What Should a Growing Business Automate First?

The best process to automate first is usually not the most impressive one. It is the process that consumes too much time, creates repeated frustration, costs the business money, and can be improved without introducing unnecessary risk.

Growing businesses should start by identifying where work is repetitive, delayed, duplicated, error prone, or dependent on someone remembering the next step. Then simplify the process before deciding whether traditional automation, AI, or human judgment is the right solution.

A practical starting point is to examine five questions: what is taking too much time, where is the frustration or inefficiency, what is it costing, what has already been tried, and what would success look like?

Start with the problem, not the technology

Many automation projects begin in the wrong place.

A business sees a new AI tool, workflow platform, or agent and asks: Where can we use this?

A better question is: Where is the business losing time, money, consistency, or visibility?

Automation works best when it solves a clearly understood operational problem.

IBM defines business process automation as the use of software to automate complex and repetitive business processes, with the goal of improving day to day operations.

That means the first automation opportunity is often already visible inside the business.

It may be the task employees complain about every week. It may be the spreadsheet that requires constant updates. It may be the follow up that gets missed when someone becomes busy. It may be the same information being entered into several different systems.

The opportunity is usually not hidden. It is often simply tolerated.

Use five questions to find the right starting point

BisGentech recommends starting with five practical questions.

1. What is taking too much time?

Look for activities that happen repeatedly. Examples include:

• manually entering information from forms into another system
• creating the same reports every week
• copying information between applications
• sending routine follow up messages
• preparing recurring documents
• checking several systems to understand the status of one process

A task does not have to be difficult to be expensive. If ten minutes of repetitive work happens dozens of times each week, the total cost can become significant.

2. Where is the frustration or inefficiency?

Time alone does not tell the whole story. Some processes create unnecessary friction for employees, clients, or both. Ask:

• Where does work frequently stop?
• Where are people waiting on information?
• Where does someone need to chase another person?
• Where are mistakes common?
• Where do customers have to repeat information?
• Where does work depend heavily on one employee knowing what to do next?

These are strong automation candidates because the benefit may extend beyond labor savings. Improving the process can also improve consistency and customer experience.

3. What is the process costing?

Automation should have an economic reason. Estimate the cost of the current process. Consider:

• employee time
• rework
• missed follow up
• delayed revenue
• errors
• unnecessary subscriptions
• manual reporting
• management oversight
• customer frustration

The goal does not have to be direct labor reduction. Automation may create value by helping the business respond faster, improve consistency, reduce risk, or give employees more time for higher value work. But there should be a clear reason to make the change.

4. What have you already tried?

This question helps prevent businesses from automating a broken process.

Maybe the problem has already been addressed with a new form, a workflow rule, a different application, additional staff, or a manual checklist. Understanding what failed matters.

If the underlying process is poorly designed, adding AI may make the problem more complicated rather than solving it.

Sometimes the right answer is not automation. It may be eliminating a step. It may be removing a duplicate system. It may be clarifying responsibility. It may be standardizing how work is performed.

5. What would success look like?

Define the outcome before selecting the technology. Success might mean:

• reducing a two hour task to fifteen minutes
• eliminating duplicate data entry
• responding to new inquiries within minutes instead of hours
• reducing missed follow ups
• completing onboarding with fewer manual steps
• improving reporting accuracy
• giving the owner better visibility into the business

A measurable outcome makes it easier to determine whether the automation actually worked.

Eliminate before you automate

One of the most important automation principles is simple: Do not automate unnecessary work.

A process should be examined before technology is added. Ask:

• Does this step still need to exist?
• Is the information already available somewhere else?
• Are two systems performing the same function?
• Could the workflow be simplified?
• Is approval really required at this point?
• Is the business collecting information it never uses?

Removing unnecessary work is often more valuable than automating it. Use this BisGentech operating principle: Eliminate before you automate. Automate before you delegate. Delegate before you hire. Measure before you scale.

Not every task needs AI

Traditional automation remains the right solution for many business processes.

If a task follows clear rules and the expected outcome is predictable, a simple workflow may be safer, less expensive, and easier to maintain than an AI system. Examples include:

• moving approved form data into a CRM
• sending a confirmation message
• creating a task after a specific event
• notifying a manager when a deadline approaches
• updating a status field
• routing a document to the correct folder

AI becomes more useful when the work requires interpretation. Examples might include:

• classifying an inquiry
• summarizing a document
• reviewing information from several sources
• drafting a response for approval
• identifying patterns
• recommending a next action within defined boundaries

The distinction matters because unnecessary AI adds complexity.

Use the simplest reliable solution

The goal should not be to make a process look advanced. The goal should be to make it work better. Present this decision sequence clearly:

• Can the step be eliminated?
• If not: Can the process be simplified?
• If not: Can a rule based automation handle it reliably?
• If not: Would AI provide useful interpretation or reasoning?
• If AI is involved: What still requires human approval?

Keep people involved where consequences increase

The more important the decision, the more carefully the business should define human involvement.

NIST states that human roles and responsibilities in overseeing AI systems should be clearly defined and differentiated.

For a growing business, AI may be appropriate for preparing information or recommending an action, while a person still approves:

• pricing
• contracts
• financial commitments
• security changes
• employment decisions
• sensitive customer communications
• regulatory or compliance decisions

Automation should reduce unnecessary work without removing accountability.

A practical example

Consider a company that receives leads through its website. The current process might look like this:

• A form is submitted.
• Someone receives an email.
• The employee copies the information into the CRM.
• They determine which service the prospect may need.
• They create a follow up task.
• They send a standard response.
• They schedule a reminder.
• Later, they manually prepare information for the sales conversation.

That workflow contains several automation opportunities. Form information can move into the CRM automatically. A workflow can create the task. Approved communication can be sent automatically. AI may help classify the inquiry or summarize the information. A person can review the opportunity before making a pricing or service commitment.

The business does not need to automate everything at once. It can automate the predictable parts first and add intelligence where it creates additional value.

How to prioritize multiple automation opportunities

The strongest first candidates usually combine high frequency, meaningful cost or frustration, and low to moderate implementation risk.

Measure before expanding

An automation should not be considered successful just because it runs. Measure the process before and after implementation. Useful measures might include:

• time per transaction
• number of manual steps
• number of errors
• missed deadlines
• response time
• employee involvement
• customer complaints
• cost per process
• revenue impact

Then decide whether to improve, expand, or stop the automation. This is particularly important with AI because systems can appear useful while quietly adding review work, risk, or complexity.

The best first automation is usually boring

The highest value automation is often not a sophisticated AI agent.

It may be removing duplicate entry. It may be automatically creating the next task. It may be connecting two systems that employees currently update manually. It may be ensuring every new inquiry receives the right follow up.

Those changes are not flashy. They are useful. Useful automation is what creates the foundation for more advanced AI enabled operations later.

Key Takeaways

• •Start with an operational problem, not an AI tool.
• •Look for repeated work, frustration, cost, delays, errors, and missed follow up.
• •Simplify or eliminate unnecessary work before automating it.
• •Use traditional automation when rules are predictable.
• •Use AI when interpretation adds meaningful value.
• •Keep human approval where decisions carry greater consequences.
• •Measure the result before expanding the automation.

Sources and References

1. IBM — What Is Business Process Automation? (source)
2. National Institute of Standards and Technology — Artificial Intelligence Risk Management Framework (source)
3. NIST AI RMF — Human AI Interaction (source)
4. NIST AI RMF Playbook — Govern (source)

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