AI Portrait Design: Solving Authenticity, Consistency, and Representation in AI Imagery
Problem:
AI-generated portraits often fall short of professional standards. Faces appear over-polished or distorted, subtle details break realism, and the same subject can look inconsistent across variations. In addition, biased training data results in underrepresentation, raising concerns about inclusivity.
Action:
Directed AI tools to replicate studio photography techniques—adjusting camera angles, lighting setups, and artistic styles to achieve realistic, expressive results.
Applied iterative prompting and refinement to preserve subject identity across multiple outputs, ensuring continuity.
Curated and adjusted outputs to broaden representation across skin tones, ages, and cultural identities, countering model bias.
Leveraged hybrid workflows (AI + Adobe Photoshop/Lightroom) for detailed retouching and professional polish.
Result:
Produced authentic, human-like portraits that balance realism with artistic intent.
Solved the challenge of identity drift, enabling consistent subject representation across campaigns.
Elevated inclusivity by intentionally diversifying outputs, making AI portraiture usable for brands with diverse audiences.
