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Which creative skills actually still sell now that everyone has access to AI? That's what I went looking for real data on this time. I dug up job posting numbers and freelance rate reports, and I also went back through my own 2018 portfolio, which is mostly dropshipping ad cuts made in Premiere and Filmora and Canva templates with a different product photo dropped in. It's cringe. it's not bad work, but it looks exactly like everyone else's portfolio from that era.
Inside the episode: an analysis of roughly 180 million job postings showing computer graphics and 3D roles down 33% while creative director postings stayed basically flat — same industry, completely different graph. Why London illustration agencies are signing woodblock printmakers and linocut artists right now. What happened when businesses fired their copywriters for ChatGPT in 2024 and quietly hired them back in 2025 at higher rates. And the same execution-versus-judgment split showing up, discipline by discipline, across design, writing, video, and marketing.
Then I walk through the actual audit I ran on my own portfolio this week, sorting a year of client work into two piles, and being honest about which pile most of it landed in.
RESOURCES & LINKS MENTIONED
→ Central Illustration Agency — London illustration agency now representing traditional, hands-on craft (woodblock printmaking) alongside its usual roster → IllustrationX — international illustration and animation agency, mentioned alongside CIA for signing a linocut artist
→ Bloomberry (Henley Wing Chiu) — "I analyzed 180M jobs to see what jobs AI is actually replacing today," the source behind the job-posting split→ Upwork In-Demand Skills 2026 — source of the Brand Strategy (+26%) demand figure → Upwork Future Workforce Index 2026 — source of the "34% more per hour" AI-freelancer earnings figure
→ Rob Palmer — direct-response copywriter referenced for the "fired for AI in 2024, rehired at higher rates in 2025" story 
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If this one hit close to home, hit follow on Apple Podcasts or Spotify, new episodes land every week, and this thread on career adaptation isn't done yet.
And if you want the longer written breakdown of the numbers from this episode, that'll be up on the newsletter/blog once it's live.
CHAPTERS
00:00 The cringey 2018 dropshipping ad and Canva portfolio04:08 Intro: what this episode is about06:07 The split: 180 million job postings, two different graphs08:21 Why London illustration agencies are signing woodblock printmakers09:42 The four-discipline breakdown: design, writing, video, marketing11:05 The complication: the broken ladder for junior creatives13:01 Is "taste" really a permanent moat?13:46 The copywriter who got fired for AI, then rehired at higher rates14:56 The portfolio audit: sorting a year of work into two piles17:07 Homework for you
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AI search is changing how clients find creative professionals, freelancers, designers, writers, podcast producers, photographers, and other independent creatives online. In this episode, I’m looking at how ChatGPT, Google AI Overviews, Perplexity, and other AI search tools are changing online discovery, what Generative Engine Optimization (GEO) actually means, and what you can do to improve your chances of appearing when a potential client asks AI to recommend someone with your skills. I also dig into why traditional SEO still matters, how AI decides who and what to cite, and why consistent positioning across the web is becoming increasingly important.
I went pretty deep into the research for this one because there are a lot of sweeping claims about AI replacing Google, and the actual picture is more complicated. Google still dominates search, while AI referral traffic is relatively small, but it’s growing very quickly. I also found some interesting evidence that people arriving through AI recommendations may be much more qualified than traditional search visitors. And one of the biggest surprises for me was LinkedIn: individual creators and their content are showing up in AI-generated answers far more often than I expected.
Then I get into what you can actually do about it. I explain why specific positioning tends to work better than vague marketing language, why you should describe what you do consistently across your website, LinkedIn, podcast bio, directories, and other profiles, and why third-party mentions are becoming so valuable. If you publish podcasts or videos, I also explain why transcripts matter for AI discovery. And I’ll give you a simple experiment you can run today: ask ChatGPT or Perplexity the exact question your ideal client would ask when looking for someone like you and see whether you exist in the answer at all.
RESOURCES AND LINKS MENTIONED
→ Semrush research on AI referral traffic and AI citations
→ Pew Research on Google AI Overviews and search behavior
→ BrightLocal research on AI-assisted local business discovery
→ Seer Interactive research on AI-referred traffic and conversions
→ Ahrefs research on brand mentions and AI visibility
→ KDD 2024 research on Generative Engine Optimization (GEO)
TIMESTAMPS
00:00 Can AI find you?02:56 Google still dominates, but AI search is growing03:59 How quickly ChatGPT referral traffic is increasing05:26 How AI Overviews are changing clicks07:06 Creative professionals already getting clients through ChatGPT08:45 Behance, Dribbble, LinkedIn & Upwork09:47 Why LinkedIn matters for AI discovery11:10 Why AI-referred visitors may convert better12:52 What is Generative Engine Optimization (GEO)?14:41 How AI builds a picture of who you are15:45 Reddit, LinkedIn & AI citations17:23 The importance of third-party mentions18:16 Audit your AI visibility18:37 Write a specific positioning sentence19:28 Make your audio and video content readable by AI19:54 Build third-party mentions20:44 What all of this means for creative professionals
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Why does having AI handle more of your work leave you feeling more anxious, not less? That's the real question behind this episode on AI burnout and AI anxiety for creative professionals: designers, writers, marketers, anyone whose day is work plus side projects plus a constant queue of content. I break down exactly what the stacking looked like for me: client work, my own side projects, YouTube, newsletters, and Netflix with my partner, all with zero gap in between and why the stacking itself, not any one piece of it, was the actual problem.
So last month I started sitting on my patio most nights around 10pm, thirty minutes, no phone, iced decaf or a zero sugar soda, notebook and pen mostly untouched, my cats usually trying to get in on it too. I talk through how bad I was at just sitting there the first few nights, the voice that kept telling me I should be working instead, and a 2025 Scientific Reports study on why letting your mind wander actually helps creative thinking plus the specific catch on when it works and when it doesn't.
This one's a direct follow-up to the concert episode last week, same underlying idea, opposite setup,
and it connects straight back to my freelance pricing math episode too, on deciding whether to productize, upskill, or step back from production work. If you've been feeling that low hum of overstimulation and couldn't point to why, this is for you.
RESOURCES & LINKS MENTIONED
→ Mind wandering during creative incubation predicts increases in creative performance in a writing task — McDaniel, Habibi & Kaplan, Scientific Reports (July 2025), USC Brain and Creativity Institute 
→ Previous episode: the Godsmack concert / collective effervescence episode
→ The overcommitting pattern this episode's guilt voice comes from (episode)
→ Content Overload Is Real — But Attention Spans Aren't Actually Shrinking (episode)
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If this one landed, hit follow on Apple Podcasts or Spotify so next week's episode shows up automatically.And if you want the written version of this one plus more episodes like it, the newsletter signup's will be linked soon.
TIMESTAMPS:
00:00 The small thing that changed everything01:13 The scene: patio, 10pm, iced decaf, notebook, thirty minutes02:46 Why "doing nothing" used to feel like wasted time05:15 What the ritual actually looks like, phone included07:36 Why it started: work, side projects, content, and Netflix stacked with no gaps09:40 How AI and algorithms engineer away the gaps between things10:07 The guilt voice: "I'll just finish this, then I'll chill"11:29 The research rabbit hole: default mode network and the Scientific Reports study12:40 The thread connecting this episode to the concert episode13:25 Bringing it back to your career, side hustles, and the pricing math episode15:51 The practical takeaway, the patio callback, and next week's tease
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There are experiences AI still can't replace - live music, theater, live sports, and handmade craft all resist AI replication for real psychological reasons, not just sentiment. This episode breaks down exactly why, using concepts like collective effervescence and the effort heuristic to explain what AI can generate versus what it can never actually recreate.
I went to a Godsmack concert last Sunday and for two hours I did not pull my phone out once and somewhere around the third song I felt like I was sixteen again, standing in a crowd at my first real show. I looked around and everyone near me had the exact same look on their face. Turns out there's a reason this hits different and it's not just me getting sentimental in my thirties... there's a real sociological term for it (collective effervescence, if you want to sound smart at a dinner party), plus this thing called the effort heuristic that explains why we value stuff more when we know a human actually sweated over it.
If you're a creative freelancer and your whole thing is "I deliver a fast, polished asset," you're fighting AI on AI's home turf, and that's a losing fight. There's a better move, and I get specific about what it actually looks like. Also: homework. You're picking one hobby and banning AI from it. No arguing.
RESOURCES & LINKS MENTIONED
→ Collective effervescence (Émile Durkheim) — the sociological concept behind why crowds synchronize emotionally at live events → Effort heuristic — the cognitive bias where perceived effort increases perceived value
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If you're finding this useful, hit subscribe on Apple Podcasts or Spotify so you don't miss next week's episode.
The written version of this one will be up on the blog soon — link coming, along with the newsletter signup.
TIMESTAMPS
00:00: the Godsmack concert and feeling 16 again02:28: Intro: what this show's about04:09: Why this hits different: collective effervescence, the effort heuristic, and provenance07:34: It's not just music: theater, sports, and handmade goods10:15: What this means for your creative business14:35: Callback + what's coming next week
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If you're a creative professional - a designer, writer, marketer, videographer, illustrator - using AI tools to work faster and still not seeing your rates move, this episode is probably about you. I'm following up on something I said back in June and didn't fully explain: that I'm thinking about upskilling into something closer to where client revenue actually lives. A month later, I still don't have a clean answer. But I'm thinking through it out loud, because that's what this show does.
I get into why creative professionals who use AI tools to speed up production work tend to hit a pricing ceiling that strategists don't, and it's not a mindset thing, it's structural. I talk about what direct response taught me about proximity to measurable outcomes, what AI actually amplifies in creative work (and what it can't touch), and the question I'm asking myself right now that feels different from "I should probably upskill."
This one doesn't wrap up neatly. If you're a freelance creative doing good work, using the tools, still feeling stuck, it might be worth 17 minutes of your time.
RESOURCES & LINKS MENTIONED
→ AI for Freelancers: The Math Nobody Warned You About episode
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New episodes every week - follow on Apple Podcasts or Spotify so you don't miss the follow-up when I actually have something figured out.
The written version of this episode, plus the newsletter, will be added once it's live.
TIMESTAMPS:
00:00 Following up on June's 2am episode02:26 Career arc: 2018 to now04:19 The thing I didn't clock for a long time05:21 The webinar that reframed everything07:45 Being three steps from the outcome09:23 Where AI actually fits in and where it doesn't12:07 The real risk for creative producers right now13:04 What I'm doing differently with existing clients14:38 The bigger move I'm still figuring out15:26 The question that hits different16:18 The thing to sit with before you close this app
 
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Is stock photography dead? That's the question that sent me down a rabbit hole this week... after a random Saturday spent bouncing between buying Godsmack tickets, messing with my own website, and generating about forty AI images for my blog. One of them looked exactly like something I would've paid twelve bucks for on a stock site a couple years ago. So I went and checked what's actually happening in the AI stock photography world right now, and it's messier than the headlines suggest.
There's a viral stat going around claiming stock photographer earnings collapsed 98%. I tried to find the source. Couldn't. Turns out it traces back to an unsourced SEO blog post, not real reporting. What IS real: the $3.7 billion Getty Images/Shutterstock merger just fell apart after the UK's competition regulator blocked it, Getty's stock jumped 90% off a new OpenAI licensing deal days later, and individual contributor payouts have genuinely dropped, some by 40%+. I get into where the value moved, and why it's not where you'd think.
This one also goes somewhere I didn't expect: AI-generated fashion models. Zalando, H&M, Mango, and Guess are all using synthetic models now, and the Model Alliance has real concerns about consent and diversity that are worth sitting with. If you're a creative freelancer wondering which parts of your own work are AI-vulnerable versus AI-resistant, this episode is basically a case study for that question - using someone else's industry before it's yours.
RESOURCES & LINKS MENTIONED
→ PetaPixel — coverage of the Getty/OpenAI licensing deal and stock surge 
→ PhotoWorkout — source for the $0.78/download average Shutterstock contributor earnings in 2025, down from $1+ 
→ Brutally Honest Microstock — one contributor's own earnings tracked dropping from ~$1 to ~$0.30/download after Shutterstock's tier reset 
→ Model Alliance (Sara Ziff) — advocacy group raising consent and diversity concerns around AI fashion models 
→ Model Alliance Press — coverage of the H&M AI "digital twin" models story specifically
→ New York State Fashion Workers Act — official NY Dept. of Labor page on the 2025 law requiring separate consent for AI "digital replicas" of models
TIMESTAMPS
0:00 Intro
2:59 Welcome
3:45 Getty & Shutterstock Merger
6:32 Fact-Checking the 98% Collapse Stat
9:20 Where the Value Actually Went
10:28 AI Models & Fashion Industry
12:09 What This Means for Creative Freelancers
14:09 Wrap-Up
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If you've got a minute, a review on Apple Podcasts genuinely helps more creative pros find the show. Even just a rating, you'd be doing me a solid.
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If you've ever searched "best freelance business tools" or "simple tech stack for freelancers" at eleven at night instead of doing the actual client work sitting in another tab.... well, same, and this episode's for you.
I break down the four things a service-based creative business actually needs - a website, an onboarding process, one workspace, and a real offer. And where that stack usually balloons into $300-400 a month before you've delivered a single project. Then I walk through my actual freelance tech stack, tool by tool: Netlify for the website, Tally for applications, Notion for the client portal, Slack for communication, Descript for editing, Claude and ChatGPT for drafting, Wise and PayPal for payments. This one's specifically for solo service providers, so you, maybe a VA, maybe a bookkeeper, not course businesses or teams with employees, since those come with different bottlenecks entirely.
If you've got four browser tabs open comparing project management software right now, press pause on that and press play on this instead.
RESOURCES & LINKS MENTIONED
→ Netlify — static website hosting, no plugins or maintenance 
→ Tally — free form builder used for client applications 
→ Notion — client portal and internal workspace → Slack — private client communication channel → Google Drive — client file storage → Google Calendar & Google Meet — booking and calls → Descript — primary editing, transcripts, captions → Canva — thumbnails and simple design work → Claude — writing partner and repurposing→ ChatGPT — brainstorming and image creation → Google eSignature (Google Workspace) — contracts, no separate legal platform → Wise — primary payments → PayPal — backup payments → LastPass — client password collection
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If this saved you from opening a fourth pricing tab this week, subscribe on Apple Podcasts or Spotify so next Tuesday's episode just shows up.And if you want the written version of this one plus the full tool-by-tool breakdown, I'll post it here once it's live.
CHAPTERS
00:00 – Intro02:20 – Why tool research is actually avoidance03:01 – Who this episode is (and isn't) for04:40 – The fantasy tech stack and the $400/month problem06:44 – The four things every service provider actually needs07:14 – Thing 1: a simple website08:24 – Thing 2: onboarding, the most underrated one09:36 – Thing 3: one workspace instead of six threads10:03 – Thing 4: structuring the actual offer12:41 – The two-week rule for adding new tools13:42 – My real tool stack, tool by tool16:37 – Final thought: simplicity beats automation
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This episode is a little different.
I'm answering a completely unprepared round of This or That questions that ChatGPT asked, from food, travel, fitness, and music to freelancing, creative work, money, personal projects, and the kind of creative career I actually want.
Some answers were easy. Others made me question choices I've apparently been making for years.
We get into everything from creative freedom vs. financial success and specialist vs. generalist to perfectionism, procrastination, personal projects, and whether I'd rather be a creative director or a maker.
Consider this a more personal introduction to the person behind AI for Creative Professionals.
And because this got much longer than expected, the AI edition is coming in Part 2.
TIMESTAMPS
00:00 A taste of the harder questions before you know what's going on01:32 how ChatGPT built these from my past chats02:42 Round 1 begins: food this or that06:57 Fitness & everyday life this or that10:14 Travel this or that12:56 Movies, TV & music this or that17:59 Wildcard: what she'd do if creative careers got banned tomorrow18:16 Round 2 begins: creative brain this or that26:16 Open-ended: first creative job, what I wanted to be at 10, and more28:32 Wrap-up and the part 2 AI edition tease
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If you want part two the second it's out, subscribe on Apple Podcasts or Spotify so it just shows up instead of you having to remember. And if you'd rather read than listen, the written version lands on the blog too, link's below once it's up.
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If you're a creative freelancer using AI and still not making more money, you're not imagining it — the math in fact doesn't work out the way everyone promises. This episode is the honest, unfiltered version of that problem, starting from a night I couldn't sleep doing that exact math in my head.
I'd been lying awake doing math in my head, realizing I was repeating the exact same overcommitting pattern I swore off in 2025 - saying yes to clients randomly, never actually productizing my own service even though I tell other creative professionals to do it constantly. And the math got worse from there: with everything AI has supposedly changed about how I work, I'm charging roughly the same as I was before any of it.
This one's for my editors, designers, writers, video people, social media managers - anyone whose work sits a step or two away from a client's actual revenue, which makes "just charge more" a lot harder to pull off than the advice makes it sound.
I get into why the work itself slowly gets worse when AI lets you take on more than you can actually hold, what I've started doing differently (including capping my client roster and bundling deliverables instead of taking on more people), and the harder question underneath all of it - whether the real fix is productizing, upskilling into something closer to the money, or stepping away from production work entirely.
I don't wrap this one up with a bow. But if you've had your own version of the 2am loop, I think you'll feel it here.
TIMESTAMPS
0:00 Intro
4:50 How the Overcommitting Trap Works
11:21 When the Work Itself Starts to Slip
16:29 Why "Just Charge More" Doesn't Cut It
18:27 What I'm Actually Doing About It
25:54 The Question to Sit With
26:17 Your Way Out
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If this one hit home, hit subscribe on Apple Podcasts or Spotify so the next episode lands in your feed automatically.
The written version of this plus a couple of things that didn't make it into the recording — is up on my newsletter and Substack. 
Come find me on Instagram or Substack.
If you've got a minute, a review on Apple Podcasts  helps other creative pros find the show. Even just a rating helps more than you'd think.
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I've heard some version of the same advice about five times in the last couple weeks from content coaches, creator newsletters, and other podcasters: in the age of AI, people crave authenticity, so keep your episodes messy, leave in the tangents, don't over-edit. I agree with about 70% of that. It's the other 30% I think we're taking way too far.
In this episode I get into why editing and authenticity aren't actually opposites, the difference between personality-led, entertainment-led, and utility-led podcasts (and why the "keep it raw" advice only really fits two of those three), and the four rules I actually use when I'm editing my own show. Plus the fitness podcast story that's been bugging me for years, from way before AI was even part of this conversation.
If you've ever felt like a podcast made you wait too long for the thing it promised you, this one's for you.
TIMESTAMPS
00:00 The "leave it messy" advice I've heard five times in two weeks03:37 Where this take actually comes from (a fitness podcast, years before AI)06:11 Why niche interview podcasts drift off-topic07:35 Personality-led vs. utility-led vs. entertainment-led podcasts13:16 Signifiers of authenticity vs. authenticity itself16:14 What every creative discipline already knows about constraints19:49 Four rules for editing without losing your voice
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If this got you thinking about your own line between raw and just untidy, hit subscribe on Apple or Spotify so you don't miss where this goes next.
And if you'd rather read this one than listen, the written version lands on the blog soon.
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Six AI subscriptions. Three I use regularly. That's what I found going through my own bank statement, and it's the whole reason this episode exists because collecting AI tools isn't the same thing as having an AI strategy, and I think a lot of us have basically mixed those two up.
This one's about where AI actually fits into creative work: research, ideation, production, distribution, and why spreading five tools across all four stages usually costs you more than it gives back. I walk through my own podcast workflow as the real example: what I use Claude for, where Audacity and Descript come in, and the six or more Claude skills I ended up building instead of adding more subscriptions. There's also a closet analogy in here that I didn't expect to lean on this hard, but it stuck.
If you've got a pile of AI logins and a nagging feeling that none of it's actually saving you time, this is the episode to start with.
RESOURCES & LINKS MENTIONED
→ Claude (Anthropic) – used for research, ideation, and the six custom skills for repurposing → Previous episode on podcast production workflow
→ Bango, "Rise of the AI Subscriber" (May 2026) – average AI subscriber spend and churn behavior → Lokalise, "Too Many Tools, Too Little Time" – tool-switching time cost → MIT Project NANDA, "The GenAI Divide: State of AI in Business 2025" – AI ROI findings 
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If this one hit close to home, hit subscribe on Apple Podcasts or Spotify so the next one lands automatically.
And if you've got a second, a rating on Apple Podcasts helps other creative pros find the show. I would appreciate it!
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"AI slop" isn't just a meme - it's a real design failure pattern, and it's got a 1985 ancestor most designers have never heard of. This episode breaks down the "ransom note effect," why AI image tools are heading toward smooth sameness instead of visible chaos, and what that means for anyone using AI tools for designers right now.
Okay so you know that specific visual, the AI-generated poster with the floating shapes and the busy text that almost looks designed but doesn't quite hold together? There's actually a name for that. A typography term from 1985, coined the first time professional design tools landed in untrained hands. It's called the ransom note effect, and this episode is about why we keep living through the same moment over and over with different tools.
I counted four times it's happened (there's probably more but I focused on these four): desktop publishing in the '80s, early web in the '90s, Canva in the 2010s, and now ChatGPT Image 2.0 in 2026. The difference this time is that the output is smooth enough that we're not heading into the obvious chaos phase. We're heading somewhere more like WordPress sameness: everything competent, everything identical, and way harder to spot than blinking text and mismatched fonts.
RESOURCES & LINKS MENTIONED
→ ChatGPT Image 2.0 – OpenAI's image generation tool released April 2026; renders readable text, generates matching image sets, searches the web mid-process → PageMaker – Desktop publishing software from 1985 that triggered the original ransom note effect when combined with the Macintosh and LaserWriter→ Canva – Design platform; My closest historical parallel to the current AI image moment 
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If you've felt exhausted before you've even opened an app, you're not imagining it — content overload is a real, measurable problem, and it started well before AI showed up. This episode traces it back to 2015, debunks the "humans have shorter attention spans than goldfish" myth that never had real science behind it, and gets into why AI didn't create the oversupply problem, it just stepped on the accelerator.
I pulled stats on what's happening right now: 74% of new web pages contain detectable AI-generated content, a startup is producing 3,000 AI podcast episodes a week for a dollar each, and consumer trust in AI content has dropped from 60% to 26% in three years. I also get into the attention span myth, because it turns out the whole "humans now have shorter attention spans than goldfish" thing didn't really come from any real science. People aren't broken. They just got pickier. And pickier is a very different thing to compete against.
The practical section at the end is what I'd actually want you to take away, specifically what this means if you're a creative professional making content for clients or for your own brand right now.
RESOURCES & LINKS MENTIONED
→ Ahrefs study – Analysis of nearly a million web pages measuring AI-generated content prevalence → Gartner projection – Forecast on synthetically generated content by 2026 → Nielsen survey – Research on streaming subscriber overwhelm and subscription behaviour → McKinsey research – Data on UK media consumption trends and attention plateauing → Adobe digital trends report – Survey on marketer adoption of generative AI workflows in 2026 → Inception Point AI – The startup producing 3,000 AI podcast episodes a week 
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If this resonated, hit follow on Apple Podcasts or Spotify. New episode every week.
The written version of this one, plus extra thoughts that didn't make it into the recording, is over on the newsletter. Link below.
And if you've got 30 seconds, a rating on Apple or Spotify helps new listeners find the show more than you'd think.
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Here's my actual AI-assisted podcast production workflow - no editor, no team, recorded to fully scheduled in under two hours most weeks. If you're a solo creator wondering how AI tools actually fit into a real production process (not a fantasy one), this is the unglamorous, specific version.
In this episode I walk through exactly how I do it. The tools, the order I do things in, and why that order actually matters. I talk about how I plan episodes quarterly so I'm never starting from a blank page, the 70/30 split I keep between keyword-researched episodes and the ones I just make because I feel like it, and the Claude skill I built that takes one transcript and spits out every repurposing output in a single pass.
I'm also testing the whole thing on a second podcast right now in a completely different niche. Same system, different content, different audience. If it holds up there, it's actually a system. If it only works here, it's just something I got good at through repetition, which is a different thing.
The principles at the end apply no matter what tools you're using, so those are worth sticking around for.
RESOURCES & LINKS MENTIONED
→ Audacity – Free audio recording and editing software, used for noise reduction, compression, and EQ immediately after recording → Descript – Transcript-based podcast editing software for content polish, cutting dead air and tangents, adding transitions → Podbean – Podcast hosting platform for upload, metadata, scheduling, and distribution 
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If you're a working artist trying to understand the AI copyright lawsuits actually happening right now — Disney, Midjourney, Stability AI, Andersen v. Stability... this episode breaks down what's real, what's legal precedent, and what it means for your work. I spent a night deep in r/ArtistHate and came out with the data, the court documents, and the industry reporting to back it up.
What I discovered kept me up until 3am. 26,000 artists documenting the real-time collapse of their careers, backed by hard data, court documents, and industry reporting.
WHAT YOU'LL LEARN
Survey data: 26% of illustrators already lost work to AI, 37% report decreased income (Society of Authors, 2024)
Real stories from working artists documented by tech journalist Brian Merchant
Which companies are being sued: OpenAI, Midjourney, Stability AI, Adobe, DeviantArt
Major lawsuits: Disney, Universal, and Warner Bros sue Midjourney; Andersen v. Stability AI heads to trial September 2026
Artist resistance tools: Glaze (7.5M downloads) and Nightshade (1.6M downloads)
Platform migration: How Cara grew from 40K to 650K users in one week
PRIMARY SOURCES & RESEARCH
Journalism & Reporting
Brian Merchant — “Artists are losing work, wages, and hope”
The Globe and Mail — “Lost gigs and lower pay”
Legal Coverage
NYU Journal — Andersen v. Stability AI Analysis
Georgetown Law — Disney/Universal/DreamWorks Sue Midjourney
McKool Smith Law — AI Case Updates
NPR — Bartz v. Anthropic Ruling
Technology Coverage
MIT Technology Review — “Data poisoning tool lets artists fight back”
MIT Technology Review — “AI lab waging guerrilla war”
MIT Technology Review — “2024 Innovator: Shawn Shan”
University of Cambridge — LightShed Study
Nightshade (Official Site)
Company Coverage
TechCrunch — OpenAI Ghibli Controversy
80.lv — OpenAI Calls Artist Tools “Abuse”
Benzinga — 4,700-Artist Midjourney Lawsuit
Harvard Cyberlaw — Adobe Firefly Investigation
Slate — “How DeviantArt died”
Cara (Platform) — Wikipedia
KEY STATISTICS
26% of illustrators lost work to AI
37% reported decreased income
16,000 artist names in Midjourney training
$300M Midjourney 2024 revenue (11 employees)
170M images in LAION-5B dataset
57M AI images in Adobe Stock (14%)
7.5M Glaze downloads
1.6M Nightshade downloads
40K → 650K Cara users in one week
TOOLS & RESOURCES
Artist Protection:
Glaze
Nightshade
Cara
 
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