The future prospects of differential privacy are promising, as the need for robust privacy-preserving data analysis continues to grow. With increasing awareness and regulatory requirements for data privacy, differential privacy is likely to become a standard practice in data analysis, especially in sectors handling sensitive information. As technology evolves, we can expect more advanced and user-friendly differential privacy tools, making it accessible to a wider range of users. Additionally, ongoing research in the field is likely to address current limitations, such as the accuracy-privacy trade-off, making differential privacy even more effective and versatile. The application of differential privacy is also expected to expand beyond traditional sectors, contributing to innovative solutions in areas like smart cities, IoT, and personalised services, all while safeguarding individual privacy.