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Privacera Unveils AI and Data Security Governance Predictions for 2024

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Privacera anticipates that policy automation and inference will become the cornerstone of efficient security control, which will allow organizations to respond to emerging threats and vulnerabilities in real-time proactively.

Privacera, the AI and data security governance company founded by the creators of Apache Range, is revealing its trends and predictions for AI and data security governance for 2024. We are witnessing an extraordinary transformation driven by generative AI across various facets of business operations and industries. Privacera anticipates that this transformative impact will continue to deepen, compelling organizations to reevaluate their data security and governance strategies to align with this evolving landscape. These emerging trends and predictions are poised to shape the landscape of AI and data security governance.

Privacera’s 2024 AI and data security governance trends and predictions include: 

Safeguarding Sensitive Generative AI Data Will Become The Default

As generative AI continues to evolve at breaking speeds, in 2024, we expect more organizations will begin to use sensitive data to train their AI models and Large Language Models (LLMs) to harness the true value of generative AI. The presence of this sensitive data in models and embeddings will create serious risks of sensitive data leakage. Privacera advises organizations to adapt their data security governance frameworks to accommodate these additional use cases, emphasizing the need for a proactive approach and continuous fine-grained policy-based security enforcement.

“In 2024, we expect a large influx of innovations by enterprises of every scale adopting and deploying generative AI, and using sensitive data to train the underlying AI and Large Language models,” says Balaji Ganesan, co-founder and CEO, Privacera. “This transformation can only be successful with a unified data security governance strategy in place, and requires data leaders to apply controls to both, sensitive data and AI, in a consistent and scalable manner.”

Convergence of a Unified Data Security & Governance Strategy

With many organizations utilizing numerous data platforms for different use cases, a unified approach to data security governance is more important than ever. Adopting a unified approach ensures that security and governance controls are consistently applied across the entire heterogeneous data estate – from structured to fully unstructured data, regardless of the organization’s size. It allows organizations to address ever-changing compliance and security requirements by discovering sensitive data, deploying and enforcing robust data policies, and providing the necessary access transparency at scale.

“Data governance and provenance are perhaps the central issue that will determine the pace of deployment of AI applications in the Enterprise,” says Praveen Akkiraju, Managing Director at Insight Partners. “The need to safeguard proprietary data and comply with the myriad regulations under consideration will require a platform like Privacera to de-risk the adoption of AI.”

Intelligent Data Security Platforms Will Simplify and Automate the Administration of Security and Governance Controls

It’s clear that Data Security Platforms (DSPs) are on a trajectory to extend their influence into the evolving landscape of generative AI applications and LLMs. We want to emphasize that the fusion of DSP with AI technologies is not only inevitable but also essential for unlocking the full potential of generative AI.

Privacera anticipates that policy automation and inference will become the cornerstone of efficient security control, which will allow organizations to proactively respond to emerging threats and vulnerabilities in real-time. Self-service capabilities will empower teams to manage security and governance with precision and prudence; allowing everyone in a data-driven organization to formulate required policies in natural language.

Persistent Growth of Multi-Cloud Adoption and Large Scale Data Governance Platforms

Building upon our predictions from last year, we highlighted the surge in multi-cloud adoption and the importance of business leaders increasingly adopting a “best of breed” strategic approach, leveraging various cloud partners and services to address their specific use cases.

While consolidation is expected to continue, the fact that no single cloud vendor can do it all will continue to lead to the robust growth of an ecosystem approach to data intelligence and data security governance that spans the entire data estate. Incorporating data security platforms into multi-cloud strategies is vital to tackling the complexities that come with managing data and AI models across multiple clouds. Privacera acknowledges the need for scalable solutions to build modern applications, empower self-service analytics, and enable collaboration across cloud boundaries while ensuring consistent data security and governance at the same time.

“As we head into 2024, enterprises will continue to deploy solutions using services from different cloud service providers,” says Eric Wolford, Partner at Accel. “For those seeking to leverage the power of generative AI, comprehensive data security and governance, including solutions like Privacera, should be included in that strategy to address privacy, regulations, and security challenges. Same will hold true for the underlying data stored with the continued proliferation of large data platforms, such as AWS, Snowflake, Databricks, and cloud-native solutions.”

Global Momentum in AI Regulation & Data Residency

The spotlight on privacy, data security, and compliance concerns is set to intensify as indicated by the recent White House Executive Order on AI, driven by new regulations, and the ongoing need to comply with existing mandates such as GDPR. Just as technology knows no borders alongside the rise of multi-cloud, the impact of AI and data spans across geographies, verticals and industries. Privacera underscores the urgency for organizations to proactively stay ahead of the regulatory curve, ensuring that their data and AI practices remain secure and compliant at global scale. As we move forward, data-driven organizations must be prepared to implement these safeguards and additional transparency in a unified, automated and global manner.

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