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Just 6 days into 2026 and the AI space is as lively as ever.
What’s strange is how normalized all of this feels now.
A few years ago, the things I’m about to mention would’ve sounded bizarre.
Today? They barely register.
So let’s talk about them.
The No. 1 Twitch Streamer is AI-Made
An AI VTuber named Neuro-sama is now the most subscribed streamer on Twitch.
Not “one of the top.” Not “trending.” Number one.
She streams almost 24/7, chats with viewers, plays games, reacts and sings. And people stay.
At current subscription numbers, the channel is estimated to be making over $400,000 a month from Twitch subscriptions alone.
That’s before ads, donations, or brand deals.
This isn’t a side experiment.
It’s a full-fledged business.
Streaming was supposed to be personality-driven, human, authentic.
But turns out consistency and availability matter more for viewers.
Once an AI can deliver the output people want, the human behind it stops being essential.
The 2026 Predictions
The year started with researchers, analysts, and big AI names putting out their predictions for 2026.
Different voices.
Same conclusion.
AI won’t just assist work anymore. It’ll run it.
The broad consensus looks like this:
AI moves from tools to operators
Fewer humans inside workflows
Efficiency becomes the default
Here’s what I think: The shift isn’t about AI suddenly getting smarter.
It’s about companies finally trusting it with responsibility.
And once that happens, everything downstream changes.
Banks are Cutting the Roles That Trained People
European banks are planning to cut around 200,000 jobs over the next few years.
Why? Because AI can now handle large parts of their internal operations.
What’s important is where these cuts are happening.
- Compliance.
- Risk.
- Reporting.
- Back-office roles.
These weren’t just “boring jobs.” They were how people learned how the system worked.
You start with these jobs, you understand the rules, and then move up.
Once AI takes over that layer, the cost savings are obvious.
The long-term damage isn’t.
And banks are only starting to talk about that after committing to the cuts.
Meta is Dealing With a Different Tension
Meanwhile, Meta hired Alexander Wang, the 29-year-old founder of Scale AI, as its Chief AI Officer.
From a business point of view, it made sense.
Meta had already invested heavily and bought a 49% stake in Scale AI.
But Meta’s former Chief AI Scientist, Yann LeCun, publicly criticized the decision.
Not because Wang is young.
Because he hasn’t led a research-first AI organization.
LeCun’s concern was clear:
Meta is leaning toward “safe” AI paths
Real research is being deprioritized
Top researchers may leave
This isn’t gossip. It shows the tradeoff companies are struggling with right now.
AI as scalable infrastructure vs AI as long-term scientific progress.
Doing both is harder than most companies admit.
What This Means for You in 2026
This isn’t the year to “learn AI tools.”
That phase is over.
This year, the focus should be on:
Understanding workflows, not features
Knowing what to automate and what not to automate
Using AI as leverage, not replacement
Protecting learning paths while scaling efficiency
Because AI isn’t replacing people loudly.
It’s replacing systems quietly.
And once systems change, roles change with them.
That’s the real shift worth paying attention to this year.
- AP
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