Professional real estate photography relies on extensive post-processing, including window exposure correction, sky replacement, object removal, and lighting balance.
This work is time-consuming, expensive, and must meet strict MLS accuracy requirements where images must reflect reality exactly. The question was whether modern generative AI could meaningfully automate this workflow without compromising accuracy.
We tested a multi-step AI retouching workflow using the latest generative image models to perform common real estate edits such as window pulls, sky replacement, lighting correction, and minor object removal.
Each step was evaluated independently and compared against professionally retouched images to assess visual quality and fidelity to the original scene.
The results showed strong potential. Window exposure correction and interior enhancement performed especially well and could significantly reduce editing time and cost.
However, current models still introduce occasional visual inaccuracies that subtly alter reality, which is unacceptable for MLS-grade listings. At this stage, AI can assist and accelerate parts of the workflow, but cannot fully replace professional retouching. Rapid model improvements suggest this may change in the near future.