When Gartner unveiled its top eight cybersecurity predictions for 2024, most data security and privacy experts weren’t surprised to see generative AI (GenAI) adoption as a leading trend. The advanced technology is expected to help solve several data security challenges, including closing the cybersecurity skills gap and reducing human-driven data security breaches.
The world of data security is undergoing a remarkable transformation in 2024, driven in large part by AI’s rapid advancements. In this blog, we explore the key trends shaping the future of data security, including:
- Its growing reliance on AI.
- New regulatory challenges.
- The transition from data security posture management (DSPM) to data security platforms (DSPs).
- The consolidation in the cloud security space.
- Supply chain security.
- The rise of advanced privacy-preserving technologies.
As organizations continue to pivot toward digital transformation and AI integration, they’ll require future-ready strategies capable of evolving with emerging threats. Below are the six trends we believe will define 2024 for data security professionals, helping them navigate complex security challenges and ensure lasting resilience.
6 Leading Trends in Data Security & The Role AI Will Play
While AI brings numerous opportunities for enhanced security measures, it also introduces new challenges and risks that industries across the board must grapple with. For instance, the healthcare sector has the complex and often overwhelming task of protecting sensitive patient data against increasingly sophisticated AI-driven cyber threats. The finance industry must secure vast amounts of customer data while adapting to AI-powered fraud detection systems.
With these and other emerging threats fundamentally altering the data security landscape, organizations are obliged to invest in advanced technologies like AI, machine learning, and blockchain to fortify their defenses, retain consumer trust, and remain regulatory compliant. The dynamic interplay between AI and data security is helping businesses balance the technology’s potential while mitigating its risks.
1. AI’s Relationship to Data Security
One of the most significant data security trends is the increasingly synergistic relationship between AI and security. On the one hand, enterprises are using AI as a powerful tool to enhance security measures; on the other, as AI systems become more common and sophisticated, the need for robust security becomes paramount:
- AI-Powered Threat Detection and Response. AI-based algorithms are being used to analyze vast amounts of data, quickly identify patterns, and detect potential security threats in real time, allowing businesses to respond to cyber attacks more rapidly and effectively.
- Automated Security Tasks. AI excels at automating repetitive security tasks such as vulnerability scanning, patch management, and user access review. This frees security teams to focus on more strategic initiatives.
- Secured AI Systems. As AI systems become more ubiquitous, ensuring their security and resilience is critical. The development of advanced techniques like adversarial machine learning and trusted AI frameworks can protect AI models from attacks and ensure their integrity.
2. Latest AI Regulation Challenges
Rapid advancements in AI have led to a growing need for comprehensive regulation to address the ethical, privacy, and security concerns associated with the technology. A current surge in new AI regulations is posing unique challenges for organizations.
- Compliance with AI Regulations. Organizations must navigate a complex web of regulations, including the proposed EU AI Act and an increasing number of national AI strategies, to ensure their AI systems and practices are compliant.
- Balancing Innovation and Regulation. Striking a balance between fostering innovation and implementing robust regulatory frameworks is an intricate task, as organizations are required to adapt their AI development and deployment processes to meet the new regulatory requirements.
- Interpretability and Explainability. As regulators increasingly demand that AI systems be transparent and their decision-making processes be interpretable, organizations developing complex AI models find the process more and more challenging.
3. Transitioning From DSPM to Data Security Platforms
The focus in the data security landscape has, in recent years, shifted from traditional DSPM approaches to comprehensive, AI-driven DSPs, driven by the need for a more holistic and integrated approach to data protection. For example, AI-powered DSPs are being adopted by the finance sector to provide a unified view of data security through combined capabilities like data discovery, classification, access control, and breach detection. By using machine learning to continuously monitor and adapt to changing security risks, financial institutions can stay ahead of emerging threats and protect sensitive customer data.
- Integrated Data Security and Privacy Management. AI-powered DSPs combine various capabilities, such as data discovery, classification, access control, and breach detection, into a single, cohesive solution, providing organizations with a unified view of their data security posture.
- Expanded Scope Beyond DSPM. While DSPM has typically focused on protecting sensitive data, AI-driven DSPs encompass a broader range of functionalities, including threat detection, incident response, and cloud-based data governance.
- Adaptive and Responsive Approach. AI-powered data security platforms use machine learning to continuously monitor and adapt to changing data security risks, ensuring businesses can stay ahead of emerging threats.
4. Increased Cloud Security Consolidation
Cloud security trends are also evolving, with increased consolidation among cloud security vendors and the emergence of more comprehensive, AI-powered cloud security platforms.
- Mergers and Acquisitions. As the cloud security market matures, we’re experiencing a wave of mergers and acquisitions, with more prominent players seeking to expand their offerings and provide more integrated, AI-powered solutions to their customers.
- Rise of Comprehensive Cloud Security Platforms. In response to the cloud environment’s growing complexity, cloud security vendors are developing platforms that combine multiple security capabilities, such as cloud infrastructure security, application security, and data protection, into a single, unified solution, leveraging AI to enhance their abilities.
- Increased Focus on Cloud Security Orchestration and Automation. Cloud security platforms are incorporating advanced AI-powered management and automation capabilities that make it easier for organizations to streamline security operations and respond to threats more efficiently.
5. Supply Chain Security
An increasing reliance on global supply chains has brought heightened attention to the security of these interconnected systems. In 2024, AI-powered supply chain security is emerging as a critical data security focus area.
- Vendor Risk Management. Enterprises are implementing AI-driven vendor risk management practices to assess their suppliers’ security posture and ensure the security of their entire supply chain.
- Software Supply Chain Security. As attackers increasingly target third-party software vulnerabilities, the security of software components and the software development life cycle is becoming another crucial concern. AI can enhance the detection and mitigation of these threats.
- Blockchain-Based Supply Chain Traceability. Companies are using emerging technologies like blockchain in conjunction with AI to enhance supply chain transparency and traceability, enabling them to better identify and mitigate security risks.
6. AI-Powered Privacy-Preserving Technologies
In response to escalating data privacy concerns, organizations are turning to cutting-edge technologies to safeguard sensitive information while still unlocking valuable insights. For instance, healthcare providers can use AI-powered privacy-preserving tools to analyze patient data and improve treatment outcomes without compromising individual privacy. This approach enhances data security while ensuring providers can continue to innovate and make informed decisions based on their data.
- Differential Privacy. Techniques that leverage AI, such as differential privacy, are being adopted to allow for the release of sensitive data while providing strong mathematical guarantees of individual privacy.
- Homomorphic Encryption. AI-enhanced homomorphic encryption allows organizations to process encrypted data without the need to decrypt it, enabling secure data analysis and collaboration.
- Federated Learning. This AI-driven approach enables the training of machine learning models on distributed data sources, minimizing the need to share raw data and enhancing privacy.
A Promising Future That’s Not Without Challenges
Data security’s future is continually being shaped by multiple factors, including:
- The dynamic interplay between AI and regulatory changes.
- The evolution of AI-driven data security platforms.
- The AI-powered consolidation of the cloud security space.
- A focus on AI-powered supply chain security.
- The rise of advanced privacy-preserving technologies enabled by AI.
As organizations strive to navigate this rapidly changing landscape, strategic integration of AI will be vital in safeguarding their data and maintaining a competitive edge in 2024 and beyond. The future of data security is clearly intertwined with AI advancements, and organizations that embrace this synergy will be better equipped to tackle the evolving security challenges in the years to come.
While 2023 ushered in many new data security concerns, 2024 is poised to introduce AI-driven technologies and solutions that will transform how businesses protect their sensitive data. Powered by AI, Velotix was designed to help organizations prepare for the unknowns in data security. Its future-proof data security standards can help ensure you’re ready to meet escalating cyber threats and heightened privacy concerns head-on, automating policy management and supporting innovation and growth. It’s the only DSP that allows organizations to become truly data-driven, simplifying data security, streamlining data access to the right people in record time, and making it easier than ever to anticipate and prepare for the future.
Contact Velotix today to learn more or to schedule a demo.
