RSMUS.comConstruction automation governance helps construction finance teams use AI-assisted tools while keeping people involved in consequential decisions. Construction remains human-driven: people bring the judgment, practical experience and hands-on involvement needed to design, build and manage projects. Technology can support that work, but it does not remove the need for human review.
What is the AI Trust Label?
Trust in AI depends on transparency and accountability, especially when financial results, reputation, health and safety may be affected. Sage Intacct’s AI Trust Label is intended to make key information available about labeled solutions, including:
- How customer data is used
- Practices for AI accuracy and monitoring
- How bias is mitigated
- Which global regulations are followed
- Which ethical controls are present
Not every user will examine every detail. Still, access to this information gives teams a clearer basis for evaluating how an AI-assisted feature operates.
How do people retain control of decisions?
AI can support complex work, but consequential decisions still need human involvement. Sage Intacct describes a model in which users approve or authorize actions, AI presents recommendations rather than making autonomous financial decisions and generated outputs include information about the workflows and logic used to reach a conclusion.
Across AI-enabled features, actions are described as traceable, workflows as auditable and insights as monitored. This approach keeps people involved in review and supports clearer accountability from input to outcome. For construction organizations, that visibility matters when financial decisions carry material consequences.
Construction automation governance is most useful when controls are clear, review points are visible and people can question or reject a recommendation.
How is this approach to automation different?
Sage Intacct’s stated approach focuses on making workflows more efficient without allowing them to operate independently from human review. Rather than automatically posting every transaction, the described features help detect anomalies, recognize patterns, model scenarios and guide analysis. Examples in the draft include:
- General ledger outlier detection
- Variance analysis
- Close automation guidance
- Finance intelligence agent insights
- AP Automation with discrepancy detection and matching
These capabilities are intended to reduce time spent organizing and analyzing data, flag potential errors or omissions and surface insights for further review. Human decision-makers remain responsible for interpreting the information and deciding what action to take.
Evaluate automation through trust and governance
Construction teams have many AI-enabled tools to consider. A practical evaluation should look beyond speed and ask how a solution handles transparency, approval, monitoring, auditability and accountability.
For Sage Intacct, construction automation governance centers on AI as a tool that supports people rather than replacing them. Teams considering AI-assisted financial workflows can review both the capabilities and the controls before deciding where the technology fits.
Contact RSM to learn more about the capabilities and controls.
Keith Rodriguez
Keith is a Sage Intacct implementation consultant who specializes in the construction and real estate industry. He has led engagements from client discovery and system design through handoff to the client’s new ERP system. With eight years of experience in construction project management and real estate property management, Keith is able to engage with CRE clients at their level through a deep understanding of the systems and processes in these industries.
