For the COO
Sovereign intelligence for the COO
Turn AI into operational execution.
The COO is judged on throughput, quality, cost and service levels, and cares less about what a model can say than what the process can do. Operations also carries the day-to-day consequences when a tool misbehaves, so reliability and recovery matter as much as capability. AI becomes operational when it sits inside a workflow with owners, handoffs and exceptions, rather than in a side window.
What a COO worries about
AI beside the process, not inside it
An assistant that employees consult occasionally changes little. The gains come when AI steps are part of the workflow, with inputs, outputs and handoffs defined.
Exceptions and escalations
Most processes are easy until they are not. The cost of automation is decided by how well edge cases reach a person with the right context.
Reliability and recovery
A workflow that fails halfway can leave orders, tickets or records in a bad state. You need retries, idempotency and a clean way to resume or roll back.
Unclear accountability when AI acts
If an agent approves, sends or changes something, who is responsible? Operating teams need approval rules that match existing authority limits.
Savings that cannot be shown
Without baselines for cycle time, error rate and cost per case, claimed benefits remain anecdotes. Operations leaders need measurement designed in.
What a Sovereign Intelligence Platform gives you
Governed workflows
The workflows layer is designed to embed AI in how the organisation operates, with approvals, limits and records built into each step.
Agents inside defined authority
The agents layer lets AI act without uncontrolled authority, as in the AI Procurement Agent example, which can draft purchase orders but cannot make payments.
Human approval where it matters
Approval rules, thresholds and escalation put people in the path for purchases above a limit, contract changes and sensitive external communications. See runtime governance.
Templates to start from
Studio builds agents and automations without code, and the Marketplace offers pre-built agents and workflow templates as starting points.
Outcomes you can measure
The solutions layer focuses on measurable business results, so each deployment has a metric and an owner from the start.
Capabilities are described as what the platform is designed to let you do. For what is true today and what is not claimed, see the trust centre.
Questions to ask any vendor
Use this as a checklist in any evaluation, ours included. Each question comes with what a good answer looks like.
01How are human approvals built into workflows, and what happens while an item waits?
A good answer: Approval steps are native, with timeouts, reminders and delegation, and the state of waiting items is visible and recoverable.
02How do workflows handle failure, retries and partial completion?
A good answer: Idempotent steps, configurable retries, durable state and a defined resume or rollback path, shown in a failure demo.
03How are exceptions routed to people, and with what context?
A good answer: Routing rules by type and risk, with the full case history, the AI's reasoning summary and the data it used attached.
04Can we set limits by value, volume and action type?
A good answer: Yes. Limits such as spend per transaction, records per hour and allowed systems are enforced by policy, not by prompt wording.
05How do we see work in progress, throughput and error rates in real time?
A good answer: Operational dashboards by workflow and step, with alerts and exports to existing reporting tools.
06How do we integrate with the systems we run today, and who maintains the connectors?
A good answer: A list of supported systems and open protocols, with ownership of connector maintenance stated and options for custom connectors.
07What is the process for changing a live workflow safely?
A good answer: Versioning, staging, test runs on historical cases and a controlled release with rollback.
08How is cost per case calculated and capped?
A good answer: Per-run model, tool and compute cost recorded and reported, with budgets and routing choices that let us reduce cost.
09What baseline and measurement method do you recommend for proving benefits?
A good answer: Pre-launch baselines for cycle time, quality and cost, and a comparison method, with the metrics owned by the process owner rather than the vendor.
10How do people on the floor tell the AI it was wrong, and what happens to that feedback?
A good answer: A one-click correction route inside the tool people already use, with each correction attached to the case, reviewed by the process owner and fed into evaluation sets, so quality improves from real operations rather than from a vendor's generic data.
11How do you handle peaks, queues and seasonal volume without degrading quality?
A good answer: Queue management with priorities, controlled concurrency, graceful degradation to a human queue when model capacity is constrained, and reporting that shows how quality and turnaround behaved during the last peak.
12What are the support and escalation arrangements when a workflow stops?
A good answer: Named support tiers and response commitments in the contract, or a placeholder stating they are still to be agreed. Do not accept an unstated service level.
Recommended reading
- Guide: design governed workflows
- Operational sovereignty
- Controlled autonomy: a practical rollout plan
- Platform: governed workflows
- Platform: AI solutions
Not sure where to start? Take the readiness assessment or read the build guide.
Frequently asked questions
Where should a COO start with AI in operations?
Pick a repeatable process with clear inputs, an owner and a measurable outcome, then begin with AI recommending and a person approving.
Will agents replace approval steps?
Over time some approvals can move to thresholds and exceptions, but only where evidence supports it. Approval rules should match your existing authority limits.
How is a workflow different from an agent?
A workflow defines the steps and handoffs of a process. An agent is one actor within it that can reason and use tools. Governed workflows combine both under shared policy.
Build with control: for the COO
Start with one entry point. Add intelligence, agents, workflows and infrastructure as you prove value. Or read the step-by-step build guide and take the readiness assessment.