The cybersecurity landscape is constantly evolving, with new threats emerging at a rapid pace. In response to this volatility, security and risk leaders are in need of practical guidance on managing existing spending and adapting to new budgetary requirements. Forrester’s 2026 Budget Planning Guide highlights a significant shift in how organizations allocate cybersecurity resources, with software now commanding 40% of cybersecurity spending, surpassing hardware, outsourcing, and personnel costs. This shift comes as organizations face gen AI attacks that execute in milliseconds, compared to a Mean Time to Identify (MTTI) of 181 days.
Three converging threats are challenging traditional cybersecurity measures. Generative AI (gen AI) enables attackers to craft personalized phishing emails at a rapid rate, posing a significant risk to organizations. The looming NIST quantum deadline threatens data encryption, with $425 billion at risk of retroactive decryption. Additionally, deepfake fraud has seen a 3,000% surge and now bypasses biometric authentication in 97% of attempts, forcing security leaders to rethink defensive strategies.
Platform consolidation is becoming essential as security teams managing multiple tools face integration challenges and lose millions annually to overhead costs. Gartner predicts a decline in interactive application security testing (IAST) tools, while Security Service Edge (SSE) platforms add complexity rather than simplifying operations. Standalone risk-rating products flood security operations centers with alerts lacking actionable context, leading to analysts spending significant time on false positives.
Security budgets are on the rise, with 55% of security leaders expecting significant increases in the next 12 months. The rise in budget reflects the asymmetric battlefield where attackers leverage gen AI to target thousands of employees simultaneously. Regional spending variations highlight different threat landscapes and responses, with Asia Pacific organizations leading in budget increases.
Software dominates cybersecurity budgets in 2025, reflecting the need for runtime defenses to combat emerging threats. Protecting the inference layer of AI model development is crucial, with cloud security, on-premises technology, and security awareness training topping investment priorities. Quantum computing poses a growing risk, with the need for organizations to prioritize Post-Quantum Cryptography (PQC) adoption.
The explosion of machine identities fuels a credential crisis, requiring scaling machine identity management to mitigate threats. Ivanti’s AI-driven Vulnerability Risk Rating (VRR) enables organizations to patch vulnerabilities faster, highlighting the importance of combining AI with Unified Endpoint Management (UEM). Forrester advises security leaders to divest legacy tools and prioritize integrated platforms for enhanced visibility and streamlined management.
Consolidating security at AI’s inference edge is crucial for CISOs to maintain control and secure AI deployments at scale. By following a clear playbook that includes robust behavioral anomaly detection and investing in runtime defenses, organizations can adapt to the evolving cybersecurity landscape and stay ahead of emerging threats.
