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5 Cybersecurity Predictions for 2026 — Featuring Protegrity’s Quantum–AI Outlook

By Protegrity
Dec 5, 2025

Summary

5 min
  • Cybersecurity 2026: trust, AI, and compliance collide:
    In a Security Magazine expert roundup, leaders highlight accelerating shadow AI, converging security and compliance, deepfake defenses, and the rise of biometrics—signaling that enterprises must prove trust continuously across data, identity, and AI workflows.

  • Protegrity’s quantum–AI outlook on verifiable trust:
    Protegrity’s Arjun Kudinoor explains how quantum technologies like self-verifying random number generators, combined with agentic AI and data-centric protection, will shift security from “promised” to physically proven—helping organizations secure sensitive data and AI systems at machine speed.

In this expert roundup from Security Magazine, five leaders forecast what’s next in 2026—spotlighting shadow AI, the convergence of compliance and security, deepfake-driven disinformation defenses, quantum–AI security advances, and the mainstreaming of biometrics. Notably, Protegrity’s Arjun Kudinoor argues that the convergence of quantum tech and AI will redefine trust: from “promised” to physically proven through technologies like self-verifying quantum random number generators and agentic AI that adapts and mitigates errors in real time.

What’s in the piece

  • Shadow AI risk accelerates: Unsanctioned tools, plugins, and “micro-AI” expand the attack surface and complicate governance.
  • Compliance & security converge: EU AI Act, state AI bills, and sovereignty mandates push real-time assurance and automated controls.
  • Disinformation security goes enterprise-grade: Organizations move from awareness to deployment of deepfake defense and trust operations.
  • Quantum × AI reshapes trust (Arjun Kudinoor): Self-verifying QRNGs and agentic AI usher in security backed by physics and adaptive control.
  • Biometrics scale: Easier management and unified identity stacks bring biometrics into everyday access control.

Why it matters

The 2026 agenda blends policy, physics, and pragmatism: organizations must govern how AI is used, verify what data and signals can be trusted, and automate which controls keep pace with machine-speed threats. The common thread is trust that can be demonstrated continuously—across people, processes, and increasingly autonomous systems.

Protegrity’s perspective

  • Data-centric security for AI: Field-level protection (tokenization, masking, encryption) keeps sensitive data usable yet safe across agentic and LLM workflows.
  • Built-in guardrails: Discovery, classification, and semantic controls reduce leakage and enforce least-privilege by default.
  • Crypto-agility & quantum-safe roadmap: Preparing for PQC while leveraging advances in verifiable randomness and adaptive controls.

Trust moves from promised to proven:
As Arjun Kudinoor notes, quantum–AI advances (e.g., self-verifying randomness) and agentic guardrails will anchor security in physics and continuous verification.