Choose from a wide range of NEWCV resume templates and customize your NEWCV design with a single click.
Use ATS-optimised Resume and resume templates that pass applicant tracking systems. Our Resume builder helps recruiters read, scan, and shortlist your Resume faster.
Use professional field-tested resume templates that follow the exact Resume rules employers look for.
Create Resume
Use professional field-tested resume templates that follow the exact Resume rules employers look for.
Create ResumeIf you used AI to write your resume, you are not alone. Recruiters increasingly see resumes generated with AI tools, but many are easy to spot because they sound generic, over-polished, repetitive, or disconnected from how real professionals describe their work. Humanizing an AI resume means keeping the speed and structure AI provides while removing the patterns that trigger skepticism during screening.
The goal is not to hide AI use. The goal is to make the resume sound like an actual person with measurable experience, specific accomplishments, and a believable career story. The resumes that get interviews are not the most polished. They are the ones that feel authentic, relevant, and aligned with how hiring managers think.
Recruiters review hundreds of resumes. After enough exposure, certain patterns become obvious.
Common AI signals include:
Generic achievement statements with no context
Repeated phrases across multiple bullet points
Excessive use of corporate buzzwords
Unrealistic accomplishment claims
Perfect but emotionally flat wording
Broad statements that lack specifics
Identical sentence structures throughout the document
A hiring manager rarely says, “This was written by AI.” Instead, they say:
“This feels generic.”
“I still do not know what this person actually did.”
“This sounds like everyone else.”
That reaction matters because resumes survive screening through specificity, not polish.
Most candidates paste a job description into an AI tool and ask it to create an optimized resume.
That shortcut creates a major problem.
The resume often mirrors the language of the job posting instead of reflecting real experience.
Recruiters notice when every bullet point looks engineered around keywords rather than actual work.
Weak Example
“Utilized strategic collaboration methodologies to drive cross functional operational excellence.”
This says almost nothing.
Good Example
“Worked with sales and product teams to redesign onboarding workflows, reducing customer setup time by 35%.”
The second version sounds like a person. It explains action, context, collaboration, and outcome.
AI should organize information. It should not invent your career story.
Before editing your resume, write down:
Projects you actually worked on
Problems you solved
Metrics you improved
Teams you worked with
Systems or tools you used
Difficult situations you handled
Business outcomes you influenced
Recruiters evaluate credibility through details.
Candidates who rely entirely on AI often lose the experiences that make them stand out.
Many AI tools write like they are generating annual reports instead of resumes.
People do not naturally speak this way.
Human resumes use clearer language.
Weak Example
“Leveraged innovative strategies to optimize stakeholder engagement initiatives.”
Good Example
“Built a weekly reporting process that gave leadership better visibility into customer retention trends.”
The second version explains what happened.
Humanization often means simplifying language, not making it more impressive.
Many job seekers worry that humanizing a resume will hurt ATS performance.
That concern is understandable but often misunderstood.
ATS systems primarily identify relevance through skills, terms, titles, and experience alignment. They do not require robotic writing.
Instead of stuffing keywords into every line:
Use skills naturally inside accomplishments
Mirror role terminology when accurate
Keep core tools and technologies visible
Use role specific language recruiters expect
For example, if the role requires CRM management, customer onboarding, Salesforce, and forecasting, incorporate those terms naturally into real examples.
Good Example
“Managed Salesforce pipelines and forecasting reports that supported a 15 person sales team.”
The keyword exists naturally.
The strongest AI edited resumes usually follow a simple structure.
Think:
Action + context + outcome
Instead of:
Action + buzzword + buzzword
Example:
Weak Example
“Implemented innovative client engagement strategies.”
Good Example
“Introduced a follow up process for enterprise clients that increased renewal rates by 18%.”
Recruiters screen for evidence.
They want to understand:
What you did
Why it mattered
What changed because of your work
AI generated resumes often create bullet points that all look identical.
Example pattern:
“Led...”
“Led...”
“Led...”
“Led...”
Humans naturally vary how they describe work.
Use combinations like:
Built
Improved
Partnered
Designed
Reduced
Created
Streamlined
Managed
Developed
Introduced
Sentence variation makes resumes sound more natural.
It also keeps recruiter attention longer.
One overlooked signal of authenticity is context.
Real professionals work under constraints.
AI often removes them.
Examples include:
Limited budgets
Tight deadlines
Team growth periods
Process failures
High volume environments
Cross functional complexity
Good Example
“Redesigned support workflows during a period of 40% customer growth without increasing headcount.”
That sounds believable because it reflects a real business situation.
Certain phrases appear repeatedly in AI generated resumes.
Watch for:
Results driven professional
Dynamic self starter
Proven track record
Detail oriented individual
Synergy focused
Strategic thought leader
Passionate and motivated professional
These phrases rarely influence hiring decisions.
Replace them with evidence.
Instead of claiming you are results driven, show measurable results.
This is one of the simplest editing techniques and one of the most effective.
Ask:
Would I actually say this in an interview?
If the answer is no, revise it.
Resumes and interviews are connected.
Candidates often struggle during interviews because AI wrote stories they cannot naturally explain.
A resume should sound like a future conversation.
Most candidates think resume screening is purely keyword based.
That is incomplete.
Recruiters assess risk.
Every resume creates an internal question:
Can I confidently move this person to the next step?
Overly polished AI resumes sometimes reduce trust because they feel manufactured.
Ironically, resumes with realistic detail, imperfect phrasing, and specific experiences often perform better.
Hiring teams trust candidates who sound like practitioners rather than marketers.
What works:
Specific achievements
Natural language
Measurable outcomes
Real project details
Varied writing patterns
Context around challenges
What fails:
Buzzword stacking
Empty corporate language
Generic AI summaries
Unrealistic accomplishments
Excessive keyword repetition
Over engineered writing
Before submitting your resume, review these questions:
Could a recruiter understand what I actually did?
Would I comfortably explain every bullet point in an interview?
Does each achievement include context?
Do accomplishments sound believable?
Are keywords integrated naturally?
Does the resume sound like a person instead of software?
If you answer yes to those questions, you are likely ahead of most AI generated resumes in today's market.
Upload Resume
Import from Linkedin
