01
Intentional oversight
Select human involvement based on risk, autonomy, decision authority, and the consequences of error.
White paper · October 2026
Beyond the Approval Button
Rethinking human-in-the-loop for Veeva Vault AI and Veeva Falcon
Get the 18-page white paper18 pages 9 sections Human oversight in practice
The approval paradox
An approval step is not automatically an effective control.
As AI moves from assisting with individual tasks to executing broader workflows, human oversight must evolve with it. Reviewers need the evidence, expertise, and authority to detect and prevent the errors that matter.
This paper explores how to preserve meaningful judgment, accountability, and control as Veeva Vault AI and Veeva Falcon take on more of the work—without defaulting to an approval step for every task.
What you will learn
- Recognize when an approval step becomes a formality instead of a meaningful control.
- Match oversight to intended use, agent autonomy, triggers, and the consequences of error.
- Assess whether vendor Agent Cards and qualification evidence cover your data, process, and reviewers.
- Establish accountability beyond audit trails with appropriate evidence and retention.
- Test reviewer effectiveness and scale oversight through monitoring, escalation, and exception handling.
From principles to practice
Three principles for defensible human oversight
02
Demonstrable accountability
Retain sufficient evidence to reconstruct agent activity, human decisions, and regulated outcomes.
03
Proven effectiveness
Evaluate the combined human-AI process under realistic conditions and monitor whether its controls continue to work.
Prove the control works
Measure effectiveness, not just approvals.
The paper identifies practical monitoring measures for the combined human-AI process. These are measures to track, not claimed performance outcomes.
Errors that escape review
Track consequential errors that reviewers miss to test whether the control provides its intended protection.
Corrections and rejections
Examine reviewer patterns. Low rejection rates may reflect better AI performance—or declining attention.
Escalation and resolution
Check whether exceptions are detected, routed, and resolved before unacceptable consequences occur.
“Human oversight should be treated as a control whose performance can be evaluated, not as a procedural label.”Beyond the Approval Button, page 4
Get the white paper
Make human oversight defensible.
Explore the approval paradox, regulatory expectations, vendor evidence, accountability, and testing the effectiveness of the human-AI process.
18-page PDF · USDM Life Sciences · October 2026
The paper distinguishes regulatory requirements, draft guidance, and design references. Applicability depends on intended use; platform capabilities vary by release.
Contributors
Brittany Walker
Principal Consultant
Hovsep Kirikian
Vice President of Strategy and Operations
Source: USDM Life Sciences, Beyond the Approval Button, October 2026. General information, not legal, regulatory, or compliance advice.