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Workflow Automation and AI Operations

Design workflows, approvals, tasks, AI recommendations, and exception routines that speed work without removing accountability.

3 lessons 45 min 5-question assessment 80% to pass
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What you’ll learn

  • Design automation from the business outcome backward
  • Choose triggers, conditions, actions, and human gates deliberately
  • Use AI suggestions as reviewed signals, not blind commands
  • Monitor logs, exceptions, and versions after publishing

Course content

3 lessons · 45 min of reading
01
Lesson 1 of 3 Workshop 14 min

Design backwards from the decision

The best workflow is not the one with the most steps. It is the one that makes a repeated decision happen consistently, with the right evidence and the right owner.

Start by naming the decision: approve a purchase, notify a manager, assign a task, escalate a late receipt, or suggest a reorder. Then work backward to the trigger and conditions that prove the decision is needed.

Workflow design canvas

1

Decision

What must happen differently because this workflow exists?

2

Trigger

What event or schedule starts the workflow?

3

Condition

What facts must be true before action is safe?

4

Action

Notify, create task, request approval, call webhook, or update status.

5

Proof

What log, comment, version, or evidence shows it ran correctly?

02
Lesson 2 of 3 Lab 15 min

Automation with human gates

Automation should remove repetitive chasing, not accountability. AWRA workflows can trigger from events, evaluate conditions, create tasks, request approvals, and send notifications while keeping sensitive decisions human-reviewed.

The pattern is simple: automate the routing and evidence collection; keep judgment where risk is high.

Automation boundary

Situation Automate Human gate
Low-value reorder Notify buyer and draft request Buyer confirms quantity
High-value purchase Route approval with evidence Approver accepts or rejects
Delayed PO Create escalation task Owner contacts vendor and records outcome
Failed webhook Retry and log failure Admin reviews repeated failure
Suspicious adjustment Flag anomaly Manager investigates before posting

Key takeaways

  • Automate routing, reminders, and evidence collection.
  • Keep judgment on high-risk decisions.
  • Logs and versions make automation governable.
03
Lesson 3 of 3 Practice 16 min

AI signals, logs, and continuous control

AI in operations is most useful when it narrows attention: possible stockout risk, stale RFQ, overdue invoice, unusual journal, or recommended workflow draft. The user still owns the decision.

After publishing, the workflow enters operations. Review logs, failed runs, exceptions, version changes, and AI recommendations. A workflow that nobody monitors becomes invisible risk.

Automation health signals

Run rate

Volume

Spikes may reveal noisy triggers or business change.

Failure age

Reliability

Old failures usually mean no one owns the exception.

Approval age

Bottleneck

Slow approvals turn automation into delay.

AI rule

AI can recommend, summarize, and draft. A person still approves the operating decision, especially when money, access, stock, or customer commitments are affected.

Finished the material?

Take the 5-question assessment and earn your certificate — 80% to pass.

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