The 2026 Artifact Management Report
As AI-generated code becomes the norm, the systems responsible for securing, governing, and delivering software artifacts are under unprecedented strain.
The 2026 Artifact Management Report examines the structural vulnerabilities now embedded in modern development pipelines, and the operational, regulatory, and architectural responses required to address them.
There is an enforcement gap: detection without action
Organizations have made meaningful investments in vulnerability visibility, but visibility alone does not constitute security.
Many can quickly determine whether a specific vulnerability affects their environment soon after disclosure, yet only a minority have automated security policies in place to act on that information. The majority still rely on manual investigation and remediation - an approach that does not scale with the speed and volume of AI-assisted development, or with the reporting timelines mandated by emerging regulation.
of teams can identify vulnerable dependencies within six hours of disclosure
automatically enforce security policies using that data
AI adoption has outpaced governance frameworks
AI adoption has outpaced governance frameworks. AI-generated code is now near-universal in professional software development, with the vast majority of organizations using it to accelerate delivery. The security implications are significant and remain underaddressed.
AI coding agents introduce dependencies that have not been vetted against organizational risk tolerances, while hallucinated package references - a known failure mode of large language models - create new vectors for supply chain compromise. At the same time, AI/ML models have themselves become a primary artifact type, yet only a small minority of organizations govern these models using the same security policies and provenance tracking applied to traditional binaries.
The result is a fragmented control plane: AI is generating more of the software supply chain while remaining largely outside the governance systems designed to secure it.
of organizations use AI to accelerate software development, yet most lack governance policies to validate AI-generated dependencies or artifacts.
Dependency risk is rising
Dependency risk is rising. Modern applications are compositional by design, with the average application now containing more than 1,200 dependencies - each representing an artifact with its own provenance, maintenance history, and vulnerability surface.
Over the past 12 months, a significant proportion of organizations have experienced dependency-related security incidents or near misses, reinforcing that the probability of encountering a compromised or vulnerable dependency is no longer a tail risk, but a baseline operating condition.
dependencies are included in the average application
of organizations experienced a dependency-related security incident
reported a near miss
Compliance pressure is increasing
Compliance pressure is increasing. The EU Cyber Resilience Act enters enforcement in September 2026, establishing strict, time-bound reporting requirements for actively exploited vulnerabilities, from early warning through to final reporting following corrective action.
While most organizations now generate SBOM data, only a minority integrate SBOMs into automated security gatekeeping. For the majority, SBOMs remain static compliance artifacts rather than operational tools - a posture that is directly incompatible with the Act’s requirements.
Confidence is also low when it comes to passing an unannounced software supply chain audit, highlighting a clear gap between compliance activity and true operational readiness.
of teams generate SBOMs
actually use them in automated security policies
Legacy infrastructure imposes a measurable operational cost
Most organizations operate artifact management systems that were not designed for the scale, distribution, or threat environment of AI-accelerated development. The consequences are clear: distributed team members frequently experience performance issues, and many teams are forced to manually provision infrastructure in response to usage spikes.
This operational overhead - what the report terms the “operational tax” - diverts engineering resources away from high-value work and compounds existing security exposure. Organizations that are most resistant to infrastructure modernization often cite security as their rationale, while continuing to run systems that represent some of their greatest architectural vulnerabilities.
of organizations use artifact management systems not built for AI-driven scale, distribution, or security.
of distributed team members experience frequent performance issues
manually provision infrastructure in response to usage spikes
Download 2026 Artifact Management Report
The 2026 Artifact Management Report explores how engineering teams are responding to AI-driven development, rising supply chain attacks, and new regulatory requirements.
