprise

Generative AI technologies are gaining unprecedented popularity, causing a mix of excitement and apprehension through their remarkable capabilities.In this paper, we study the challenges associated with deploying synthetic data, a subfield of Generative AI.Our focus centers on enterprise deployment, with an emphasis on privacy concerns caused by the vast amount of personal and highly sensitive data.We identify 40+ challenges and systematize them into five main groups -- i) generation, ii) infrastructure \& architecture, iii) governance, iv) compliance \& regulation, and v) adoption.Additionally, we discuss a strategic and systematic approach that enterprises can employ to effectively address the challenges and achieve their goals by establishing trust in the implemented solutions.