Looking ahead, differential privacy is expected to see continued evolution and innovation. Key areas of future development include improving the utility-privacy trade-off, developing more efficient and effective noise addition mechanisms, and exploring ways to integrate differential privacy with other emerging technologies like machine learning and artificial intelligence. Research is also likely to focus on making differential privacy more accessible and easier to implement, with efforts to develop standardised tools and frameworks. Additionally, as legal and regulatory landscapes evolve, adapting differential privacy to meet these changing requirements will be an important area of focus.