In the AI Era, It May Be the Big Companies That Are Truly Anxious

Many people assume that in the AI era, it is small companies that are most at risk.
Quite the opposite.
Those who are truly starting to feel anxious may be the ones with:
complex processes, bloated hierarchies, and slow decision-making – the big companies.

Because AI is changing something that has not changed for decades –

"Company scale" and "productivity scale" are decoupling for the first time.

01Why Did Big Companies Used to Win?

Why did big companies used to win?
Because complex software is essentially a war of "organisational capability."
You need a large number of programmers, a large amount of communication, a large amount of management, and a large amount of coordination.
A single requirement flows layer by layer from the customer to the product manager, then to development, testing, and operations.
So the software industry in the past naturally gravitated toward "big teams."

But after AI appeared, one change has been underestimated by many:

What AI truly amplifies is not "coding speed."It is "the action capability of small teams."

In the past, a 10-person team
wanting to test a new direction
would at least need meetings, project approval, scheduling, and resource coordination.

Now, a person who understands the industry,
working with AI,
can build a prototype on the same day,
let customers try it the next day,
and start iterating on the third day.

You will find:

AI is transforming "software development" from "heavy industry" into "light industry."

What matters most here is not technology.
It is organisational structure.

02Big Companies Excel at Standardisation, but AI-Era Opportunities Come from Rapid Trial and Error

Because what big companies are best at
is often: standardisation, processisation, and risk control.
But in the AI era, many opportunities come precisely from: rapid change, rapid trial and error, and rapid iteration.
Whoever is closer to the customer,
whoever responds faster,
is more likely to survive.

Why?
Because AI has drastically compressed the "cost of trial and error."

In the past, a small industry need had no one willing to take it on.
Because development costs were too high, customer budgets too low, and it simply was not worthwhile.
But now it is different.
A small team, or even one person, can quickly produce a usable version.
So many small software tools, small utilities, and small scenarios that were previously "not worth existing" suddenly have commercial value.

This means:

The future software market will not necessarily become more and more concentrated.It may instead become more and more fragmented.

There will be a large number of:
"small and deep," "small and fast," "small and specialised" AI software teams.
They may have only three to five people.
But their understanding of a certain industry is deeper than big companies';
their response to customer problems is faster than big companies';
their product iteration speed is more aggressive than big companies'.

03From "Project Thinking" to "Continuous Co-Creation"

Many traditional software companies are still stuck in "project thinking":
sign the contract, define requirements, develop and launch, accept and deliver.

But in the AI era, a more important capability is emerging: "continuous co-creation."
Software is no longer a one-time delivery.
It is constantly evolving.

Today the customer raises a requirement,
tomorrow it can go live;
the day after, based on real usage feedback, it can be quickly adjusted.

You will find:

AI is pushing the software industry from "engineering-driven" to "feedback-driven."

Whoever can receive market feedback fastest
can complete product evolution fastest.

And in this, small companies are naturally advantaged.
Because small teams do not carry so much historical baggage.
No waiting for approvals, no cross-department coordination, no consideration of complex internal interests.
Often the boss is on the front line, and when the customer says one sentence, it can be changed the same day.
In the past, this was a "disadvantage of small companies."

But in the AI era, it may become an extremely strong competitive advantage.

04From "Resource Density" to "Cognitive Density"

The deeper question is:
In the past, the software industry competed on "resource density."
Whoever had more capital, whoever had a bigger team, was more likely to win.

But in the future, the software industry will increasingly resemble competition on "cognitive density."
Whoever understands the industry better,
whoever understands the scenario better,
whoever understands the customer's real pain points better,
can rapidly amplify their capabilities with AI.

So the people with the greatest opportunities in the future may not necessarily be the best coders.
But rather: people who understand business, understand the industry, and have long been rooted in a specific niche.
Because AI is gradually turning "development capability" into a public capability.

What truly becomes scarce begins to be:

insight, decision-making speed, industry understanding, and continuous iteration capability.

Many people have not yet realised: AI is not simply improving software development efficiency.
It is more like redefining: what kind of company is more likely to win.

In the coming years, the software industry may see more and more counterintuitive cases:

A company with dozens of people cannot beat a small team of three;a heavily funded large platform cannot outrun a vertical niche product;not because of a technology gap.But because: big companies are still waiting for processes, while small teams have already shipped their fifth version.