Keep Up with 2024’s Top Data Privacy Trends with OpenPages Data Privacy Management
Did you know last year, there were about 4,100+ data breaches, accounting for 22 billion publicly exposed records? Another research predicts that by the end of 2023, the global cost of cybersecurity would reach $10.5 trillion!
It is evident that cybersecurity and privacy trends go hand in hand with technological innovations. At the dawn of the GenAI era, leaders, consumers, regulators, and governments are becoming acutely concerned about data privacy and protection practices. As we come closer to 2024, it is highly likely that data privacy and security will remain a true competitive differentiator for brands and businesses that value customers’ trust and loyalty. With IBM OpenPages Data Privacy Management, firms can understand how personal data is used across the value chain and automate private data reporting for better accuracy and audits to accelerate initiatives tied to their governance, risks, and compliance (GRC) objectives.
But, first, let us level up our understanding of data privacy challenges and privacy trends in 2024 that every CISO and data privacy leader wants us to know.
Data Privacy is a Fundamental Psychological Need!
Managing data privacy in a digital era requires an approach beyond the theoretical lens of deploying data management platforms and systems with force-fitted security policies. Today, data is collected at a nano-level to power AI advancements and data mining algorithms that help organizations gain deeper consumer insights to enhance personalization.
An extensive series of research on digital privacy states that it is not a unidimensional concept. Digital privacy is a fundamental psychological need that can have an economic impact and can be treated as a technology artifact. The concern for information privacy includes an individual’s concern about organizations’ privacy practices like collection of personally identifiable information (PII), unauthorized secondary use of PII, improper access, and errors.
Recently, consumers have increasingly become aware of high-profile data breaches and leaks from phishing, malware, and cyber security attacks. Data from Cisco 2023 Data Privacy Benchmark study finds that 94% of organizations said their customers wouldn’t buy from them if there was no proper data protection. Also, 81% of consumers perceive that the way an organization treats its data is a direct indication of how they view and respect customers, according to reveals 2022 Cisco survey. With the ongoing wave of rapid GenAI adoption, organizations need to implement a ‘privacy by design’ approach. To foster trust-based relationships with their customers, businesses are actively striving to move into the future without relying on the third-party data captured by cookies. Additionally, the legal components enforced by General Data Protection Regulation (GDPR) in the Europe and California Consumer Privacy Act (CCPA) in the U.S. are strong indicators of worldwide data protection momentum.
By the end of 2025, one-third of the global population would take active personal data protection measures like encryption, multifactor authentication, masking and erasure, along with data resilience. We believe that organizations must broaden their awareness about the evolving landscape of data privacy and five trends to proactively implement befitting measures to meet their GRC requirements.
Five Data Privacy Trends to Watch Out in 2024
- Data Localization:
Scientists predict that by 2025, there will be about 463 exabytes of new data every day. That is equivalent to making a video call and letting it run for the next 110 million years! Data produced in the cloud computing age has garnered concerns of regulators, privacy advocates, and consumers about its storage and access. It has resulted in the development of many data localization laws. As of 2021, there were about 144 data localization controls in place. According to McKinsey’s data, 75% of all countries would have implemented some form of data localization rules. This is a byproduct of emerging privacy laws that attempt to standardize uneven regulations with respect to the data residing in multi-country cloud across all service models. It prevents companies from using or transferring customer data for their own interest without permission from the government and customers.
To restore digital privacy and trust among customers as the custodians of their data, companies need to understand data localization requirements fragmented across geographies. They need to design and plan decentralized security models, infrastructure, resources, governance, and documentation that comply with local laws and requirements. It also includes prioritizing the design and acquisition of cloud services for data sovereignty.
- Privacy-enhancing Computation Techniques:
Privacy-enhancing computation techniques like homomorphic encryption, secure multi-party computation (SMC), zero-knowledge password proof, and differential privacy help multi-party users to perform data calculation tasks without revealing the exact information. The complexities of data architectures or analytics engines supporting public cloud, AI models, and multi-party data sharing and analyses require higher privacy standards to protect personal and sensitive data. Unlike the data-at-rest security control, privacy-enhancing computation shields data-in-use. This would benefit organizations to implement and use data processing and analytics without worrying about privacy or security concerns.
Although the implementation of privacy-enhancing computation techniques won’t be a cakewalk, distributed computing and blockchain’s decentralized architecture and personal data privacy mechanisms will provide an innovative angle to support complex privacy-related challenges. Gartner’s prediction suggests that by 2025, 60% of large companies will use at least one form of PEC technique in analytics, business intelligence, and/or cloud computing.
- AI Governance:
Another hot trend on the radar for 2024 is AI governance. As AI-powered platforms and systems continue to revolutionize businesses, stakeholders are veering towards the ethics behind the AI models and framework to foster an equitable and accountable AI workflow and safeguard against cybersecurity breaches and risks. Recently, malicious cybersecurity attacks like ransomware are growing in sophistication and complexity as bad actors take the AI-powered route to perpetrate attacks. According to Gartner, almost 40% of companies experienced AI-led privacy breaches and one in four of those breaches were malicious. Also, the cost of data breaches in 2023 reached a record high of $4.45 million, finds the IBM’s cost of data breach report!
AI governance and data privacy concur as most of the AI-driven platforms amass high volumes of user data for analysis and actionable insights. The common use cases of embedded AI functions include ingesting and mining data that reveal employee behavior, consumer sentiments, psychographic data, and more. Learning models and algorithms influencing AI-enabled decisions and activities also need thorough regulation and governance to help enterprises building those AI systems to justify and explain those models with utmost accuracy and transparency. Global governments and regulators are working towards establishing stringent AI governance laws to enforce compliance across AI development, deployment, and overall workflow. Efforts are underway and enterprises can expect policies for AI governance in 2024.
- Centralized Privacy User Experience (UX):
Almost 30% of customer-facing businesses by 2023 were predicted to include a self-service transparency portal on their digital platforms for users’ privacy preference and consent management. Consumer awareness about data privacy rights and expectations for high data protection standards from enterprises is pushing the need for privacy-aware design framework or privacy UX. It involves building ethical and respectful user interfaces as a part of data collection, processing, storage, and usage processes. It means organizations will take a collective, ethical initiative to include user content, notices, cookies, and subject rights request (SSR) handling under one self-service portal to help users consciously choose how they allow a business to deal with their information online. Centralized privacy UX is integral to building customer trust and simplifying online users’ journey and experience in navigating the key constituents of privacy-related permission and consent options, enabling better time and cost efficiencies.
- Remote to Hybrid Engagement Model:
Evolving work trends and norms in 2023 push leaders and talent resources managers to implement a human-centric work design for a productive workforce. The shift from remote to hybrid everything dictates data privacy and protection practices of organizations. Various businesses across industry verticals are observing the privacy implications of hybrid-led interactions, work collaborations, and data exchanges while requires a human-centered approach to make end-user processes less complicated and riddled with the risk of burnouts and unnecessary operational overkill.
IBM OpenPages Data Privacy Management: Built for Data Visibility and Monitoring
Fending off data privacy-related risks isn’t just about implementing a couple of data protection measures. The need for stronger data privacy is a global attitude. IBM OpenPages Data Privacy Management module is built to empower enterprises to stay abreast of the latest data privacy trends and to take proactive approaches towards their GRC requirements. The fully integrated, enterprise risk platform offers complete visibility into a company’s risk position and improves data access to establish a predictive approach to GRC. The advanced AI capability powered by natural language processing (NLP) enables data categorization and mapping suggestions to the users, helping them attain higher data accuracy in risk reporting and reduced reporting time. IBM Design Thinking Principles embedded in the OpenPages platform provides users with dynamic dashboard capabilities with custom visualizations, task tabs, widgets, and landing pages unique to the user profiles.
The Data Privacy Management module within the OpenPages platform helps data leaders confidently tackle data privacy concerns by gaining a holistic view of sensitive data, its usage, source, user entities, and purpose. To assist privacy assessments and reporting, OpenPages has integration with the cloud-based, data catalog and governance platform, IBM Watson Knowledge Catalog to load metadata. Both these platforms work cohesively to run discovery and usage scans to detect sensitive and private data.
Here are some of the core features of OpenPages Data Privacy Management:
Real-time Private Data View: Users can leverage the data privacy management module of OpenPages to create an inventory of sensitive and private data across the organization and integrate it with IBM Watson Knowledge Catalog to maintain an updated record of data assets that involve the use of private data.
Privacy Assessments: The module’s questionnaire assessment feature helps users create and implement privacy assessments wherever fit in their organization.
Automated Workflow Management: This feature enables privacy assessment process automation for data assets and applications or systems that make use of personal data.
Data Compliance and Audit: Consolidate and maintain records of privacy assessment on data assets for compliance and audit.
Issue management: Take a proactive measure to manage issues based on privacy assessment results that can be created, logged and assigned to the appropriate stakeholder and tagged to appropriate risks and controls.
Get to Know Us!
Robust data privacy and governance within an organization largely depend on the technology, best practices, and platforms. Understanding our commitment to data privacy and OpenPages’ highly secure data architecture can be a game-changer to most companies trying to minimize privacy-related complexities and apply industry-specific regulatory policies and rules to their data assets, leveraging the platform’s myriad of capabilities.