AI agents may soon surpass people as primary application users

Accenture report: By 2030, autonomous agents — not people — will be the “primary users of most enterprises’ internal digital systems.

By 2032, “interacting with agents surpasses apps in average consumer time spent on smart devices.”

“A ‘binary big bang’ occurred when AI foundation models cracked the natural language barrier.”

Pretty soon we’ll have AI watching movies for us and we’ll have them read us their summaries

I laugh at these articles. This is complete and utter BS. AI cannot be copyrighted, because all AI is derivative from other people’s works. The court has stated this, so it’s not my opinion. AI cannot write anything new, just derive patterns from existing code, and write something similar. It’s not ground breaking, it’s not original thought. It’s just large data with large computing. If anything, AI would be able to eliminate CEO’s, and their outrageous pay. In fact a magic 8 ball is just as good for a CEO.

I got into an argument with my first bot on reddit the other day.

I consider myself a smart person and it’s frankly horrifying that it can do what it does. It wasn’t until it said something kind of dumb that I looked at the profile and say it had a thousand comments in 3 days all on political topics.

That was the only proof I had I wasn’t arguing with a real brainwashed idiot who is good with words.

This is already a thing. It’s called the Dead Internet Theory. It’s likely already the case that a number of platforms have an outsized number of bots.

Let me give an example of how this outcome CAN (emphasis on can) be a good thing:

Example: An analyst at work, needs to analyze information and come to a conclusion, so that they may act on that conclusion. They take the first piece of information, and input it with some parameters into app A. Based on the outcome they change some parameters and run it again. Based on that, they go to a different screen and input the new information. That output is then taken into app B and follows a similar pattern. After a few hours of doing this between a few core apps, the analysts has finished analyzing the information and can now write recommendations based on the outputs received through following the above process. It is a highly manual task with a lot of steps, but the most valuable part of it is at the end where the analyst actually gets to think about the information uncovered and provide insightful recommendations.

Introducing an AI agent into the process, that is able to learn all of the above highly manual steps, and repeat them so that the only thing that the analyst does is get all of the analysis and think about what insightful recommendations can be made.
In this scenario, the AI agent becomes the primary “user” and will spend a lot more time interacting with apps than the analyst. It is a good outcome, where the analyst’s time is spent on the high value part of the task.

In general, AI agent can be used to help humans scale – meaning, they help humans do more with the same amount of time. They become the primary users of apps, because humans spend more time thinking and less time clicking. That is a good outcome.

Note that this isn’t a scenario like Meta (or insert any company that is generating shareholder value that maybe at some point will generate value for consumers), where AI agent are performing tasks that don’t actually provide any REAL value to humans (like interacting with them on IGFB for the sole intent of engagement).

So I’m not saying it will only be good, but it CAN be good.