"Image Trace or an AI vectorizer?" usually gets answered with labels: one is built into Illustrator, the other says AI on the box. Both do the same job, rebuilding a raster image as vector paths. Adobe documents Image Trace's presets and its controls for paths, corners, noise and colors in the Image Trace panel guide, but not enough of the implementation to say which approach is "more AI". The label tells you little. The expanded output tells you a lot.
Workflow is the honest split. If you already edit in Illustrator and like hand-tuning a trace before you expand it, Image Trace is right there. If you want an automated result without opening a design app, or you need an API or batch surface (some dedicated tools have one, so check the docs), test a dedicated vectorizer. Neither turns a photo into a clean SVG: continuous tone comes back as posterized art or thousands of shapes, and no tracer invents detail a low-res source never captured.
What decides your cleanup time is the paths: how many segments the same shape needs, whether you can select and recolor one region instead of a welded tangle, and whether the silhouette still matches the source. So trace the same image in both, at the same intended fidelity, and put a number on it. This dependency-free script counts the drawing segments in a plain SVG:
import re, sys ARGS = dict(m=2, l=2, h=1, v=1, c=6, s=4, q=4, t=2, a=7, z=0) TOKEN = re.compile(r"[MmLlHhVvCcSsQqTtAaZz]|[-+]?(?:\d*\.\d+|\d+\.?)(?:[eE][-+]?\d+)?") def segments(d): """Count drawing segments in one path's d attribute, implicit repeats included.""" count, cmd, nums = 0, None, 0 for tok in TOKEN.findall(d) + ["Z"]: if tok.isalpha(): if cmd and ARGS[cmd]: count += nums // ARGS[cmd] - (cmd == "m") # extra M pairs are lines cmd, nums = tok.lower(), 0 else: nums += 1 return count svg = open(sys.argv[1], encoding="utf-8").read() paths = re.findall(r"<path\b[^>]*?\sd=[\"']([^\"']*)", svg) images = len(re.findall(r"<image\b", svg)) print(f"{len(paths)} paths, {sum(map(segments, paths))} segments, {images} embedded images") Run python count_nodes.py trace-a.svg and python count_nodes.py trace-b.svg, then put both files side by side at the same zoom. Fewer segments for the same silhouette means easier edits and lighter files downstream; a non-zero "embedded images" count means part of the file is still a bitmap. The script reads <path> elements only (shapes like <circle> are skipped), doesn't count the implicit closing line of z, and expects arc flags separated by spaces or commas. On a 60-path test file it matched svgpathtools' segment count exactly.
The full guide has the side-by-side comparison table, when each tool is the right call, where both approaches struggle, and an FAQ: Image Trace vs AI Vectorizer: Choose the Right Tool
We build PerfectVector, an AI image-to-vector converter designed for low-node, editable paths. Run the same image through it, inspect the paths in a free preview, and pay only if you download (compare it with Image Trace).
