The Latest Advancements in Personal Security and Digital Privacy
According to Gartner, by year-end 2024, predicts that 75% of the world’s population will have their personal data covered under modern privacy regulations. This evolution has been the main driver behind privacy becoming operational.
The coming years will bring many new privacy laws and it is already being talked about. This direction from the point of view of legal regulation will become more stringent. Gartner predicts that by 2024, large organizations’ average annual budget for privacy will exceed $2.5 million.
What is the future of digital privacy?
#1 AI governance
According to a survey conducted by Gartner, around 40% of organizations experienced an AI privacy breach. Surprisingly, only one in four of these breaches was actually intentional. Whether personal data is processed through an AI-based module integrated into a vendor offering or a separate platform managed by an in-house data science team, the risks to privacy and potential misuse of personal data are evident. “Most of the AI utilized by organizations today is integrated into larger solutions, often lacking proper oversight to assess its impact on privacy. These embedded AI capabilities are employed to monitor employee behavior, evaluate consumer sentiment, and develop “smart” products that continuously learn. Additionally, the data fed into these learning models at present will significantly influence future decision-making,” stated Henein. “Once AI regulation becomes more established, undoing any harmful data ingested in the absence of an AI governance program will be nearly impossible. IT leaders will end up having to completely replace whole systems, incurring substantial costs and risks to their organizations.”
#2 Remoteness in everything
Engagement models in work and life are now transitioning into hybrid, which has led to an increased need for tracking, monitoring, and processing personal data. As a result, privacy concerns have become even more crucial. This all-hybrid way of interacting has also brought about improvements in productivity and work-life balance satisfaction across different industries and fields. To address these privacy implications, organizations should prioritize a human-centric approach. Data monitoring should be minimized, while purpose and clear objectives should guide its use. For instance, it can be used to enhance employee experience by reducing unnecessary obstacles or identifying well-being risks to prevent burnout.
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#3 Data localization
In a world without borders, it may seem counterintuitive to have control over where data resides. However, with emerging privacy laws, this control becomes a necessity. Multinational businesses face risks with their current strategies, leading to a new approach in cloud design and acquisition. Security and risk management leaders navigate through varied regulatory landscapes, requiring different strategies for data localization. Consequently, prioritizing data localization planning becomes crucial in cloud service design and acquisition.
#4 Centralized Privacy UX
Due to the growing demand from consumers for privacy rights and increased expectations around transparency, there will be a need for a centralized privacy user experience (UX). Forward-thinking organizations have recognized the benefits of creating a self-service portal that combines all aspects of the privacy UX, such as notices, cookies, consent management, and subject rights requests (SRR) handling. This approach offers convenience for customers and employees, resulting in significant time and cost savings. Around 30% of consumer-facing organizations are expected to provide a self-service portal for preference and consent management.
#5 Privacy-Enhancing Computation Techniques
Data processing in untrusted environments, such as the public cloud, and multiparty data sharing and analytics have become critical for the success of organizations. Rather than applying a separate approach, the increasing complexity of analytics engines and architectures requires vendors to incorporate privacy capabilities from the start. The proliferation of AI models and the need to train them only deepen concerns about privacy. Unlike typical data-at-rest security controls, privacy-enhancing computation (PEC) safeguards data while it is being used. Consequently, organizations can now implement data processing and analytics that were previously hindered by privacy or security concerns. According to Gartner, by 2025, 60% of large organizations will utilize at least one PEC technique in analytics, business intelligence, and/or cloud computing.
Conclusion
The protection of personal data is important and its value will continue to be recognized by both companies and individuals. For this reason, the business must provide all necessary measures to protect privacy, and the users must do the rest. The worst thing you can do for yourself is to shelve the issue.
