Software transparency as a business priority: Governing AI-driven development and complex supply chains

Software supply chain integrity appears to be becoming an increasingly important consideration in enterprise risk management. This comes as AI-assisted development expands and software supply chains gain additional complex layers.

These developments invite business leaders to consider a fundamental question: Can they confidently account for the software they develop, purchase, and deploy? For enterprises pursuing innovation alongside resilience, software transparency may provide a valuable foundation. It can help with understanding intellectual property, licensing responsibilities, and the economic implications of software supply chain decisions.

Aaron Branson is chief growth officer of FossID, a software composition analysis (SCA) company specializing in source-code intelligence and software supply chain transparency. He notes that the question begins with visibility into the code itself.

“Organizations can know which suppliers they engage and which software products they procure, but establishing the precise composition of those products can require additional investigation,” he states.

The visibility gap

Open-source libraries, transitive dependencies, supplier-developed components, and AI-generated snippets may enter a codebase through different channels. Branson highlights an important distinction. Supplier records can provide useful context. Examining the underlying code may offer further insight into its origins and associated obligations.

This visibility gap can have implications across several business functions. Unclear software provenance may complicate intellectual property assessments, licensing reviews, procurement decisions, and customer assurances.

Branson explains, “An organization’s understanding of its software can influence how confidently it evaluates the assets it builds, the obligations it accepts, and the commitments it makes to customers.”

Software transparency, in this context, can support more informed decisions across the product lifecycle.

AI changes the pace

AI-assisted development adds another dimension to this challenge.

“Companies need to adjust their oversight as development moves faster,” Branson says. “AI can pump out code in seconds, but our review processes, documentation, and compliance checks just aren’t set up for that speed. Plus, snippet-sized code can sneak into applications without ever showing up in standard dependency records.”

He adds that as a result, organizations may benefit from examining how they compile their software inventories. They may also check how reliably those records reflect the code in use.

The quality of documentation matters within this process. Software Bills of Materials (SBOMs) can provide structured inventories of software components and dependencies. They help teams organize information across complex products. CISA’s 2026 Minimum Elements for a Software Bill of Materials provides guidance on the information an SBOM may contain and its role in software supply chain transparency.

For enterprises receiving software from multiple suppliers, the value of these inventories may depend on the detail, consistency, and currency of the information provided. Source-code analysis can complement dependency documentation. It helps teams assess whether component records correspond with the software they are examining.

From origin to obligation

FossID’s work in software composition analysis relates directly to this need for verifiable information. FossID designed its technology to identify open-source components, licenses, and third-party code fragments. That includes material that may be difficult to trace through package declarations alone. This capability can help organizations investigate the composition of software that incorporates third-party contributions or AI-assisted code.

“Software provenance becomes more useful when teams can connect a component’s origin with the responsibilities that may follow it,” Branson remarks.

Such information can give engineering, legal, security, and compliance teams a shared basis for evaluating software decisions.

These considerations also suggest an opportunity to integrate governance more directly into everyday work. Software composition and licensing checks can become part of development pipelines, procurement reviews, and supplier-management processes. When teams refresh component information as software changes, they may find it easier to assess new dependencies, review licensing requirements, and prepare for product or regulatory evaluations.

Organizations can distribute responsibility for this work across functions. Engineering contributes technical context, legal teams interpret obligations, procurement reviews supplier information, and leadership establishes priorities and accountability.

Where leaders can start

As Branson notes, business leaders can begin by identifying who owns software supply chain risk. They can also look at how that responsibility connects to existing governance structures. Reviewing the methods used to create, validate, and update software inventories may help reveal where additional verification could be useful.

Supplier due diligence can also incorporate questions about software composition, provenance, and SBOM quality. Product lifecycle processes can establish expectations for keeping those records current. Aligning these activities with development speed may allow governance to support innovation as teams create, integrate, and release code.

Essentially, software transparency may offer enterprises a practical foundation for resilience, accountability, and sustainable innovation. AI expands the ways teams can produce software, and interconnected supply chains get embedded more deeply within organizations. Understanding code composition can help leaders evaluate both opportunities and responsibilities.

For Branson, the broader ambition is to connect software creation with informed oversight.

He says, “The opportunity is to make software supply chain integrity central to how organizations innovate, ensuring that growth strategies account for code lineage and its associated obligations.”

Enterprises that pair development capability with reliable knowledge of their software may be better positioned to make informed decisions. That holds throughout the product lifecycle.