You’ve heard that AI can help you get more work done, faster. But where do you start?
To know what to automate, you’ll need to identify tasks that are repetitive, rule-based, and easy to check. Then you’ll need to set up a workflow that can run without constant supervision but flag failures before they cause problems. Finally, you’ll need to leave enough room for human judgment where a mistake could be costly to undo.
If you’re on our website, you’re probably also considering the privacy and security implications of workflow automations. You’ll need to know where your business and client data goes, who can access it, and how it will be used.
In this guide, we’ll walk you through each of these decisions, step by step, to help you spot good candidates for automation and run a pilot that saves your team valuable time.
We’ll answer every question you have about workflow automation including:
- What is workflow automation
- How to identify tasks that are easy to automate
- How to vet every automation before you commit
- How to plan an automation workflow sequence
- How to leave room for human judgement in your automation workflow
- How to choose automation software that protects your data
- How to test your workflow automation
What is workflow automation?
Workflow automation uses software such as Zapier, Microsoft Power Automate, and Jira to carry out steps that would otherwise be done manually. For routine work, this often means following straightforward rules, such as sending a reminder when a deadline passes or uploading an approved report to the correct folder. In the next section, we’ll show you how businesses are automating tasks in every department, from customer inquiries to marketing reports.
AI workflow automation uses large language models to interpret information, generate content, or choose the next action within a workflow. Large language models can work with connected software, such as calendars or file storage services, to take actions within the permissions they’re given.
Depending on the connected tools available, an AI assistant for business can manage a whole workflow from start to finish or handle individual steps. For example, you could ask Lumo to prepare a project update from your team’s weekly progress notes.
Workflow automation benefits and examples
| Workflow | Example of automation | Practical benefit |
| Customer inquiries | Acknowledge incoming requests and route them to the appropriate team | Faster responses: Customers receive confirmation outside office hours, and requests reach the right people sooner |
| Invoice processing | Transfer invoice details into accounting software and flag missing fields or possible duplicates | Lower processing costs and fewer errors: Less time spent entering information and correcting transcription mistakes |
| Employee onboarding | Create setup tasks, send welcome information, and notify colleagues when their input is needed | Greater consistency: Each new hire gets the required steps without relying on someone to remember every detail |
| Sales handoffs | When a deal is marked complete, create an onboarding task and notify the account team | Better coordination: Teams know when work is ready for them and who is responsible for the next step |
| Inventory updates | Transfer stock figures between systems and flag items below a set threshold | More capacity: A growing number of products and orders requires fewer manual stock checks |
| Marketing reports | Collect campaign metrics and populate a standard report | More time for analysis: The team spends less time assembling figures and more time deciding what to change |
How to identify tasks that are easy to automate
Before automating a task, consider whether it still needs to be done at all. A report nobody uses may be worth retiring rather than automating. Then, for the work you’ve decided to keep, look for tasks that share these traits:
- They happen often: The task comes up daily, weekly, or with every new request, so time saved adds up.
- They follow the same steps each time: You could write the process down as a set of rules without needing many exceptions.
- The information arrives in a predictable format: Forms, spreadsheets, and standard documents are easier to automate than free-form requests.
- Mistakes are easy to spot: A missing field or misfiled document is quickly noticed and fixed.
To find them, look for where work slows down or goes wrong. Common signs include information copied by hand from one place to another, colleagues waiting for someone to pass work along, and the same errors being corrected again and again. Tasks like these are often well suited to automation, such as:
- Copying information between apps or spreadsheets
- Sending standard reminders and confirmations
- Checking whether required fields are complete
- Preparing reports from the same sources
- Moving files into predictable folders
Now that you’ve identified tasks you could automate, it’s time to check whether each one is worth the effort.
How to vet every automation before you commit
Because every automation takes time to set up, check, and maintain, run each task through these five checks before you commit to it:
- Compatibility: Confirm the software you’re considering can exchange information with the apps you already use. If it can’t connect to where your data lives, someone will end up moving it by hand, which defeats the purpose.
- Ownership: Name one person to set up the automation and keep it running. When a process changes or a step fails, your team needs to know who to go to.
- Technical support: Find out whether that person can manage the setup alone or will need help from IT or an outside provider. Build that time and cost into your plan from the start.
- Current workload: Ask the people who do the work how long each task takes, how often they fix mistakes, and how much time they lose waiting on approvals.
- Time saved: Using those figures, compare the time automation could save with the time it takes to set up, review, and maintain, plus any subscription costs. For example, a three-hour setup that cuts a two-hour monthly task to 30 minutes of review pays for itself in two months.
How to plan an automation workflow sequence
Automation is easier to set up and check when you have a clear plan for how the work should move from start to finish.
Sketch the process as a simple flowchart and work through these points:
- Start and end points: Define what kicks the workflow off, such as a form submission or an email arriving, and what counts as finished.
- Each action in order: List every step between the two, and note what information each step needs and what it passes on to the next.
- Decision points: Wherever the work could go more than one way, write the rule as a yes-or-no question. “Is the amount present and readable?” is something software can check. “Does the claim look right?” isn’t.
- What happens when something goes wrong: For every “no,” decide where the work goes next, who gets notified, and where it rejoins the workflow once the problem is fixed.
- Approvals: Mark any step where the workflow should stop and wait for a person before it continues. The next section covers how to decide which steps need one.
For example, you might use document workflow automation to process expense claims that employees submit with receipts for their purchases. The plan below shows how the software reads each receipt, handles missing information, and sends a complete claim for approval.
How to leave room for human judgement in your automation workflow
If you’re worried about automation making a mistake that nobody catches, the answer isn’t to avoid it. It’s to decide in advance which steps need a person to check them.
Start with how the result will be used and what happens if it’s wrong. An incorrect internal label is usually easy to change, but an incorrect price sent to a client may already have shaped their expectations.
If a step needs review, give the reviewer access to the original information and a clear decision to make. For steps that run automatically, make sure the software waits for required approvals, records what happened, and alerts the person responsible when a step fails.
For each step, choose whether to automate it, use software to prepare work for someone to review, or keep it manual.
| Approach | When it fits | Example |
| Automate | Clear rules, predictable inputs, and errors that are easy to detect and correct | Create a task from a completed form |
| Assist and review | Software reduces preparation time, but the result needs checking before use | Summarize meeting notes or draft a client update |
| Keep the decision manual | The step depends on negotiation, empathy, conflicting evidence, or an exception to policy | Agree on compensation for an unhappy client |
How to choose automation software that protects your data
Before uploading business or client information to an automation tool (and especially personally identifiable information), check how the company behind it handles your data.
Once you’ve shared it, reviewing or rejecting the result won’t change the fact that the provider already has your information. Expense receipts, for example, may reveal employee travel or client relationships.
For each service you’re considering, find out:
- What you need to share: Which details, files, or conversations it needs, and what you can leave out.
- How the information is used: Whether the provider uses your information beyond carrying out the task. For AI services, check whether uploads and generated content are used to train models.
- Who can access it: People in your team, the provider, and any other companies involved in processing it. Note: A promise not to train AI on your data doesn’t establish whether the provider can read your stored information.
- What’s stored: Whether the service keeps files, conversations, or processing logs, how long it retains them, and what you can delete. You’ll find all this information in each application’s data retention policy.
- How it’s protected: What encryption covers and whether the provider holds the keys needed to read stored information. A file copied from encrypted storage into another service becomes subject to that service’s protections and practices too.
How to test your workflow automation
Running your first automation as a small pilot lets your team find problems before more work depends on it.
- Pick a low-risk task: Choose something repetitive that doesn’t involve private or confidential information and produces results that are easy to check.
- Put one person in charge: Make sure colleagues know who can pause the workflow, investigate failures, and update it when the process changes.
- Brief the people doing the work: Explain which steps now happen automatically, what’s still their responsibility, and how to report a problem.
- Test the awkward cases, not just the easy ones: Run ordinary cases alongside incomplete submissions, duplicates, and failed transfers. Check that the workflow waits for approvals and sends problems to the right person.
- Measure the results: Compare the effort involved with the original process, including the time spent reviewing outputs, correcting mistakes, and maintaining the automation.
- Expand only if it holds up: If the pilot saves work overall and quality holds up without creating extra work elsewhere, you can extend it to more tasks.
Choose a business AI assistant that’s private
Lumo is a business AI assistant that helps with summaries, comparisons, and drafts without using your conversations to train models by default. Saved conversation history is protected with zero-access encryption, so even Proton can’t read it. With appropriate human review, these protections give teams a private environment for AI assistance involving business information.
Privacy needs to carry through the rest of the workflow, too. After preparing a summary or draft, a technical colleague or IT provider can use the Proton Drive CLI for Business to automate file workflows from the command line and script file uploads, downloads, and management.
Automation should give your team more capacity while preserving the confidentiality of the information entrusted to it.
