The surge in generative AI has moved beyond simple curiosity, becoming a fundamental driver of strategy for consumers, businesses and investors alike. Organizations are increasingly relying on artificial intelligence, AI technologies and AI systems to speed up workflows, automate decisions and eliminate repetitive tasks.
Businesses and consumers are now leveraging large language models (LLMs) such as ChatGPT, Gemini and Claude to support a growing range of use cases, from customer support to content creation and analytics. In the midst of this rapid adoption of machine learning and deep learning, new anxieties around data protection, information privacy and AI-driven data collection continue to gain momentum.
To keep up, organizations need to understand where data privacy is breaking down and how best to prevent or manage emerging privacy risks. Learn how to safeguard personal data as AI increasingly changes how we work, live and understand ourselves.
The Upsides and Downsides of the Rise of AI
As more people use generative AI and the technology itself continues to develop, risk managers will face both new opportunities and emerging challenges. Understanding the complex relationship between artificial intelligence and data privacy is now essential for effective data governance.
How AI Benefits Data Management
AI tools can not only streamline business operations but also help you gather more and higher-quality data. When aligned with a strong data governance strategy and a clear regulatory framework, AI can enhance both efficiency and compliance.
Here’s how data managers can make the most of AI:
- Data volume is growing: As the adoption of AI grows, these systems are amassing exponential volumes of personal data from their users. Even if you don’t directly offer AI-supported services, you’ll need to account for the fact that corporate, governmental and other actors may have access to increasing amounts of specific data regarding your users.
- Data is diversifying: AI systems aren’t just gathering more data; they’re also collecting more and more personal types of data, such as biometric information like fingerprints and facial recognition.
- Personalization is more achievable: According to a 2025 Qualtrics study, 64% of consumers want companies to use data such as purchase history and site visits to create personalized experiences. Thanks to the data being gathered by AI, personalization is increasingly achievable on multiple levels.
- Navigate complex regulations: AI tools can work with your organization’s legal counsel to simplify the process of understanding and complying with the industry-specific patchwork of data privacy laws and regulations.
How AI Adds Risk to Data Management and Data Protection
On the other hand, increased AI implementation has created new perceived and actual threats to data privacy and data protection:
- More data means more complexity: As AI systems gather more and more diversified personal data, companies and organizations are expected to manage this data both effectively and responsibly.
- Balancing personalization and privacy: While AI makes more types of personal information more accessible, your organization will need to balance consumer expectations of personalization against their desire for privacy. According to the Qualtrics study, only 33% of respondents reported mostly or totally trusting companies with their data.
- Data breaches are riskier than ever: The data gathered by AI doesn’t just present opportunities for companies and consumers. It also provides a tantalizing target for cybercriminals and other bad actors. According to a Pew Research poll conducted in 2025, 71% of U.S. adults reported feeling concerned about their personal information being misused by AI.
The Biggest Data Challenges of the Age of AI
Clearly, the rise of AI is complicating the jobs of information security officers and risk managers. The largest privacy risk factors raised by this technology occur across industries in companies of all sizes.
Organizations Are Divided on the Risks of AI Adoption
It’s impossible to effectively safeguard your customers’ information without buy-in from the highest levels of your organization. But the latest Proofpoint report demonstrates that alignment between boards and chief information security officers (CISOs) has decreased from 84% in 2024 to just 64% in 2025.
This data shows that in addition to the many challenges posed by AI technology itself, you may also face internal resistance to meaningful efforts to address those risks.
Greater Distribution of Data Means Multiplied Risk
As AI tools become more integrated into every type of organization, the end result is often that single CISOs will be tasked with managing personal data across a variety of tools, platforms and environments. According to a 2025 study by MIND, most senior cybersecurity leaders acknowledge that sensitive data is housed across various types of storage, including cloud-based services and on-premises locations.
Of course, multiple data locations create multiple opportunities for catastrophic breaches.
A significant gap divides how customers and employees perceive AI
The rising adoption of AI has brought up a variety of concerns for the average consumer. Your customers are likely aware of AI tools that have mismanaged user data or even violated data privacy laws, such as the Clearview AI lawsuit that resulted in a $51.75 million settlement.
Understandably, events like these leave many consumers opposed to their personal information being used as training data for AI programs. On the other hand, employees of your organization are likely to see AI as a time-saving opportunity rather than a privacy risk.
Read: Data Privacy: A Comprehensive Guide
Why You Should Invest in Your Data Privacy
With AI bringing up so many potential risks, most risk managers understand the importance of investing in their organization’s data security. That said, you’ll likely still need to convince relevant stakeholders like investors or company leaders in order to get the resources and support you’ll need to effectively protect your data.
Luckily, you won’t need to rely on the projected costs of an imagined data breach to sway privacy decision-making at your organization. According to a 2025 Cisco survey, a majority of security and privacy professionals reported a 1-2x return on their investments in data privacy, with 29% seeing ROI anywhere from double to quintuple (2x-5x) their initial investment.
Where does all of this revenue come from? First, you’ll save money that the company otherwise might have spent addressing security breaches. Less obvious are the benefits you’ll reap from increased consumer trust, translating into improved customer retention and loyalty.
Read: Top 5 Objections to Data Privacy Management Software
The Problem With Most Data Privacy Tools
It can compound problems to try to handle your organization’s data privacy concerns with a never-ending parade of standalone tools. Instead of solving security risks, such tools tend to introduce delays by segmenting data rather than facilitating access and communication across teams.
Another issue with implementing standalone tools to address individual security challenges is that doing so inevitably creates blind spots in your organization’s risk assessment efforts. Only a platform that enables an enterprise-wide view of the current state of your data privacy can empower you to predict and address data incidents before they happen, instead of merely reacting to problems as they come up.
Furthermore, our full suite of governance, risk and compliance tools puts data privacy in context of your organization’s overall risk.
Protect Your Business and Consumers With Data Privacy Management
The rise of AI is presenting an encouraging array of benefits but a daunting set of new challenges for anyone responsible for gathering and protecting sensitive data. While the use of AI by both consumers and companies can introduce risk, the bottom line is that you’ll need to adapt to artificial intelligence, not fight it, to safeguard your customers’ data, strengthen data protection and protect your organization’s revenue.
You can learn more about the risks and opportunities posed by AI in the Onspring eBook Data Privacy in the Age of AI. Download the eBook now.
