Is Generative AI Art Disrupting Creative Industries?

I was sat in a coffee shop the other day having my lunch when two guys next to me started talking about AI in modelling agencies – using AI-generated people to show off clothes and products. Then they moved on to whether AI is disrupting creative industries as a whole. Naturally, my ears pricked up.

I’m a generative artist. I use AI daily, along with other tools, to create my work. So I’ve got a few thoughts. This is my take on it, and honestly, I’d love to hear other people’s opinions too.

My opinion? Generative AI is disruptive, but not in a simple “good” or “bad” way. The real disruption isn’t “AI art” itself – it’s the speed, the scale and the mindset it encourages. Used well, it’s another form of generative art that can actually open doors for creatives. Used badly, it floods the market with low-effort rubbish, undercuts craft and makes clients think real creative work is just pressing a button.

• AI is a tool, not a replacement for artistic thinking.
• The biggest disruption is mass-produced, low-quality output and the whole get-rich-quick mentality around it.
• Skilled creatives who adapt their workflow to AI are still essential.

Generative AI is just the latest chapter in generative art

Generative art didn’t suddenly appear the day text-to-image AI went viral. Artists have been playing with systems, rules, chance and code for decades. Plotter drawings, software-based installations, procedural visuals in games – that’s all generative art.

Generative AI is basically a newer, more accessible branch of the same tree. Instead of writing your own code, you tap into a model that’s already learned from a huge dataset. You still make choices: prompts, references, iterations, edits, composition, colour, how you finish the image and where it ends up.

The big difference now is the barrier to entry. You don’t need to code or build your own tool. You can type a sentence and get an image. That’s where disruption really starts: not because generative art is new, but because almost anyone can suddenly generate something in seconds.

Where the real disruption is: speed, scale and sameness

When people say “Generative AI is disrupting creative industries”, they often jump straight to “AI will take all the jobs”. In reality, what I see most at the moment looks like this:

• Mass-produced, low-quality designs churned out in minutes.
• Template-driven tools that make everything look the same.
• Clients and customers seeing “AI art” everywhere and assuming that’s what the whole industry is now.

The Poundland tote bag problem

Here’s a real example from my life: AI-generated tote bags in a UK chain called Poundland. I was in the shop the other day having a look around when my girlfriend spotted some tote bags. Naturally, given our line of work, we were interested in the designs and curious about what they’re selling.

We looked closer and the designs were poor: distorted fingers, odd joints, the classic AI nonsense. And yet it still ended up on the shelf, and to be honest, people are probably buying them.

For me, this is disruption. Not because AI was involved, but because nobody cared enough to catch the error. Speed and cheapness were more important than quality control. The result is mass-produced rubbish that says, “This is what AI art looks like,” which drags down public perception of generative work and illustration in general.

Accessibility vs low quality: two sides of the same coin

One of the strongest arguments in favour of generative AI is accessibility. You don’t need years of training to start experimenting visually. People who struggle with drawing or traditional tools can suddenly explore ideas, styles and compositions they’d never have reached before. That’s genuinely powerful.

But accessibility cuts both ways. When anyone can make an image in seconds, you get:

• More people exploring creativity for the first time (which is great).
• A lot more low-effort content flooding marketplaces and social feeds (not great).

The tech itself isn’t “disruptive” in a moral sense. It doesn’t care if you’re making meaningful, carefully edited work or ten thousand near-identical posters. The disruption comes from how people choose to use the tool and what platforms reward.

From the outside, it can all blur together. If you’re scrolling Etsy or print-on-demand sites, it’s not obvious which pieces were crafted, refined, edited in Photoshop and proofed for print, and which were literally a one-click output uploaded at 3am.

Can generative AI actually replace an artist?

For me, the answer is no.

The thing about art is that it lives in perception and emotion. A real artist – people like my sister, for example, who specialises in pencil work – has a level of pride in every pencil stroke or brush stroke. They draw things they like and things they feel. There’s time spent, care taken and a personal connection to the subject. That’s not something you just swap out for a text box.

If you’re curious, her work is here: EmeliaArtUK on Etsy. It’s a good example of what I mean by human touch and intention.

Yes, some people will buy the Poundland tote bag, and that’s fine – those people have different priorities. But there will always be a place for real art made with time, skill and feeling.

Generative AI has also given other people the chance to become artists in their own way. When the dust settles and the hype calms down, what should be left is a new branch of art: work made with AI, but still grounded in meaning, effort and a human guiding hand. That’s the space I’m trying to sit in with my own generative images.

Style vs substance

Generative models are very good at mimicking style, especially if you know how to guide them. You can get something that “looks like” a certain genre, era or artist pretty quickly.

Substance is harder. Nuanced emotion, lived experience, specific cultural references, subtle humour – all of that is much harder to capture reliably with one prompt. You still need a person deciding what matters.

In practice, most artists using AI seriously are not typing one sentence, hitting generate and posting the first image. They’re usually:

• Iterating on prompts to refine composition and structure.
• Testing different lighting, angles and crops.
• Exporting images and editing them heavily in tools like Photoshop.
• Cleaning artefacts, fixing anatomy, adjusting colour and contrast.
• Preparing files so they’re actually print-ready, not just pretty on screen.

That’s creative work. It might look different from traditional painting or illustration, but it still takes decisions, skill and time.

The invisible work: from “cool image” to finished piece

There’s also a big gap between something that looks good as a phone wallpaper and something that works as a high-quality print or client-ready asset. Resolution, aspect ratio, colour profiles, text integration, scaling, retouching – none of that magically happens just because an AI model spat out an image.

When people say AI art is “just pressing a button”, they’re usually reacting to the laziest examples. When clients assume “AI makes it easy”, they often underestimate how much work still goes into getting a professional result.

Platforms and templates: when everything starts to look the same

Another big factor for me isn’t just the AI models, but the platforms built around them. Design tools that bundle templates, fonts and AI elements in one click are great for beginners, but they also make entire marketplaces feel samey and unintentional.

If every shop on a marketplace uses the same trending templates, fonts and AI styles, you end up with an endless scroll of “almost identical” products. That’s not only a technology problem; it’s also a taste and effort problem. But generative tools make it very easy to coast on the default look instead of digging deeper into your own style.

Then there’s the rise of people selling AI prompts that clearly haven’t been tested in a real workflow. If you’ve ever bought a prompt written purely by a language model with no artistic experience behind it, you’ll know the pain – it sounds clever, but it doesn’t reliably generate usable, repeatable results.

This all feeds into the idea that AI is “cheap and lazy”. Not because the tech can’t be used well, but because people are monetising the fastest, lowest-effort version of it as a get-rich-quick scheme.

So, is Generative AI disrupting creative industries?

Short answer: yes. But it’s mostly disrupting how work is valued, produced and perceived, rather than instantly replacing every creative professional overnight.

Here’s what that disruption actually looks like day to day:

• Clients expecting work to be faster and cheaper because “AI does most of it, right?”.
• Having to explain your process more because of negative social opinion around AI art.
• Feeds and marketplaces full of low-effort AI designs, making thoughtful, high-quality work harder to find.
• Real generative artists constantly pushing back against the idea that all AI art is lazy, soulless or “cheating”.
• Physical artists and makers struggling to stay visible next to thousands of copy-paste AI listings.

If you’re already a generative artist, you know the skill is in how you guide the tools: how you iterate, how you interpret, how you edit, how you bring your own taste and references into the work. Generative AI disrupting creative industries doesn’t mean the end of human creativity; it just widens the gap between low-effort output and intentional work – and that includes AI-based work.

How to use AI without losing your artistic soul

1. Treat AI as a sketchbook, not a factory

Use AI for ideas, rough compositions and visual exploration. Then take the good stuff into your usual tools to refine, redraw, repaint or collage. Let it speed up the early stages, not replace the whole process.

2. Build your own visual language

Instead of chasing whatever style is trending in AI communities, put time into a consistent aesthetic. That might mean a specific colour palette, composition style, subject matter or a particular way of mixing AI with drawing, photography or painting.

3. Show your workflow

Clients and customers usually have no idea what goes into a finished piece. Sharing before/after shots, process clips or breakdowns of how you go from prompt to print-ready artwork helps people see the value you add beyond the raw AI output.

4. Set your own standards for quality

Just because you can generate ten images in a minute doesn’t mean you should use all of them. Be ruthless. Check hands, faces, text, perspective, lighting. If something looks slightly off now, it’ll look even worse printed big.

5. Keep improving your non-AI skills

Whether it’s Photoshop, illustration software, 3D tools or traditional media, your non-AI skills matter more than ever. They’re what turn “interesting AI output” into finished, polished work that actually stands out in a sea of quick prints and templates.

That’s all for now

Generative AI isn’t going anywhere, and neither are artists. The tools will keep improving. The real question for creative industries isn’t “How do we stop this?” but “How do we hold a line on quality, originality and ethics while using these tools in a way that actually serves the work?”

If you work in art, design or any visual field, you don’t have to pick a side between “traditional” and “AI-only”. You can build a hybrid workflow that keeps your eye, your taste and your standards at the centre, and lets the machine handle the boring parts.

I’m Jack, the founder of CITTRA Collective, and I’m a generative AI artist. I use AI tools to create most of my base images, then take them into other software to edit, refine and get them print-ready. Honestly, I’d never have been able to bring CITTRA Collective to life without this tech – but I’m also feeling the disruption we’ve talked about here.

At CITTRA, we make art in a mix of styles, both traditional and non-traditional. We pull ideas from travel, culture, history and everyday life, and use that as the backbone for modern, contemporary pieces. AI is part of the process, but it’s not the whole story – the meaning still comes from the people behind it.