For companies using AI

Useful AI-enabled workflows begin with usable information. Documents, recordings and operational knowledge need appropriate organization and context. Introducing AI into an operation also creates choices about what happens before and after a generated result. Which information is appropriate to use? What needs checking before the next step? Who decides when an unusual case falls outside the instructions? Those choices define the human work the process requires.

ADCO can scope review and operational support around those responsibilities. Begin with the actual workflow, its intended result and the consequences of error, so the role of the reviewer is clear before work begins.

A review task can focus on source support, relevance, completeness or conformity with approved instructions. Verification can trace a claim to evidence and record unresolved conflicts. Exception handling can organize the facts and route the case to a person with authority to decide. Each task needs its own criteria and working context.

For example, a hypothetical AI-assisted knowledge workflow might send an unsupported answer for source checking before release. That example describes a possible design, not an ADCO client project. The required checks depend on the information and the use.

Agree who assigns work, reviews it, handles escalations and accepts the result. Establish what happens when information is missing, an instruction is unclear or an output needs correction. Findings become more useful when they reach an owner who can improve the source material or change the process.

Managed delivery and client-directed talent offer different ways to organize that work. In either arrangement, human review complements appropriate system permissions and technical controls. Specialist or regulated decisions require the relevant qualifications and authority; an operational reviewer cannot replace those requirements.