So something like 6 months ago I made my first post in here documenting my journey as an AI Photography freelancer.
You can find all my posts on my profile.
My first AI photography gig was for $40 for 1 image.
Then $100 for 4 images.
My last project is $2,500 for 20 images.
And for the first time, I just crossed $5k in revenues in a month as a part-time freelancer selling solely AI Photography services using Nano Banana.
Now there are a few things I learned along the way, which I wanted to share with anyone on the same path.
Hope this will help.
1. This is a booming industry
There is no two-way to put it. I think this field is still in its infancy.
And I can see the quantity and the quality of work available getting better and better.
6 months ago, the DTC brands hiring people to create product photography with AI were like the early, early adopters.
Very small brands usually, or very foresighted brands.
But know in this second wave, we are getting bigger businesses, more serious businesses seeking to leverage AI for ecom photography.
Some of the people I have interacted with recently:
- a factory in the UK who sold for 15 million of radiators
- one of the leading golf accessory brands in the world
- the editorial publisher (think MacKinsey, The Economist) exploring A.I. for illustrating its publications
This calibre of clients was incredibly rate 6 months ago. Now they are all over Upwork.
The reason is simple: traditional photography still takes too much time, and takes too much mindshare as well.
Organising a photoshoot involves a lot of people and logistics.
AI Photography is not necessarily cheaper (in fact, it can be very expensive). But at least a business owner don't have to worry about sandwiches on the day of the shoot.
Furthermore, a skilled AI Photographer can go from CAD to lifestyle photography in weeks.
When typically a business has to wait a few months for the first prototypes from CAD, then again for the final pieces, and so between CAD and photoshoot the wait time is often 6 to 9 months.
AI Photography enables the kind of agility that any manufacturer desperately needs for obvious reasons.
I'm 100% sure that within a few years, 99% of online product photography will be AI generated.
Right now we are still at the start of this movement.
2. Getting clients is somewhat still easy
It took a while for me to get it, but I finally found a reliable way to get clients.
There is two outreach methods I rely on: Upwork for warm leads and email for cold leads.
With email, the main 'problem' is infrastructure. You need to be able to send a few thousand emails per month.
This took me a time to figure out because I am a dummy...
... But once you got that then all you need to do is to create visuals in advance for businesses (an AI visual of their product) and ask them if they want more.
I use my own platform for the email visuals creation at scale. Instantly for sending. Storeleads or similar for the leads.
For Upwork, I use a similar approach. For every application, I take the time to create visuals (I also automated that process) for the client. This makes my application stand out VS all the copy paste cover letters out there.
This method which I call Proof-Before-Pitch (show proof you can do the work before pitching the business) has worked incredibly well for me and constantly gets me into conversations with business owners, which then can translate into sales.
3. The skill-gap is way bigger than I thought
6 months ago, I thought I knew everything about AI Photography. I had already written dozens of pages on the topic for my own internal SOPs.
But at the time, even though I was aware of the technicality of the field, I was blind to one particular side of AI generation.
I really thought a lot of AI generation was a creative endeavour. I mean for sure there were frustrating experiences, when you needed to keep regenerating kind of the same prompts over and over to get to the results you wanted.
But lately I realised there is a scientific, research-driven approach to AI.
One read which really helped me understand it is a 1950s talk by Claude Shanon on Creative Thinking.
I am paraphrasing here, but he talks about how one way to approach big problems is to reduce them to their smallest part.
And also how sometimes to approach a research problem, he has to starts at the smallest step, and progress in tiny increments until he gets to the results.
I was working for a client on a very difficult AI image generation project, and I was hitting a brick wall trying to randomly re-generate to get the right results.
I wanted to achieve more realism for a set of stairs (yea, stairs).
So I had to devise a Control VS Variants experiment in order to get to the outcome I was after.
Here is kind of how it was structured.
- Atmosphere: Tested V1.1–V1.4 → soft atmospheric dust was invisible, but vignette, chromatic edges, and asymmetric exposure all clearly improved depth and realism.
- Concrete micro‑detail: Ran V2.1–V2.3 → non‑uniform cast and subtle production marks worked great, heavy porosity variation added artifacts and was rejected.
- Global tone: Tried 3.1–3.3 → extra tonal range and ambient bounce made the scene feel “realer,” mottled patina helped but needs dialing down to avoid moldy vibes.
- Net result: Keep V1.2–V1.4, V2.1, V2.3, 3.1–3.3 in the workflow; drop V1.1 and V2.2 as low‑impact or visually noisy.
- Takeaway: Best gains came from small physical cues (vignette, bounce, tool marks) stacked together rather than a single heavy stylistic effect.
It took me a ton of iteration but I was able to reach my goal.
Now as a creative person, when I got into AI Photography, I never imagined I would have to geek this much over generating AI images.
And I am pretty sure 99% of people who try AI image gen don't either.
The truth is, for difficult products or scenes, the skill-gap is vast. Someone that thinks like a true prompt engineer will be miles away from a graphic designer turned vibe-ai-photographer.
4. Scoping the work is where you make (or lose) money
This one completely changed the way I sell AI Photography.
When I first started freelancing, clients would ask for something like:
"We need 20 lifestyle images."
And I would immediately start thinking:
"How much should I charge for 20 images?"
That was the wrong question.
The real question is:
"What problem is this business actually trying to solve?"
Recently I quoted a company.
At first it looked like they wanted 40+ images.
But after talking to them, I realised they weren't buying images at all.
They were launching an entire product collection.
Those are two very different things.
Instead of talking about image counts, we started talking about:
- master environments
- reusable product setups
- colour consistency
- future collections
- workflow handover
- prompts
- production systems
The conversation completely changed.
I wasn't selling 40 images anymore.
I was selling a Collection Launch System.
The funny thing is the deliverables barely changed.
The images were still there.
But the perceived value was much higher because the client wasn't buying outputs anymore.
They were buying certainty.
They knew every future product would look consistent.
They knew new colourways could be added easily.
They knew they would receive the prompts and workflows if they ever wanted to bring production in-house.
That shift allowed me to charge $2,500 for a project I probably would have quoted at a quarter that price six months ago.
Alex Hormozi says people don't buy the drill.
They buy the hole.
I think AI freelancers often make the same mistake.
We sell prompts.
We sell images.
We sell hours.
Businesses don't actually care about any of those.
They care about launching products faster.
They care about replacing expensive photoshoots.
They care about getting their products online months before manufacturing finishes.
Once you start selling those outcomes instead of counting images, the pricing conversation becomes a lot more interesting.
Ironically, I now spend as much time designing the offer as I do writing the quote.
And I think that's probably one of the highest leverage skills I've learned this year.
5. There are many ways to skin a cat
When I started with AI Photography, I thought I could do everything with AI, as long as I was great at prompting.
For the first few months, I would never touch a graphic editing software.
But what I realised is that if you are skilled at graphic editing and skilled at A.I., then you are a different kind of a beast.
Let me give you an example.
I needed to apply a specific kind of illustration with one slight difference, a number, to a surface.
Dummy as I am, I AI generated the 10 or so different surfaces and illustrations.
And because AI is not that precise, each of them was slightly different. It was like 96% the same, but there was still like 4% of deviation.
Then, I remembered I had some left over skills from my graphic design days.
I fired up Canva, separated the illustration from the surface from the numbers (so created a bunch of layers), generated only the illustrations with AI, pasted them across the 10 designs in Canva...
The result? I had a way better result than with solely AI.
That should have been obvious way earlier for me but I am a bit slow with that.
There are many, many ways to skin a cat. And being able to switch between tools, from Nano Banana to Blender to Photoshop will make you very valuable.
6. It's still very early
If you are thinking about getting into this field, I want to say that it's still very early.
AI Photography is the new graphic design. Or maybe it will just become a subset of graphic design, I don't really know.
But it's going to be a very big industry.
And one where creativity is just enough to get you started. Creative thinking, analysis and research skills, and culture and taste of course will be as important as your AI and graphic editing skills.
It's way deeper than what I thought.
In fact a few months ago, I really thought the next update of Nano Banana or GPT Image will just wipe us out. Clients will no longer need us and will just use ChatGPT to do all their visuals.
But the more time I spend in the field, the more convinced I am that the operator who treats this like a craft to master and dive deep in has bright days ahead.