The perception trap 🚨

Hello marketers. Welcome to AI Marketing School, where we dish out the latest and greatest in AI-powered marketing.

In this week’s issue:

• The Stack: Turn blogs into videos/ads

• AI Marketing Update: AI marketing perception and how to crack it

• Consultant’s Corner: Top AI marketing events this year

Onwards!

THE STACK

📹 Quickads.ai — Scalable video ads from your blog

If you’re running paid, building a content engine, or just trying to keep up with the short-form grind — Quickads.ai is one of the coolest tools I’ve seen lately. I have no affiliation with them, and this is not a paid ad. 

At its core, Quickads is an AI-powered ad creation platform. It helps you generate short, polished, performance-style videos without the usual production bottlenecks. Just drop in your content, and the tool will turn it into high-performing ad creative.

It’s especially useful for e-commerce, coaches, B2B content marketers, and UGC creators looking to scale faceless videos. Think: Instagram reels, TikTok-style ads, YouTube Shorts, explainer videos.

The standout for me is the blog-to-video generator. 

Paste in a blog post from a URL, and Quickads uses AI to summarize the core message, pull out the main points, and translate them into a video script.

From there, it builds out a full video using its massive stock library (16M+ assets), automatic scene generation, dynamic text overlays, transitions, and pacing — all optimized for short-form.

I tried it with a blog on accounting – specifically, changes to electric vehicle taxation. It did a really good job of pulling out key facts from the blog and narrating them over decent stock video. 

A really easy way to turn blogs into vids you can post on TikTok, Insta, etc, and push traffic to a link in bio. For the time it takes (literally about 15 minutes), I thought it was excellent. 

You can choose from voiceover styles (29+ languages, accents, tones), adjust the layout and visuals, and even fine-tune the script if needed. It’s incredibly intuitive.

The result feels more like a native social video than a stiff, repurposed blog — which is kind of the dream when you’re repackaging content for reach.

The biggest upside: you can now turn SEO-driven content into short-form social video at scale.

It does take some practice. You’ll also need to edit the auto-generated video somewhat to brand it as your own:

You can see here how I added a final frame with a placeholder logo.

You could add contact details, social handles, etc., to this frame, along with a narrated CTA.

Overall, this is a first-class tool for repurposing content for short form.

You may not achieve picture-perfect results. But you don’t need them to get content out and improve reach.

AI MARKETING UPDATE

Putting the human in AI marketing

Companies are rushing to employ people with ‘AI skills’ – which often means proficiency with generative AI tools. 

They’re then rushing to use those skills to push out AI content, maximizing efficiency and productivity.

Three recent key studies show the force behind this:

• LinkedIn just dropped their Marketing Skills on the Rise data for 2025, and AI literacy tops the list as the #1 marketing skill in demand. Nearly 60% of marketers are already using AI in their jobs, and 54% believe it will "significantly impact" how they work within the next year.

• An eMarketer report from days ago confirms this trend is particularly strong in B2B marketing. A November 2024 Madison Logic survey found 60% of marketers plan to invest more in AI tools this year across all areas of marketing. 

• The latest Content Marketing Institute survey revealed that more than half of B2B content marketers plan to prioritize AI-powered automation in 2025. 

The message from the industry is clear: learn AI or get left behind.

But the question then becomes, what is the impact of mass AI-ification of marketing, advertising, etc, on customers and buyers — those who truly matter?

Can companies bank on using AI to automate work and shape their output while maintaining the same quality?

What about public perception of their brand, their products?

We need to look deeper to answer those questions to strike the right balance and channel AI’s benefits to where they have the best impacts.  

The AI perception paradox 🤔

Marketers must understand how people perceive AI-created content if we're going to make smart decisions about where and how to deploy the technology.

I’ve been looking at some interesting recent research and what it can tell us:

The MIT marketing content study (March 2023)

This study is a really interesting one. MIT researchers tested how 1,200 participants evaluated marketing content created through four different methods: human-only, AI-only, human editing AI, and AI editing human. 

When people didn't know the creator, they rated AI-generated content higher than human-created content. But when told the source, ratings for AI content dropped significantly.

Key takeaways:

• AI content isn't inherently worse – it's about perception

• Human favoritism is strong

• AI content flies under the radar despite that

Here, the impact of AI’s use clearly depends on the consumer.

Ask: are your readers likely to know if you’re using AI to write content?

If yes, will they be sympathetic or understanding? Or might they think, ‘That’s pretty lazy’ or ‘This isn’t good quality.’ 

The cognitive research art study (July 2023)

This study showed 149 participants the same AI-generated paintings but randomly labeled some as "Human-created" and others as "AI-created."

They found people judge supposedly AI-created art much more harshly when rating profundity and worth, while the gap was much smaller for basic aesthetic judgments like beauty and liking.

Key takeaways:

• AI works fine for creating visually pleasing content

• Human touch matters more for deeper emotional connections

• AI images essentially lack depth; that’s fine when they serve a mostly practical purpose

This shows that, for really high-value marketing efforts, AI imagery could be worth swerving unless you have a specific plan for using it appropriately.

We’ve seen this in action, with Coca-Cola and Google getting blasted for using AI in their ads. Others, such as Atera, succeeded by being upfront and/or marketing to an AI-aware audience. 

The Bynder consumer detection study (April 2024)

This Bynder study showed 2,000 consumers two articles – one written by ChatGPT and one by a human copywriter – both with the same brief: "Write 300 words on how to clean your car." 

Half of the consumers correctly identified the AI-written piece.

Interestingly, 56% preferred the AI version when not told which was which, yet 52% said they become less engaged when they suspect content is AI-generated.

Key takeaways:

• Consumers are getting better at spotting AI content; some become disengaged when they clock on

• The study also found 26% think brands using AI content are "impersonal"

• And 20% think brands using AI content are "lazy"

This ties in with the above. AI content works; it looks ‘good’ – probably gratifying and readable – but essentially lacks that final piece of quality, thus risking negative perception when used poorly. 

The Bowdoin College Story Investment Study (March 2025)

This month, economists and language researchers at Bowdoin College offered 650 participants $3.50 to read and assess a short story.

Half were told it was AI-generated (which it was), while half were told it was written by a human author (it wasn't). 

When asked to rate the story's quality, the "AI-aware" group judged it significantly more harshly across metrics like predictability, authenticity, and emotional engagement.

However, when given the opportunity to spend part of their compensation or invest extra time to finish reading the story, both groups invested identical amounts.

Even more revealing, when asked afterwards, 40% of participants claimed they would have paid less for the story had they known it was AI-generated – contradicting their actual behaviour.

Key takeaways:

• People say they value human-created content more highly than AI content

• When it comes to actual consumption behavior, they seem to treat both similarly

• Here, content quality ultimately matters more than the perceived origin

Again this shows — if people know your stuff is AI-generated for sure, there might be a risk of disengagement,

BUT, it also shows that, well, people don’t really care – even if they say they do.

The sweet spot 🎯

All in all, it’s clear that understanding how your audience perceives any AI use — content or otherwise — is hugely important.

We should acknowledge that all of this is subject to change going forward. But from my experience, the capabilities of many chatbots and most image generators have plateaued quite considerably.

Based on all this research, here's how to build effective AI-human collaboration:

1. Reimagine workflows, don't just divide them: Instead of having humans simply check AI work, rethink how the entire creative process can be transformed.

2. Use AI as the creative multiplier: Let AI generate options, variations, and first drafts that humans can refine and inject with emotional depth.

3. Keep the human touch visible: Since people value the human element, make sure your audience can feel the human creativity behind your content.

4. Match collaboration methods to content goals: Basic info? Let AI lead. Emotional brand stories? Humans should guide while AI supports.

5. Test different collaborative approaches: There's no one-size-fits-all solution, so experiment to find what works for your specific content.

The winners will be those who develop thoughtful collaboration models where humans and AI each contribute what they do best. So yes, upskill on AI tools – but focus equally on mastering the art of effective collaboration.

CONSULTANT’S CORNER

🗓️ Recommended AI marketing events

Whether you’re building with AI, leading a marketing team, or just trying to stay sharp in a fast-moving space, events are still one of the best ways to plug in.

Great events do more than just deliver content — they give you context. You get to see what other teams are testing, what’s actually working, and where the market is headed.

They’re also one of the few places where you can meet like-minded people, talk shop with folks solving the same problems, and build a network that isn’t purely algorithmic!

Some top events to check out:

•  AI Agents Summit (Virtual) — September 18–19, 2025: Laser-focused on AI agents, copilots, and autonomous systems. If you're experimenting with automating parts of your marketing workflow or interested in agent-based design, this one’s worth attending.

• AI for Marketers Summit (Virtual) — November 13–14, 2025: Created specifically for marketing professionals. From prompt engineering to campaign automation, it’s a practical look at how AI is being used right now in real teams.

• Data + AI Summit (San Francisco) — June 9–12, 2025: Hosted by Databricks, there’s plenty of marketing relevance here — especially around LLM workflows, AI tooling, and future-proofing your stack.

• Ai4 2025 (Las Vegas) — August 11–13, 2025: A big-picture AI conference covering finance, healthcare, retail, marketing, and more.

Hope you enjoyed this week’s issue. If you missed the last newsletter, you can read it here.

If you found it useful, please recommend it to a friend or colleague.

Until next time. Happy marketing.

—The AI Marketer