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Introduction

In the first of a two-part report series, we examine the complex forces impacting data privacy. It is only by understanding these forces that we can formulate the optimum privacy strategies and best practices.

Highlights

  • The prevailing approach to leveraging data insights is the equivalent of fracking. This is an intrusive process operating in the margins of regulation and consumer acceptance to maximize the volume and variety of data sets and the speed of extraction.
  • Powerful consumer tech firms such as Facebook and Google are so adept at data collection at scale that they have become data super platforms. These players are also AI hyper-scalers, and the data imperatives that drive them makes privacy vulnerable.
  • AI can generate increasingly broad and deep data sets, at scale and speed. AI machine learning (ML) models can detect hitherto unforeseen patterns and connections, and make increasingly accurate predictions. This introduces new complexity and challenges for data privacy.

Features and Benefits

  • Understand how, from where, and why data insights are proliferating and what this means for consumer data privacy.
  • Understand how AI is impacting consumer data privacy today and in the future, and what this means for privacy.
  • Learn why the prevailing "data fracking" approach to data extraction must change – and how this needs to happen.
  • Get to grips with principles behind the General Data Protection Regulation – and how this sits alongside AI developments.
  • Learn about consumer attitudes to data privacy – and how they are responding to the issues.

Key questions answered

  • What impact are the big consumer tech and OTT players like Google and Facebook having on consumer data privacy?
  • Where is the data explosion coming from – how are data insights changing and how does AI affect this?
  • How is AI impacting data privacy – where are the pain points and risks?
  • Are there ways that AI can benefits data privacy?
  • What are consumer attitudes to data privacy – who do they trust most, what worries them, and how are they reacting?

Table of contents

Summary

  • In brief
  • Ovum view
  • Recommendations for consumer service providers

The consumer data explosion

  • The "datafication" of everything
  • Data is growing exponentially
  • The pivotal role of mobile
  • The IoT data floodgates are open
  • AI's impact on consumer services and devices is proliferating

AI brings new complexity to data privacy

  • New AI-powered scenarios and data insights beckon
  • But AI can be a force for good in the data privacy domain

The consumer view: concern and uncertainty

  • Attitudes and actions are not as contrary as they may seem
  • AI is adding a new dimension to consumer disquiet
  • Change is in the air: service providers beware

Privacy is caught in the digital economy crosshairs

  • Data privacy in the digital economy needs to be rebalanced
  • Data super platforms and AI hyper-scalers pile on the pressure

Data privacy legal regimes are a work in progress

  • GDPR is a solid reference point and framework for debate
  • GDPR and similar should be viewed as the start, not the finish
  • AI brings fresh challenges for data privacy regulations
  • Linking data dominance and data privacy to competition

Appendix

  • Methodology
  • Further reading
  • Author

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