Good news! The blank page is no longer the problem.

AI can generate 47 decent ideas, three blog drafts, nine social captions, and a suspiciously polished webinar outline before your coffee gets cold.

The new problem is deciding which of those things deserve to exist.

Because when everyone can make more content faster, judgment replaces output as the advantage.

 AI is officially table stakes. Just pull up LinkedIn or your competitor’s website. It’s getting harder to find content that’s not shaped by AI. 

→ 80% of marketers use AI for content creation
→ 75% use it for media production
→ 61% believe marketing is experiencing its biggest disruption in 20 years because of AI

So no, this is not another newsletter about whether marketing teams should use AI.

You should. You probably already are.

The better question is: What happens when everyone has access to the same leverage?

Faster production creates a new expectation: make more.

And more can be useful. But speed only helps if the work is worth publishing.

83% of marketers say AI has raised expectations for them to produce more content than ever before.

At the same time:

→ 52% believe AI has made content so easy to create that content is becoming less effective overall
→ 53% struggle to make their content stand out in an AI-saturated market

AI solved a production bottleneck. But it also created a filtering problem.

The market is getting more content. But not necessarily more content worth paying attention to. And audiences are noticing. (aren’t you?)

Yet, consumers want brands to make human-generated content their #1 priority.

Not because AI has no role. It has a huge role.

Research.
Ideation.
First drafts.
Editing.
Repurposing.
Etc.

Please, by all means, use the tools. But the final work still needs to feel like someone made a decision.

Someone chose the angle.
Someone rejected the safe version.
Someone found the sharper hook.
Someone noticed the generic sentence and killed it with fire.
Someone cared enough to ask whether this actually sounds like the brand.

That is where taste starts to matter.

Taste goes beyond visual polish (though that’s important, too). Real taste requires editorial judgement. 

The ability to know:

What is worth saying?
What feels generic?
What needs a sharper POV?
What should never have made it out of the draft folder? 

And the data backs that up. The top factors improving content effectiveness were:

→ Content relevance and quality: 64%
→ Team skills and capabilities: 54%
→ Measurement and reporting: 51%
→ Alignment with sales: 49%
→ Technology and tools: 41%

Tools matter. But they are not the whole story.

More efficient production only helps when the team still has the judgment to make the work relevant, distinct, and useful.

Otherwise, you have simply found a faster way to make more forgettable (or worse—irrelevant) things.

And in video, taste becomes especially visible.

It shows up in the hook, the framing, the story, the edit, and the decision to keep a little humanity in the final cut.

The goal isn’t to make everything cinematic. It’s to make it feel intentional.

Here’s a good example:

We made a video for HDX built around a deeply serious (sense the sarcasm here pls) historical question: What would’ve happened if Napoleon had access to the product?

The talent was a very real (very cool) human, but much of the world around him was built with AI.

AI wasn’t a shortcut. It was part of the creative idea.

The goal was brand awareness, reach, and memorability. AI helped us create a visual concept that would have been wildly impractical to produce the traditional way.

But the tool still needed a point.

The concept.
The human performance.
The tone.
The judgment about where AI added something useful.

That is the standard.

Use AI where it makes the idea better.
Not just where it makes the asset faster.

Before you publish the next AI-assisted asset, run it through five questions.
(Honestly, this is a good practice for any content.)

Can you explain the idea in one sharp sentence?

Not the topic. The point of the asset.

“AI in marketing” is a topic.
“AI made output cheaper, which makes judgment more valuable” is a point.

If the idea could belong to anyone, it’s not ready yet.

Generic content is easier than ever to make, so specificity matters more than ever.

Add:

A real example.
A sharp opinion.
A useful comparison.
A clear takeaway.

Give the audience something they could not get from the first AI-generated summary of the topic.

AI is very good at making things sound technically correct. Unfortunately, “technically correct” is usually a recipe for losing your compelling brand voice.

Ask:

Would we actually say this out loud?
Does this reflect how we think?
Is there a line only our team would write?

Use AI to accelerate the work. Don’t let it flatten your brand.

This matters even more in video. Keep the moments that make the expertise feel real:

The story.
The opinion.
The memorable phrasing.
The visible conviction.
The person behind the point.

Your audience does not need another perfectly polished asset with no pulse.

This is the most important question.

AI makes it soooo easy to create another asset. That doesn’t mean you need it.

Does this help the buyer understand something?
Does it answer a real question?
Does it strengthen the brand’s POV?
Does it support a business moment?

If not, maybe the best move is not to publish it. Taste is knowing the difference.

AI can help your team make more content. Taste decides whether any of it is worth paying attention to.