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02/08/2026 12:09 pm
TL;DR: Gartner’s Application Security Strategy 2026 report says 43% of organisations remain at the lowest application security maturity level, while 65% of engineering leaders already use AI tools and platform consolidation is reshaping tool strategy, according to Veracode and Gartner. The signal for practitioners is clear: governance, developer experience, and risk-based prioritisation now matter more than adding another scanner.
NHIMG editorial — based on content published by Veracode: Looking Ahead at 2026 with Gartner on application security, AI, DevSecOps, and platform consolidation
By the numbers:
- 65% of engineering leaders say their teams are already using AI tools.
Questions worth separating out
Q: What breaks when application security teams rely on tool sprawl instead of control design?
A: Tool sprawl usually breaks prioritisation, not just visibility.
Q: Why do AI-generated code changes increase application security risk?
A: AI-generated code can increase risk because it accelerates output faster than review, testing, and secret hygiene can keep up.
Q: How do you know if AppSec prioritisation is actually working?
A: Look for fewer high-exposure findings lingering across sprints, faster closure of issues tied to critical assets, and less duplicate triage across tools.
Practitioner guidance
- Prioritise remediation by exploitability and reachability Use a risk filter that sends only reachable, exploitable, or externally exposed findings to engineering first.
- Define policy for AI-assisted code generation Set rules for where AI can be used, what code paths require review, and when generated output must be blocked or rewritten.
- Inventory overlapping AppSec tools before consolidation Map scanners, posture tools, and supply chain controls to the outcomes they actually enforce.
What's in the full article
Veracode's full article covers the operational detail this post intentionally leaves for the source:
- How Veracode applies Gartner's application security strategy themes to remediation workflows and developer experience
- The specific way AI code security assistants fit into day-to-day development rather than policy discussion alone
- Veracode's examples of platform consolidation across application security testing, supply chain security, and posture management
- The article's implementation-oriented take on automating policy in the development pipeline
👉 Read Veracode’s analysis of Gartner’s 2026 application security strategy →
Application security maturity, AI and platform consolidation: what changes now?
Explore further
02/08/2026 1:13 pm
AI-assisted development is now an access-governance problem as much as a code-quality problem. Once AI systems are writing or modifying code, they influence which libraries, secrets, build paths, and deployment actions enter the environment. That creates a governance surface that looks more like identity and privilege control than traditional static scanning. The practical conclusion is that AppSec teams need policy over machine-generated actions, not just vulnerability detection after the fact.
A question worth separating out:
Q: When should organisations consolidate application security platforms?
A: Organisations should consolidate when separate tools are producing overlapping findings, conflicting policy decisions, or disconnected reporting across code, build, and runtime. Consolidation makes sense only if the new operating model preserves evidence, enforcement, and ownership. If it removes control depth, the programme becomes simpler but weaker.
👉 Read our full editorial: Application security maturity lags while AI and platform consolidation rise
