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Most companies add AI to an operating model built for manual work. Accountability, roles and controls fall behind.
Each team measures only its own step.
No one knows what AI may do or who handles a bad result.
Policies exist, but the workflow lacks permissions, logs and escalation.
Weekly updates report activity instead of whether criteria were met.
We map work to the APQC Process Classification Framework so every workflow has a standard name and boundary, then design ownership, roles and controls around it.
Place each workflow in a standard process hierarchy and name who owns each decision.
Define teams, product owners, specialists and shared capabilities.
Specify what each agent may do, what it may only recommend and where a person approves.
Put permissions, audit logs, health checks and recovery steps into the workflow itself.
Replace status meetings with scorecards. An agent gathers the evidence, and a named person approves each score.
We pick one value stream and document its decisions, costs and gaps.
We draw the new workflow, roles, approvals and measures with the accountable leaders.
We run it in one unit, fix what breaks and then expand.
Accountability is clear across teams.
Tasks, permissions and escalation are set in advance.
Every team names its work the same way.
People approve only where it matters.
Policy connects to permissions and logs.
Progress is scored against criteria.
Roles and skills change with the work.
The design is proven before it spreads.
Point One Zero practice
Point One Zero runs several client and product tracks with a lean team, and weekly status updates were taking too much leadership time. We replaced them with a scorecard in which each review system publishes one score, an agent gathers the evidence and a named person approves it. Our strategy work is mapped to the APQC framework to level four, so every initiative is described the same way.
An organization design in which people and AI agents share work under clear rules: who owns each outcome, what agents may do alone, where people approve and how results are measured.
Give each agent a job description: its task, tools and data, the actions it may take alone, what it may only recommend and who it escalates to. Enforce it with permissions.
It gives every process a standard name, number and level. Teams can then describe work consistently, compare AI initiatives, spot duplication and assign owners.
At the point of work: limited permissions, audit logs, health checks, human approval for major actions and a recovery plan. A policy document alone governs nothing.
With one commercially important value stream that crosses several teams. Prove it there before expanding.
We will map its decisions and roles and design a model your leaders can run.
Design your AI operating modelOr email us at admin@pointonezero.com.