Your Rate My CV report surfaces two different questions.

The first is about fit: does your resume reflect the role language, skills, and experience signals in the job description? The second is about delivery: is the document structured clearly enough for software-assisted screening and for a recruiter who is skimming fast?

That is the practical difference between AI Score and Structure Score.

Harvard and MIT career guidance both make the same broader point from different angles: strong resumes are tailored to the role, fact-based, easy to scan, and clear about impact. Rate My CV splits those concerns into separate signals so you can see what to fix first.

What AI Score Measures

AI Score is the content-alignment side of the analysis.

In plain English, it answers: How closely does this resume match the role I pasted in?

In Rate My CV's analysis flow, that score is driven by content signals such as:

  • keyword overlap with the job description
  • completeness of the resume information the analyzer can detect
  • skills that appear relevant to the role

That means a higher AI Score usually reflects a resume that is more tightly aligned to the target posting, not a universal statement that you are "qualified" in every hiring context.

A high AI Score usually means

  • the resume uses role language that overlaps with the job description
  • relevant tools, skills, or responsibilities are easy to detect
  • the experience reads as targeted rather than generic

A low AI Score usually means

  • key terms from the posting are missing
  • relevant experience is buried or phrased too vaguely
  • the role may genuinely be a weak fit, even if the resume is well written

This is exactly why Harvard's resume guidance stresses tailoring the resume to the position you want rather than sending the same version everywhere.

What Structure Score Measures

Structure Score is the formatting and organization side of the analysis.

It answers: Can the document be read cleanly by both parsing software and human reviewers?

Rate My CV looks for issues tied to structure and document usability, including:

  • whether common sections are present
  • whether formatting appears consistent
  • whether layout choices may create parsing friction
  • whether core contact details are detectable

MIT's ATS guidance is blunt about this stuff: boring is better. Their advice explicitly warns against graphics, text boxes, and tables that can distort or erase information in ATS workflows.

A high Structure Score usually means

  • the resume uses recognizable section headings
  • important information is easy to find
  • formatting is consistent enough to reduce parsing problems

A low Structure Score usually means

  • sections are missing or hard to detect
  • layout choices may break reading order
  • contact details or headings are not easy to parse

Why the Two Scores Need to Be Separate

People mix these up all the time, and that creates bad editing decisions.

If you only look at one headline number, you can miss the real problem:

  • A resume can be well aligned but badly formatted
  • A resume can be cleanly formatted but weakly targeted

Those are very different failures.

Scenario 1: High AI Score, low Structure Score

This usually means your background looks relevant, but the document format is getting in the way.

Common fixes:

  • remove tables, text boxes, and decorative elements
  • use standard section headings like Experience, Education, and Skills
  • move critical contact information into the body of the document

Scenario 2: Low AI Score, high Structure Score

This usually means the resume is readable, but not targeted enough for that role.

Common fixes:

  • add missing role language where it is truthful
  • rewrite bullets so tools, methods, and outcomes are explicit
  • reorder skills and experience around the target posting

Scenario 3: Both scores are low

That is not a tweak problem. That is a rewrite problem.

Start with structure first so the document becomes readable, then tighten the role targeting.

How These Scores Connect to the Full Report

Rate My CV also exposes supporting analysis details that help you understand why the scores moved.

Depending on the analysis flow, those details can include:

  • overall compatibility score
  • keywords found
  • keywords missing
  • skills detected
  • skills relevant to the job
  • sections present and sections missing
  • contact information completeness
  • word count and recommendations

That matters because the score alone is not the insight. The score tells you where to look. The supporting fields tell you what to edit.

For example:

  • if AI Score is lagging and keywordsMissing is full of core role terms, start there
  • if Structure Score is lagging and sectionsMissing includes essentials, fix the document layout before rewriting content

What Not to Do With These Scores

This is where people usually get sloppy.

Do not treat either score as:

  • a promise of an interview
  • a universal hiring cutoff
  • proof that one employer's ATS will behave exactly like another's

MIT's ATS article makes this explicit: some systems may rate or score applicants, but ATS platforms are often closer to searchable databases than magical hiring judges. The useful move is to treat your scores as diagnostic signals, not destiny.

A Simple Way to Use the Scores Well

Use this order every time:

  1. Check Structure Score first. If the document is hard to parse, fix that before chasing wording gains.
  2. Check AI Score second. If the content is not aligned, revise the summary, skills, and bullets to reflect the role truthfully.
  3. Review the supporting fields. Missing keywords, missing sections, and contact-info gaps usually show the next best edit.
  4. Re-run the analysis after each meaningful round of changes.

That workflow is boring. Good. Boring workflows beat random resume tweaking.

The Bottom Line

AI Score tells you whether your resume sounds relevant to the role.

Structure Score tells you whether the resume is organized clearly enough to be read and parsed reliably.

If you improve only one, you leave money on the table. The stronger move is to get both working together: clear role alignment, clear document structure, no gimmicks.

If you want the next step, read How to Analyze Your CV with AI for the workflow, then Understanding Your CV Analysis Scores for the full report breakdown.