Each industrial revolution has ushered in new technology to the market. As we witness its fourth wave, we are seeing important changes across many fields—most notably AI. Artificial intelligence is truly having its moment in the spotlight, evolving from chatbot technology to a foundational tool with widespread implications for businesses across industries.
AI, particularly GenAI, has become a powerful defence tool and a potential risk when it comes to data privacy. On one hand, AI tools give organisations the ability to analyse large volumes of data and identify patterns at an unprecedented rate—a true strategic time saver for enterprises in possession of large quantities of information. On the other hand, this ability to process massive amounts of data can also lead to unintentional and intentional data loss through data leakage and exfiltration.
Considering this double-edged sword, it’s clear the Fourth Industrial Revolution is well and truly here—whether we like it or not—and AI is the key to unlocking innovation today. But with AI-driven threats evolving fast, having AI-driven defence is officially a business imperative.
Keeping up: legislation catching up to innovation
Since ChatGPT’s explosive rise in 2022, countries and governing bodies have been working to create appropriate AI frameworks. These often build on existing data privacy laws, such as GDPR, but there’s a need for more clarity around how AI interacts with data. Countries such as Singapore, India, South Korea, Australia, and the UAE have invested in these programmes, all to ensure that organisations can benefit from innovations in this field whilst consumers are confident and safe to adopt AI.
In this same vein, the European Union released the EU AI Act in mid-2024, creating a ranking system for AI usage which ranks from unacceptable, high and low, or minimal risk. These provide practical guidance for organisations and companies, with the goal of addressing governance and ethical issues when designing and deploying AI solutions. These structures all emphasise accountability and transparency, to find a balance between thriving AI innovation and protecting users’ privacy.
What’s more challenging is that it is difficult for legislation to keep up with innovation. This came to a head in January 2025 when DeepSeek fell afoul of shady data processing practices. The new Chinese-based open-source large language model took users by surprise when they read the fine print and discovered that the website reserved the right to collect their keystroke patterns or rhythms. Open-ended generative AI models like DeepSeek pose unique data privacy issues, especially when you consider that they may preserve your data and can also share it with third parties such as law enforcement agencies.
Amid shifting regulatory landscapes, it’s become imperative for enterprises to be in-tune with the market jurisdictions they operate in—and even those where they do not. To reap the benefits of AI while protecting user data privacy, they’ll need to understand what their obligations are, to which regulators, users and data, where said data is stored and managed, and how it is being used. Sounds like a difficult quest to conquer—but with the right tools and protocols in place, it doesn’t have to be.
Striking the balance: Balancing AI innovation with data privacy
One way to reap the benefits of AI while being mindful of data privacy is to be thoughtful about how it is integrated into a service stack. This can be done by being transparent about how AI is being used and giving users the option to opt out of it. This must be done in a way where refusal to use AI won’t impact existing workflows.
Another great way to balance AI and data privacy is to use one to boost the other. Some businesses might be surprised to learn that AI can amplify data privacy strategies and—when used right—can be a tool for good. The implementation of data security automation can save time, ensure accuracy and free up decision-makers to take a more consistently top-down view and focus on pressing items where needed.
Enterprises can—and should—also use AI to strengthen their cybersecurity arsenal to empower tools that support data discovery, threat detection, access management, phishing detection, event management and security information, and vulnerability scanning. An AI-driven security stack can help security leaders efficiently and accurately discover, classify, and even support remediation where needed—aiding prioritization and corrective actions to protect their most sensitive data. A proper unified, AI-driven security stack can further help enterprises reduce the number of enforcement policies, leading to gains in both operational costs and keeping up with an ever-changing face of compliance.
Catching on: responsible and innovative AI use
There’s a world of opportunity ahead of us when it comes to harnessing the benefits of AI. Approaching AI adoption with care and caution—particularly when it comes to protecting personal and proprietary data—is essential in an evolving digital era.
Making sure that innovative companies adhere to legislation, embrace AI safely, and educate teams appropriately begins with getting both data security and data privacy right. In this way, companies can truly realise the potential of AI while employing the correct data protections—never compromising innovation for data privacy, or vice-versa.
