AI Headshot Before and After: Real Results From Real Selfies (2026)

MH

Matthieu van Haperen

Founder & CEO, TeamShotsPro · Updated Feb 2026

TL;DR: Quick Answer

AI headshot generators in 2026 produce professional-quality results from ordinary selfies — but the output depends heavily on what you put in.

A well-lit, front-facing selfie generates headshots that are difficult to distinguish from studio photography.

A dimly lit photo taken at arm's length in a bathroom mirror produces results that scream AI.

This article shows you exactly what to expect: real input photos, real AI output, what works, what doesn't, and how to spot the artifacts that give AI headshots away.

AI Headshot Before and After: Real Results From Real Selfies (2026)
Disclosure: This article is written by Matthieu van Haperen, founder of TeamShotsPro. We've included results from our own platform alongside competitor platforms to give you an honest picture of what AI headshots look like in 2026. Where TeamShotsPro performs well, we say so. Where others are better, we say that too. This article is part of our Complete Guide to AI Professional Headshots.

Why Before and After Matters More Than Marketing Screenshots

Every AI headshot platform shows you their best results. That's marketing. What they don't show you is what happens when the input photo is less than ideal — which is what most people actually upload.

We ran a different test. We used the same input selfies across multiple scenarios: good lighting vs bad lighting, front-facing vs angled, high resolution vs phone-quality, with accessories vs without. Then we documented every result — including the ones that didn't work.

The goal isn't to make AI headshots look good. It's to show you exactly what to expect so you can decide whether the results meet your professional standards.

What We Tested

We used input photos from 6 different people across a range of conditions:

  • Lighting: Natural window light, overhead office fluorescents, dim evening, direct sunlight
  • Angle: Straight-on, 15° turn, 30° turn, slight upward tilt, slight downward tilt
  • Quality: iPhone 15 Pro at arm's length, older Android phone, webcam still, DSLR crop
  • Accessories: Glasses, earrings, necklaces, ties, lapel pins
  • Hair types: Straight, wavy, curly, coiled, short, long, bald
  • Ethnicities: Diverse group to test for skin tone accuracy and bias
For each scenario, we generated headshots using TeamShotsPro's platform. We note below where specific results would differ on other platforms — for a full platform-by-platform comparison, see our 8-platform review.

Scenario 1: Good Input — The Ideal Selfie

Input: Front-facing selfie, natural window light from the side, plain wall behind, neutral expression, phone held at eye level. Result: This is the sweet spot. The AI had clean data to work with and produced a headshot with natural skin texture, accurate facial features, proper studio-style three-point lighting, and a clean gradient background. Hair edges were crisp. Eye color accurate. Overall impression: indistinguishable from a studio photo at LinkedIn resolution (400x400). What the AI changed: Background replaced with professional gradient. Lighting re-rendered to simulate studio setup. Clothing swapped for business attire. Minor skin refinement (not over-smoothed). What the AI preserved: Facial structure, eye shape and color, hairline, skin tone, unique features (moles, asymmetry, facial hair). Verdict: If your input looks like this, you'll get professional results from any competent AI headshot platform.

Scenario 2: Bad Lighting — The Office Fluorescent Problem

Input: Same person, same angle, but photographed under overhead fluorescent office lights. Harsh shadows under the eyes and nose. Slightly greenish color cast from the fluorescents. Result: The AI compensated for the poor lighting — it rebalanced skin tones and softened the harsh shadows. But it didn't fully solve the problem. The result had slightly uneven illumination on the left side of the face, and the skin tone was warmer than the person's natural complexion. Usable, but noticeably less natural than the well-lit version. Key takeaway: AI can improve bad lighting, but it can't completely invent light that wasn't there. The output is always a processed version of what you gave it. Start with good light, and the AI has less guesswork to do. Tip: The single best thing you can do for AI headshot quality is stand facing a window. Natural side-lighting gives the AI the depth and tonal information it needs to produce realistic results. For more input photo guidance, see our professional headshot tips guide.

Scenario 3: The Angle Test — How Much Turn Is Too Much?

Input: Same person, same lighting, photographed at four different face angles: straight-on (0°), slight turn (15°), moderate turn (30°), and profile-adjacent (45°). Results: 0° (straight-on): Excellent. Balanced, symmetrical, professional. 15° turn: Still strong. This slight angle is actually where many AI platforms produce their most natural-looking results. The subtle asymmetry prevents the "too perfect" look that straight-on shots sometimes create. 30° turn: Acceptable but with caveats. The AI correctly rendered the visible side of the face but had to infer more of the obscured side. The result looked slightly flatter than reality. Fine for LinkedIn at standard resolution; less convincing in a high-resolution crop. 45° turn: Not recommended. At this angle, the AI is generating nearly half the face from inference rather than data. The result had visible asymmetry issues — one eye appeared slightly different in shape than the other. Most platforms struggle here. Verdict: Stay between 0° and 15° for the most reliable results. A slight turn is fine and even beneficial for natural appearance. Anything beyond 30° is a gamble.

Scenario 4: The Accessory Problem — Glasses, Earrings, and Jewelry

Input: Same person wearing different accessories across separate shots: thin metal-frame glasses, thick plastic-frame glasses, hoop earrings, small stud earrings, a necktie with tie clip, and a pendant necklace. Results: Accessories remain the single biggest weakness of AI headshot generators in 2026. Here's what we found: Thin-frame glasses: The AI mostly handled these — frames were recognizable and roughly symmetrical. But there was a slight warping where the temple arm meets the hinge, and the reflection pattern in the lenses didn't match the studio background the AI added. Thick-frame glasses: Better than thin frames, surprisingly. The thicker material gave the AI more visual data to work with. Results were usable, with minor edge inconsistencies. Hoop earrings: Significant issues. The hoops appeared warped — one was slightly larger than the other, and the metal texture looked melted rather than solid. This is a known weakness across all platforms. Stud earrings: Almost invisible issues. Small studs are simple enough geometry that AI handles them well. If you wear earrings for your headshot, studs are the safe choice. Necktie with clip: The tie rendered correctly. The tie clip was a different story — it appeared slightly floating above the tie fabric rather than pinned to it, and the metallic reflection was inconsistent. Pendant necklace: Mixed results. The chain was mostly accurate, but the pendant itself had a subtle "melted" quality where it sat against the skin. Not terrible, but noticeable at close inspection. Verdict: Remove accessories before your selfie if possible. If you wear glasses and can't remove them, thick frames produce better results than thin ones. For earrings, stick with studs. For our full breakdown of what AI handles well and where it struggles, see the technology section in our hub guide.

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Scenario 5: Hair Types and the Edge Problem

Input: Four people with different hair types: straight and fine, wavy and medium-density, tightly curled, and close-cropped. Results: Straight, fine hair: Clean edges. The boundary between hair and background was sharp and natural-looking. This is the easiest hair type for AI to process. Wavy, medium hair: Good results. Some minor softness at the outermost edges where individual wisps met the background, but nothing that would look wrong at LinkedIn resolution. Tightly curled hair: This is where current AI still struggles the most. The complex, three-dimensional texture of curly hair creates edge-detection challenges. The AI rendered the overall shape correctly but smoothed out individual curl definition at the edges, creating a slightly "halo" effect. Better platforms minimize this; lower-quality ones make it obvious. Close-cropped hair: Excellent results. The simple silhouette gave the AI a clean edge to work with. Some of the most natural-looking outputs in our entire test came from people with short hair. Verdict: Hair type significantly affects edge quality. If you have curly or textured hair, check the AI output carefully at the hair-background boundary — this is where most artifacts appear. Choosing a background color that's closer to your hair color can reduce the visibility of any edge issues.

Scenario 6: Skin Tone Accuracy Across Ethnicities

Input: Six people with a range of skin tones, from very fair to very dark, all photographed under the same lighting conditions. What we measured: We compared the skin tone in the AI output to the original selfie, looking at three things: overall hue accuracy (is the tone correct?), tonal range preservation (do highlights and shadows look natural?), and undertone consistency (does the warmth/coolness match?). Results: The best platforms in 2026 handle skin tone diversity well — this has improved dramatically compared to even a year ago. We found consistent accuracy across light, medium, and olive tones. Darker skin tones showed slightly more variation: some outputs shifted warmer than the original, and deep shadow areas occasionally lost detail.

The most important factor wasn't ethnicity but lighting. A well-lit selfie produced accurate skin tones regardless of complexion. A poorly lit selfie produced tone shifts regardless of complexion. The AI reflects the data it receives.

Verdict: Skin tone accuracy has improved significantly across the industry, but it isn't perfect. If you have a deep skin tone, pay extra attention to your input lighting — avoid shadows on the face, which can cause the AI to misinterpret your natural tone. For more on how different industries evaluate AI headshot quality, see the authenticity section in our platform review.

The 5 Most Common AI Headshot Artifacts (and How to Spot Them)

After generating hundreds of test headshots, here are the five tells that appear most frequently — even from the best platforms:

1. The Porcelain Skin Effect

What it looks like: Skin that's too smooth, too even, too perfect. No visible pores, no micro-texture, no natural variation. The person looks like a mannequin or a heavily filtered Instagram photo. Why it happens: AI models are trained on retouched photography. They learn that "professional" means smooth, so they over-correct. How to spot it: Zoom to 100%. Real skin has texture — pores, fine lines, subtle color variations. AI skin often looks like soft plastic at close range.

2. The Lighting Mismatch

What it looks like: The direction of light on the face doesn't match the shadows and highlights on the background or clothing. The face appears to exist in a different lighting environment than the rest of the image. Why it happens: The AI generates the face, background, and clothing as somewhat separate elements and then composites them. The lighting models for each element don't always agree. How to spot it: Look at where the shadows fall. On the face, is the light coming from the left? If so, the shadow on the collar should also be on the right side. Mismatches here are a dead giveaway.

3. The Melted Accessory

What it looks like: Earrings, glasses frames, tie clips, or necklaces that look slightly warped, asymmetric, or as though they're merging into the skin rather than sitting on top of it. Why it happens: Small, detailed objects with reflective surfaces are hard for AI to reconstruct accurately. The model doesn't understand the physical properties of metal or glass the way it understands face geometry. How to spot it: Compare left and right sides of any paired accessory (earrings, glasses). If they're noticeably different in shape or size, it's an AI tell.

4. The Uncanny Hair Edge

What it looks like: A soft, glowing border where hair meets background. Individual strands disappear into a blurred boundary instead of having the natural randomness of real hair. Why it happens: Hair edges are one of the most computationally difficult features to render. The AI takes a shortcut by blurring the transition rather than rendering each strand. How to spot it: Look at the outermost hair strands against the background. In a real photo, you'd see individual flyaway hairs. In AI headshots, the edge is often suspiciously clean or unnaturally soft.

5. The Dead Eyes

What it looks like: Eyes that are technically correct but lack the micro-reflections and depth of real eyes. The catchlight (the bright reflection in the eye) may be in the wrong position for the lighting, or both eyes may have identical reflections despite being at slightly different angles. Why it happens: Eyes are one of the first things humans notice, and our brains are extremely sensitive to subtle wrongness in them. The AI renders anatomically plausible eyes but sometimes misses the physics of light reflection. How to spot it: Look at the catchlights in both eyes. In a real studio photo, the catchlights show the actual light source and are positioned consistently with the lighting direction. In AI headshots, they're sometimes placed symmetrically even when the lighting is coming from one side.

How to Get the Best AI Headshot Results: Input Photo Checklist

Based on everything we tested, here's what makes the difference between a usable AI headshot and a disappointing one:

Lighting: Face a window. Natural side-lighting is the single biggest quality factor. Avoid overhead lights, backlighting, and direct harsh sunlight. Angle: Straight-on or up to 15° turn. Hold the phone at eye level, not below your chin (the up-the-nose angle is the most common selfie mistake). Distance: Arm's length minimum. If possible, use a timer and prop the phone 3–4 feet away. More distance means less lens distortion on facial proportions. Expression: Relaxed and natural. The AI preserves whatever expression you give it. A tense selfie produces a tense headshot. Accessories: Remove them if you can. If you need glasses, keep them. Everything else — earrings, necklaces, scarves, hats — take it off for the selfie. You can specify accessories in the style settings of most platforms. Background: Doesn't matter much for the final output (the AI replaces it), but a clean, uncluttered background helps the AI process your face and hair edges more accurately. Resolution: Use the highest camera quality your phone offers. More pixels means more data for the AI. Avoid screenshots, crops of group photos, or images saved from social media (these have been compressed and lose detail).

For a full guide on optimizing your input photos for both AI and traditional photography, see our professional headshot tips guide.

Free vs Paid: Does the Before-and-After Differ?

Yes — significantly. We tested the same input selfies across free and paid platforms. The difference is most visible in three areas:

Skin texture. Paid platforms preserve more natural texture. Free tools tend to over-smooth, creating that porcelain look. Hair edges. Paid platforms render cleaner, more natural hair-background transitions. Free tools often blur aggressively. Accessory handling. Paid platforms have gotten better at rendering glasses and earrings with fewer artifacts. Free tools still struggle with anything beyond simple geometry.

If you're deciding between free and paid, see our free AI headshot generators guide for an honest comparison of what $0 gets you vs. what paid platforms deliver.

See for Yourself

The fastest way to evaluate AI headshot quality is to test it with your own face. TeamShotsPro offers 3 free headshots from a single selfie — no credit card required. Upload a selfie, see the before and after, and judge the quality against your own standards.

Upload a Selfie → Get Team Headshots

Related Reading

Frequently Asked Questions

How many selfies do I need for good before-and-after results?▼

It depends on the platform. Some tools need 8–20 photos to train a model on your face. TeamShotsPro needs just 1 selfie (minimum 2 for optimal results). Generally, more input photos help with facial accuracy, but a single well-lit photo beats 15 poorly lit ones. For detailed input guidance, see our [professional headshot tips guide](/blog/professional-headshot-tips-guide).

Do AI headshots look like me or an idealized version of me?▼

The best platforms in 2026 aim for "you on a good day" — your real features with professional lighting and styling. Cheaper tools tend to over-idealize, smoothing out features that make you recognizable. If your AI headshot doesn't look like you when you walk into a meeting, it's doing more harm than good. See our [full platform comparison](/blog/ai-headshots-review-2026) for how each platform handles facial accuracy.

Can I use AI before-and-after headshots for my company's team page?▼

Yes, and this is one of the strongest use cases. AI headshots give every team member the same background, lighting, and style — creating visual consistency that's nearly impossible to achieve with traditional photography when people join at different times. For the full enterprise implementation approach, see our [corporate AI headshots playbook](/blog/ai-headshots).

How do AI headshot results compare to a professional photographer?▼

For standard digital use (LinkedIn, company websites, email signatures), the best AI platforms produce results that are indistinguishable from studio photography. For large-format print or situations where someone will be examining the photo closely at high resolution, traditional photography still has an edge. See our [AI vs traditional photography comparison](/blog/ai-professional-headshots-guide#ai-headshots-vs-traditional-photography-the-2026-reality) for a detailed breakdown by use case.

What should I look for when evaluating my AI headshot results?▼

Check five things: skin texture (should have visible pores and natural variation, not plastic), lighting consistency (face shadows should match clothing shadows), hair edges (should have natural randomness, not a glowing border), accessory accuracy (glasses should be symmetrical, earrings should match), and overall likeness (should look like you, not an idealized avatar). ---

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Matthieu van Haperen

About the Author

Founder & CEO, TeamShotsPro

Matthieu van Haperen runs TeamShotsPro, where he has helped hundreds of teams get professional AI headshots. Before founding TeamShotsPro, he spent 6+ years building and scaling tech startups. He writes about professional photography, team branding, and how AI is reshaping corporate imagery.

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