Netwrix Security Research Lab Forecasts 2026-2029: The Rise of Identity and Data Security Dependency

As AI proliferates risk, jointly governing identity and data becomes mission critical

FRISCO, Texas, Jan. 27, 2026 /PRNewswire/ — Netwrix, a recognized leader in identity and data security solutions, today released its security outlook, forecasting that the next phase of cybersecurity disruption will come from adversaries scaling identity attacks to compromise data security as agentic AI becomes more prominent.

The outlook, developed by the Netwrix Security Research Lab, highlights the trends most likely to reshape cybersecurity between 2026 and 2029. These predictions are informed by ongoing research into real-world identity attacks and data exposure paths observed by Netwrix researchers.

What’s Most Likely to Reshape Security in 2026

• Identity Automation Tightens the Dependency Between Identity and Data Security
  By 2026, identity security will see a significant expansion in workflow orchestration and automation across provisioning, token validation, and privilege management. These workflows now determine who and what can access sensitive data, meaning failures in identity automation translate directly into data exposure risk.

  Adversaries are shifting their focus from individual credentials to identity orchestration, federation trust, and misconfigured automation. Since access to critical data stores starts with identity, unified visibility across identity and data security is required to detect misconfigurations, reduce blind spots, and respond faster.

• Agentic AI Expands Identity Driven Data Access at Scale
  As AI systems begin performing tasks autonomously, they rely on identities to access, move, and act on data. Understanding which identities AI agents use, what data they can access, and under whose authority they operate becomes essential.

  Without strong identity governance and data controls working together, agentic AI can rapidly amplify data exposure. The dependency between identity security and data security becomes more pronounced as AI-driven automation operates continuously and at scale.

• Cyber Insurance Enforces Proof of Identity and Data Controls
  As identity automation and AI driven access increase data exposure risk, cyber insurers are shifting how they assess and price risk. Rather than relying on periodic questionnaires, insurers are moving toward continuous validation of identity and data security controls.

  Insurers are expected to rely on telemetry that demonstrates how identities access sensitive data in real time. Organizations that can show consistent alignment between identity governance and data protection may benefit from improved terms, while those without visibility face increased scrutiny.

What Is Unlikely to Reshape Security in 2026

• The Real AI Risk Is Acceleration, Not Autonomy
  While AI is already influencing cybersecurity in meaningful ways, fully autonomous, self-directing AI-driven cyberattacks are unlikely to become a dominant threat in 2026. Recent state-sponsored espionage campaigns demonstrate that selective, high-cost autonomy is now possible under favorable conditions, but these operations remain human-supervised, fragile to unreliable feedback, and dependent on permissive identity and access environments.

  Operating effective autonomous attack campaigns in real enterprise environments remains complex, costly, and unpredictable. Noisy signals, environment variance, hallucination-prone outputs, operational risk, lack of reliable feedback loops, and high infrastructure costs make fully autonomous attacks economically unfeasible in most cases over the next year.

  Instead, attackers will continue to use AI to accelerate existing techniques – reconnaissance, impersonation, access abuse, and workflow execution – rather than fully replace human decision-making entirely. The more immediate challenge for defenders will be maintaining resilience against AI-accelerated attacks denying the conditions automation depends on, including broad access, clean feedback, and durable reward. Strong identity controls and data visibility remain the most effective safeguards, even as automation advances.

What’s Next on the Horizon by 2027

• AI-Driven Convergence of Systems and Data
  AI-driven optimization increasingly relies on AI agents that connect identity systems and data sources that were previously managed separately. These agents operate across multiple systems to carry out defined workflows, such as accessing applications, identities, and data on behalf of users or teams.

  As access conditions or data sensitivity change within any part of that workflow, governance models must ensure the AI agent’s permissions remain appropriate. In practice, this means continuously validating identity context, access privileges, and policy alignment across connected systems, rather than relying on static, siloed controls.

• Data Takes on More Built-In Protection
  Data is increasingly expected to carry encryption, provenance, and access policy with it as it moves across users, systems, and environments. Provenance provides context about where data originated, how it has been used, and which identities or systems have interacted with it.

  While this can reduce breach impact, inconsistent implementation risks fragmentation and blind spots. Strong identity context, standardized metadata, and consistent policy enforcement are required to make self-protecting data effective and manageable at scale.

Looking Ahead to 2028 and 2029: A Key Risk

• A Slowdown in AI Trust Undermines Security
  If economic pressure reduces investment in governance and oversight, organizations may be left with unmanaged models, undocumented drift, and compliance gaps. Mapping identity relationships, data dependencies, and AI ownership early will be critical to maintaining resilience.
• AI Vendor Instability Becomes a Data and Continuity Risk
  As organizations rely on a growing number of emerging AI providers, questions about where company data lives and who ultimately controls it becomes harder to answer. When prompts, training data, models, and outputs are processed or stored outside the enterprise, that data may be difficult to retrieve, govern, or even locate if a provider can no longer operate as expected. This challenge will intensify as AI vendors are acquired, restructured, or exit the market, leaving enterprises unable to easily retrieve, govern, or even locate data tied to those services.

  This creates cascading risks across compliance, security, and business continuity. Without clear data ownership, identity controls, and exit planning, reliance on upstart AI providers can turn experimentation into long-term data exposure and operational risk. Organizations that fail to establish enforceable data ownership and data governance will find that early AI experimentation has quietly evolved into persistent data exposure and business continuity risk.

“The threat landscape isn’t only expanding because attackers suddenly have better tools,” said Dirk Schrader, Vice President of Security Research at Netwrix. “It’s also expanding because identity security, data security, and automation are becoming inseparable. Our research team sees firsthand how misconfigurations and automated workflows create real exposure. Organizations that succeed will be the ones that govern identity and data security together and treat automation as something to be continuously validated, not blindly trusted.”

For deeper insight into the real-world vulnerabilities and attack paths informing this forecast, read the latest analysis from the Netwrix Security Research Lab.

About Netwrix

Netwrix’s vision is to create a world where every organization has secured its data and identities. The 1Secure SaaS platform unifies identity and data security to provide complete visibility into where data lives, who can access it, and how it’s governed. With Netwrix, security teams strengthen data protection, safeguard identities, and stay ahead of evolving threats. Today, more than 13,000 customers, including nearly 25% of the Fortune 500, rely on Netwrix solutions across hybrid and AI-driven environments. With a 95% customer satisfaction rating, Netwrix offers flexible delivery models that are quick to deploy, easy to use, and built to scale for organizations of all sizes. For more information visit www.netwrix.com.

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