How to identify a good automation candidate
The most frustrating task is not necessarily the best place to start. Look for frequent work with a clear beginning and end, consistent rules and accessible data. The result should also be easy to verify.
Do not automate a process simply because it exists. Remove unnecessary steps, choose the source of truth and clarify ownership of exceptions first. Automating a confused workflow usually accelerates its problems as well.
Simplify before you automate
Walk through the process with the people who do the work every day. A single form, a shared definition of status or the removal of an unnecessary approval can create more value than automatically reproducing every current step.
1. Recurring reports
Every Monday, someone exports data from several systems, copies it into a spreadsheet, fixes the formatting and emails the file. That work can often be separated into data collection, completeness checks, agreed calculations and publication in one location.
First ask who reads the report and which decision it supports. Instead of another file, the business may need a simple view of three current facts and a signal that shows when deeper investigation is necessary.
2. Re-entering data between systems
Customer details move from a form to an inbox, then to the CRM and finally to billing. Each transfer takes little time but creates another chance for a typo, missing field or delay.
An integration can move the data, provided that one system is identified as its owner. The workflow must also handle duplicates, missing required information and periods when the destination is unavailable.
3. Producing repetitive documents
Proposals, confirmations, protocols and agreements are often created by copying the previous file. If the document has a stable structure, it can be generated from an approved template and information already recorded elsewhere.
Automation should reduce retyping without removing necessary control. The document can go to its owner for review before it is saved or sent. AI is only relevant when part of the content genuinely depends on an unstructured description.
4. Updating the CRM after meetings
After a call, a salesperson writes a note, changes the opportunity stage, creates the next task and updates the team. Automation can prepare part of this work: create a dated task, flag a missing field or draft a summary of the notes.
It should not silently reinterpret an opportunity based on an open conversation without clear rules and a way to correct the result. The system should reduce administration while leaving the process owner in control.
5. Collecting project updates
A manager asks several people for updates, combines their replies and writes a summary. If tasks are maintained in one system, automation can collect changes, risks and dates and flag missing information before the review.
An automatic summary cannot replace a conversation about blockers. It can remove the work of retyping status so that the meeting is used to make decisions.
6. The first stage of customer service
Frequent enquiries can be categorised, routed to the right queue and linked to an approved instruction. Deterministic rules are enough when a form provides a clear subject. AI can help with free-form messages or draft a response from controlled knowledge.
Customers should be able to reach a person when the case falls outside the standard path. It should also be clear whether an answer is automatic or has been reviewed by a member of staff.
7. Handovers between departments
Sales closes a deal, operations needs the scope, finance needs billing details and support needs earlier agreements. Without a shared flow, every team asks for the same information again.
An automated handover can create the right tasks, transfer approved data and notify the owners of each next step. The crucial part is defining when a case is genuinely ready. Sending more notifications does not by itself improve collaboration.
Start with one measurable flow
Choose a frequent process spanning only a few systems. Record the current steps, effort, common exceptions and owner. Remove unnecessary work, then automate in stages while keeping the failure path visible.
After launch, review data quality, exception volume and whether the team trusts the new flow—not only the time saved. Automation should relieve the process rather than add another layer that someone must watch manually.
The most valuable automations are often simple. They connect information, keep the sequence moving and return a decision to a person at exactly the right moment.