Why approvals are a good thing to automate
Many organizations run on small decisions that need a nod from someone: a purchase under a certain amount, a day off, a new software account, an expense claim, a change to a document. The decision itself is quick. The slow part is usually finding out who should decide, getting the request in front of them, and chasing it when nothing happens.
Approval workflows address exactly that gap. They do not make the decision for anyone. They make sure the right request reaches the right person with the right information, and that a record is kept. That makes approvals a sensible early project for a team new to automation, because the rules are often already known, even if they live in people’s heads.
Start by writing down the rules
An approval automation is only as clear as the rules behind it. Before opening any tool, write the answers to these questions:
- Who can submit a request, and what information is required? A request missing a cost or a reason will stall, so the form should require the essentials.
- What decides who approves? Common factors are the amount, the department, the type of request, or the requester’s manager.
- Is one approver enough, or are several needed? Some requests need approvers in sequence, others in parallel.
- What happens if the approver is away? Name a backup.
- How long should a request wait before a reminder?
- What is the outcome of each decision? An approval might trigger a purchase order, a calendar entry or a message to the requester.
If these rules are inconsistent today, expect the discovery to be uncomfortable. That is useful. It is better to settle the disagreement before building than to bake a confusing rule into a workflow.
Typical building blocks
Most approval flows are assembled from a small set of parts, similar to the triggers and actions used in other workflows:
- A structured form. Dropdowns and required fields reduce vague requests, such as asking for a category and a cost rather than a free-text paragraph.
- Routing conditions. For example, requests below a set amount go to a team lead, and requests above it also go to a finance contact. The amounts here are whatever your organization chooses; they should be set by policy, not by the tool.
- A notification to the approver. This usually includes the key details and a way to approve or decline directly from the message.
- Reminders and escalation. If nobody responds in a set time, the request nudges the approver and later moves to a backup.
- A final step. Once approved, the system records the decision and notifies the requester.
Because this is a clear, rule-driven process, it is a good illustration of rules-based automation. No AI is needed for the routing itself.
Where AI can help, and where to be careful
Some tools add AI to the front of an approval process. For instance, a model might read a free-text request and suggest a category, or summarize a long attachment for the approver. That can save time, but it introduces a chance of error. A wrongly categorized request could go to the wrong approver, and a summary could omit something important.
A sensible approach is to let AI suggest while people confirm, and to avoid letting an AI step make final decisions on anything with financial, legal or personnel consequences. Keeping a human review step where stakes are higher is a straightforward safeguard, and accountability for the decision should stay with a named person, not with the tool.
Common design mistakes
Too many approvers. Every extra step adds delay. Ask whether each approver changes the outcome. If someone almost always says yes, consider whether they need to be in the chain at all.
Rules that cannot be explained. If an employee cannot understand why their request went to a particular person, they will work around the system.
No backup path. Illness, leave and role changes happen. A workflow that stalls when one person is out is a risk rather than a help.
No limit on exceptions. Some requests do not fit the form. Provide a clear way to raise an unusual case instead of forcing it through a poor fit.
Ignoring the record. An approval is more useful when it leaves a trail: who asked, who approved, when, and on what basis. This supports compliance records and makes later questions easier to answer. Think too about how long such records should be kept, and who can see them, since requests may contain personal details.
Handling people, not just process
Automated approvals change how people work. Approvers may feel they have lost control, or requesters may worry that a form is less flexible than a conversation. Good change management helps: explain what is changing and why, show people how to use the new form, and keep a simple route for questions. A short round of staff training is usually enough for a process this simple.
Testing before you rely on it
Before rollout, run realistic sample requests through the workflow, including awkward ones: a request right at a threshold, one from someone with no manager recorded, and one where the approver does not answer. Check that each lands where you expect, that reminders fire, and that the final notification is accurate. Treat the first few weeks as a trial and review the results with the people using it.
A small example
Suppose a small office wants to handle requests for equipment purchases. In a hypothetical setup, the form asks for the item, the reason and the cost. Requests under a limit the owner chooses go to the team lead. Anything above it also goes to the owner. If there is no reply in three working days, a reminder is sent, and after five days it goes to a named backup. Once approved, the requester gets a message and a row is added to a purchases sheet. None of this is complicated, but together it removes a lot of chasing, and every step can be explained in a sentence.