Fortinet 2026 Report Finds AI Adoption Outpacing Web Application Security Readiness
Original report publisher: not verified. Report discovered via Awesome Annual Security Reports.
Summary
A survey of 871 cybersecurity and IT professionals found 53% reported a web application or API breach in the past year. Confidence in securing AI-integrated applications was just 15%, with visibility and detection gaps widespread.
Key points
- Cybersecurity Insiders produced the Fortinet-supported report using a stratified survey of 871 cybersecurity and IT professionals conducted in early 2026.
- While 76% reported using AI or machine learning in application-security defenses, only 15% expressed high confidence in securing AI-integrated applications and 12% in defending against AI-generated attacks.
- Seventy-four percent observed an increase in attacks appearing to be AI-generated or AI-assisted over the previous year.
- APIs were identified as a leading security risk by 67% and a major visibility gap by 53%; only 13% had high confidence in their overall application and API inventory.
- Fifty-three percent reported a web application or API breach in the previous year; credential stuffing and account takeover led reported attack entry points at 58%, followed by API abuse at 49%.
- Only 20% reported detecting incidents within minutes or hours, while 39% reported remediation taking about a month or longer.
- The report recommends continuous asset discovery, behavioral and session-level inspection, shared policy and telemetry, and measured deployment of AI for detection and triage.
Article Details
- Publisher
- Cybersecurity Insiders
- Report Period
- Early 2026 survey, including retrospective questions covering the preceding 12 months.
- Scope
- Survey of organizational web application and API security, AI-related threats, detection and response, tool consolidation, and investment priorities; produced with support from Fortinet.
- Sample Size
- 871 cybersecurity and IT professionals; stratified sampling, with a reported 95% confidence level and ±3.3% margin of error.
- Key Statistics
- High security confidence was reported by 29% of respondents for overall application security, 15% for AI-integrated applications, and 12% for defending against AI-generated attacks.
- 53% of surveyed organizations reported a web application or API-related breach in the preceding 12 months.
- 74% reported an increase in attacks that appeared AI-generated or AI-assisted over the preceding 12 months, including 35% reporting a significant increase.
- Only 20% reported detecting an incident within minutes or hours; the remediation chart reports 21% within a month and 18% longer than a month.
- 62% were actively consolidating application security tools or evaluating consolidation: 29% were actively consolidating and 33% were evaluating options.
- Recommendations
- Continuously automate application and API discovery across deployment environments, separately classifying AI-integrated applications and their dependencies and data flows.
- Use behavioral analysis before granting access and session-level inspection after authentication to detect automated credential abuse, API logic abuse, parameter tampering, and excessive data retrieval.
- Replace sequential, ticket-driven handoffs with automated decision loops that correlate application and network signals to accelerate containment.
- Pilot AI for real-time detection and triage, measure decision time and detection accuracy, and scale capabilities that demonstrate improvement.
- Unify WAF, API protection, bot management, and DDoS mitigation under shared policy and telemetry, updating security policies alongside application changes.