AI and Data Privacy in Business
Aaryan Gupta, Mansi Amarnani, Surendra Soanki, Jaydeep Kishore · 2025
This review paper discusses AI innovation and data privacy imperatives in modern business applications converging. Now, with AI taking over the role of process optimization and even customer personalization, organizations that rely on this data will be more sensitive to issues related to privacy starting from data security down through potential biases introduced in models which makes it crucial for them remaining compliant. Here we review privacy-focused principles such as the pillars of Privacy-by-Design, Data Governance and Transparency that are necessary to mitigate the risks posed by AI with respect to individual or societal information. Second, it analyzes the global regulatory environments driving AI implementation and underscores that data integrity in combination with accountability are ethical imperatives when deploying AI. Fulfilling these privacy challenges can also foster trust with consumers and lead to more responsible AI usage in the longer term. This paper presents a comprehensive examination of what it will take to build an accountable AI culture, to align the next wave of technical progress with privacy ethics and responsible innovation, and for organizations so that they understand how both can be compatible truthfully.