Context graphs are structured records of how decisions are made within an organization. They capture the steps taken, people involved, information used, and reasons behind a decision, allowing others to see not just the outcome, but how and why it happened. They function like a connected record of decision activity, linking actions, communications, and approvals into a traceable history that can be reviewed and learned from. Context graphs represent a shift from tracking what happened to understanding how and why decisions happen—an increasingly important capability in complex education and workforce systems.

In practice, context graphs are used to reconstruct, understand, and improve decisions, especially in situations where judgment and exceptions are common. Common uses include:

• Explaining past decisions (e.g., why an exception was approved, why a student received a waiver)
• Improving consistency (helping staff make similar decisions in similar situations)
• Training and onboarding (showing new staff how decisions are typically made)
• Supporting artificial intelligence tools (providing examples of how people apply rules and make judgment calls)
• Identifying patterns and improving processes (revealing bottlenecks, workarounds, or inconsistent practices)

Context graphs are usually not a single visible tool or document. Instead, they are built by connecting information that already exists across systems. They are most often found:

• Within internal systems, such as workflow or ticketing systems, advising or case management platforms, customer or student record systems, and collaboration tools (messages, comments, notes)
• As part of emerging enterprise tools, especially those using artificial intelligence to analyze workflows and decisions
• Behind the scenes, assembled by data, technology, or analytics teams rather than presented directly to end users

In many organizations, context graphs are still developing and may not yet be formally labeled as such.

Context graphs are typically internal and often confidential because they include:

• Decision rationale and internal discussions
• Personnel involvement
• Sensitive student, employee, or customer information
• Exceptions to standard policies or practices

Access is usually restricted based on role and governed by data privacy and compliance policies. They are rarely shared publicly.

While context graphs support multiple roles, they are most commonly used by:

• Managers and leaders to review decisions, ensure consistency, and guide policy or strategy
• Operational staff and practitioners to understand how similar decisions have been handled
• Data, technology, and analytics teams to build systems that analyze or support decision-making
• Organizations implementing artificial intelligence tools to improve how systems interpret and replicate human judgment

Over time, their use may expand as tools make this information easier to access and apply.