Artificial intelligence · Productivity

Who Gets the Time AI Saves?

3 min read

Updated

The value of faster work depends on who gets the time saved and what they can do with it. AI can accelerate an individual task. What happens afterward is still a matter of agreements within the company. Without them, the word efficiency can conceal very different expectations.

On a presentation slide, the story is straightforward. A task used to take longer; now it takes less time. The difference is colored green. The technology has done well, and we can move to the next slide. The working day is less straightforward. The opening may be filled by another task, or by a meeting about how many more tasks should now be possible.

It is reasonable for a company investing in tools to expect better results. Producing more without expanding the team is an understandable goal. As an engineer, I want that goal stated explicitly so we can discuss whether the implementation supports it. Confusion begins when an employee is promised relief while their manager understands the same promise as room for additional work.

Consider someone who prepares reports. AI helps them produce a draft faster, and, after checking the result, there is still a real saving. They could examine the data more closely or work through outstanding requests. The team could also agree that they will finish work on time. Each outcome has value. Each requires a different decision about how work is organized.

A thorough review needs a place in the schedule. Additional requests need priorities. If the goal was to reduce overtime, every available opening cannot become an invitation to add an urgent task. Otherwise, the technical improvement will happen while the outcome promised to the employee remains on the slide.

The shape of the time saved matters too. A few minutes between messages and meetings may never become an opportunity to think. Working through a difficult problem takes a sufficiently long stretch without constant interruptions. Faster small tasks do not automatically create that stretch. The schedule may need to change as well.

Before automating, I would ask what opportunity we want to create. Do we want customers to receive answers sooner? Does the team need more time to examine difficult decisions? Naming the desired outcome tells us what to look for. It can also reveal work that must change alongside the tool if the expected benefit is to become possible.

When a customer is waiting, for example, it helps to follow the entire request. Drafting an email faster makes little difference if approval still accounts for most of the delay. If the goal is quality, the team needs to agree on the review process. A quicker draft tells us very little about the number of errors in the final document.

Giving someone discretion over some of the time can be particularly difficult. An unfilled slot is visible immediately. The value of thinking carefully may appear later. A manager who wants the team to have more autonomy has to tolerate some of that uncertainty. Filling every minute is easier than explaining why time has been left available.

I want efficiency to have an identifiable beneficiary. That could be a customer who receives an answer sooner or a business that handles more work. It could also be a specialist whose regular evening overtime ends. These interests sometimes coincide and sometimes need negotiation. The technology will not make that agreement for the people involved.

That is why I want a discussion of time savings to finish with the words, 'Because of this, we will be able to…' The rest of the sentence should describe a change in people's working lives or in the company's results. Then we have something meaningful to evaluate, and the time saved has a purpose.

Engineer, CTO and product operator. Writing about AI, teams and the responsibility of making things.