Digital privacy around the world is becoming increasingly important and long-term regulatory, leaving companies to prepare for legal demands — with consultancy Gartner predicting that the average annual budget of large companies for data privacy will exceed US$ 2, 5 million (almost R$ 12 million at current rate) by 2024, mainly due to adjustments and implementations of technological trends related to the sector.
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For Gartner, in the future of this area, companies will have to focus on five specific trends: data localization systems; privacy-enhanced computing (PEC) techniques; resources for Artificial Intelligence Governance; privacy-centric user experience (UX) models; and control policies for hybrid work. We detail them below:
data localization
Risks to a multi-country business strategy drive a new approach to designing and delivering cloud solutions across service models as security and risk management leaders will face an uneven regulatory landscape with different regions requiring different security strategies. location – resulting in a greater importance of location planning data, which will become a top priority in the design and procurement of cloud services.
Privacy Enhanced Computing (PEC) technical trends
Processing data in untrusted environments, such as the public cloud, and sharing and analyzing data between parties have become critical to an organization's success. Rather than taking a pervasive approach, the increasing complexity of data analytics engines and architectures requires vendors to incorporate a privacy-by-design feature. The spread of AI models and the need to train them is just the latest addition to privacy concerns.
Unlike common security controls for unused data, Privacy Enhancement Computing (PEC) protects data in use. As a result, organizations can implement data processing and reviews that were previously impossible due to privacy or security concerns – with Gartner predicting that by 2025, 60% of large organizations will use at least one PEC technique in analytics, business intelligence and /or Cloud Computing.
Artificial Intelligence Governance
Companies, in the next two years, must know how to apply AI governance to data security. (Image: Reproduction/Gerd Altmann/Pixabay)
Gartner research found that 40% of organizations had an AI privacy breach, and of those breaches, only one in four was malicious. Whether organizations process personal data through an AI-based module integrated into a vendor offering or through a discrete platform managed by an in-house data science team, the privacy risks and potential misuse of personal data are clear. .
“Once AI regulation becomes more established, it will be nearly impossible to unravel the toxic data ingested in the absence of an AI governance program. IT leaders will have to eliminate systems wholesale, at great cost to their organizations and jobs,” said Nader Henein, vice president and analyst at Gartner.
Privacy-centric user experience
Growing consumer demand for subject rights and rising expectations about transparency will drive the need for a privacy-centric user experience (UX) that brings together topics such as notices, cookies, consent management, and handling privacy rights requests. (SRR) in a single self-service portal.
This approach provides convenience for key constituents, customers and employees, and generates considerable time and cost savings. By 2023, Gartner predicts that 30% of consumer-facing organizations will offer a self-service transparency portal to provide preference and consent management.
Hybrid models will be even more common
With increasingly hybrid work-life engagement models, both the opportunity and desire to increase tracking, monitoring and other personal data processing activities increase, and privacy risk becomes paramount. With the privacy implications of a fully hybrid set of interactions, productivity and satisfaction with work-life balance have also increased across industries and disciplines.
In this context, organizations must adopt a human-centered approach to privacy, and monitoring data must be used minimally and for a clear purpose, such as improving the employee experience, removing unnecessary friction, or mitigating the risk of burnout. , signaling welfare risks.
