Much of the conversation around artificial intelligence focuses on what jobs AI might replace. For businesses, that framing can be distracting because the more useful question is often much narrower: what work are employees doing today that they should not have to spend their time doing?
That question came up during a recent business discussion about AI, automation, software, and growth. The conversation moved beyond the idea of simply inserting AI into existing processes and instead focused on identifying where technology could remove repetitive work while allowing employees to spend more time on judgment, customer relationships, leadership, problem-solving, and strategy.
For many businesses, that may be one of the most practical ways to think about AI.
Start by Understanding What the Work Is Supposed to Accomplish
One concept discussed during the call was the military idea of “commander’s intent.” The basic principle is that people need to understand the objective behind what they are doing, not simply the individual task they have been assigned. When people understand the intended outcome, they are better equipped to make decisions when circumstances change.
The same principle can be useful when a company is considering automation. Before asking whether a process can be automated, the business should understand why the process exists in the first place. What is the desired outcome? What information is actually needed? Who uses it? Does the process contribute to revenue, reduce risk, support a customer, or help someone make a decision?
Without that understanding, companies can end up automating inefficient processes simply because those processes already exist. Technology may make the old process faster without addressing whether there was a better way to accomplish the underlying goal.
This is one reason effective automation often begins with watching how work is actually performed rather than starting with a list of software features.
The Best Automation Opportunities Are Often Easy to Recognize
Repetitive and transactional work tends to be a natural place to look for automation opportunities. Employees may spend hours gathering information from different systems, transferring data, building routine reports, checking documents, sending predictable communications, or performing the same administrative steps every week.
The value of the employee, however, may not be in producing the report. It may be in understanding what the report means.
For example, an experienced manager might spend several hours collecting information before being able to analyze a problem. If software or AI can gather, organize, and present that information automatically, the manager can spend those hours evaluating what is happening and deciding what to do about it.
That distinction is important. Automating part of someone’s work does not necessarily mean eliminating the person’s role. In many situations, it means separating lower-value transactional work from the work that actually benefits from the employee’s experience.
AI Can Help Businesses Work Across More Information
Another area where AI can be valuable is dealing with large volumes of information spread across different sources. A project may involve contracts, specifications, emails, customer records, reports, operating procedures, and data stored in several systems. Finding a particular piece of information or understanding how several pieces relate to one another can require considerable employee time.
AI can help businesses search, compare, organize, and summarize that information much faster. What it does not automatically provide is the business judgment required to decide what the information means or what the company should do next.
A contract can be compared with another contract. A group of reports can be analyzed for differences. Customer information can be organized and patterns can be identified. However, someone still needs to determine which differences matter, what risks the company is willing to accept, how a customer relationship should be handled, or whether the organization should change direction.
The opportunity is therefore not simply to have AI make decisions. It is to reduce the amount of mechanical work required before a qualified person can make a good decision.
Some Work Becomes More Important as Automation Increases
As companies automate more transactional work, certain human skills may become more valuable rather than less valuable. Customer relationships are a good example. There is a meaningful difference between processing a customer request and understanding why an important customer is unhappy. The same is true of negotiating a contract, leading employees through a difficult change, developing a partnership, or determining how to pursue a new market.
Those activities involve context, credibility, judgment, trust, and experience. They are also exactly the kinds of activities employees have less time for when their days are consumed by administrative work.
This creates a different way to look at automation. A company does not necessarily need to ask how many people it can replace. It can ask how much more useful its existing people could become if a portion of their repetitive workload disappeared.
For a growing business, that can have a significant economic impact.
Growth Does Not Always Have to Mean Adding Headcount
Traditionally, business growth often creates a fairly predictable chain reaction. More customers lead to more transactions, those transactions create more administrative work, and eventually the company needs more employees to keep up with that work. Revenue increases, but operating costs tend to increase with it.
Automation creates an opportunity to change that relationship.
If software can handle some of the repetitive work created by additional volume, a company may be able to support more customers without increasing headcount at the same rate. That does not mean a business will never need additional employees. It means hiring can be driven more by the need for additional expertise, relationships, leadership, or productive capacity rather than by the accumulation of administrative work.
This is where the economics of AI and automation become important. A company should be able to explain what an investment is expected to change financially. Perhaps it eliminates a certain number of hours of manual work each week. Perhaps it allows one department to handle significantly more transactions. Perhaps it prevents another hire from being necessary for a period of time. In other cases, the value may come from faster customer response, fewer errors, better information, or reduced risk.
Whatever the benefit is, it should be connected to an identifiable business outcome.
Don’t Automate Something Just Because You Can
The availability of AI has created enormous enthusiasm for adding it to products and business processes. That enthusiasm can sometimes cause companies to start with the technology rather than the problem.
A more disciplined approach is to look closely at how the business operates and identify where employees are spending time on work that is repetitive, predictable, or primarily concerned with moving and organizing information. From there, the company can decide whether software, conventional automation, AI, or some combination of the three can perform that work more efficiently.
In some situations, sophisticated AI may be appropriate. In others, a relatively simple software workflow may solve the problem. The goal should not be to use the most advanced technology available. It should be to solve the business problem in a way that creates enough value to justify the investment.
The same standard should apply whether a company is considering a new AI tool, an integration between existing systems, or custom software.
Use Technology to Give People Better Work
Businesses invest a great deal of money in experienced employees and then frequently ask those employees to spend substantial portions of their day searching for information, entering data, preparing routine reports, and moving information from one system to another.
That is not necessarily the best use of either the employee or the technology available today.
A better objective is to let software handle the work that software is good at and give people more time for the work where people continue to provide the greatest value. That includes understanding customers, solving unusual problems, exercising judgment, creating strategy, building relationships, and leading other people.
AI may ultimately have its greatest impact on businesses not because it eliminates the need for people, but because it changes what businesses need their people to spend their time doing.
