Beat the AI Filter: How to Get your CV seen by Recruiters in the AI Age

It’s undeniable that AI has - for better or worse - already had a huge impact on the software industry, from its practical applications at the technology level, to the changing demand from skills and experience, to the layoffs linked to AI processes taking over. One area we haven’t really talked about in our articles yet is recruitment: it’s no secret that AI is being used to scan CVs and automatically filter candidates. Several of my developer friends have been talking about this recently, and with a slew of layoffs in tech sending a lot of IT folks on the hunt for new jobs, I thought this would be the perfect time to dive into how AI is being used to filter candidates, and what you can do to stand out and get past the filters.

65% of employers will use AI tools to reject candidates

 in 2025. That’s a staggeringly high number, but for folks who work in hiring or are currently job hunting it’s not a surprising one.

The article offers a further breakdown of how employers plan to use–or are already using–AI in their hiring process.

Unsurprisingly, the main uses are for summarizing CVs and assessing candidates’ skills. To be clear, AI tools are not (yet) making hiring decisions directly, but rather are used to automatically tag candidates as being worth (or not) pursuing for a role. 

The rest of these use cases are fairly self-explanatory, but some might be curious as to what using AI for conducting interviews entails. The article does not specify, but this probably refers to AI proctored testing. That is, online coding or general knowledge tests where an AI tool monitors your screen activity (or even your camera in some cases) to ensure you aren’t alt-tabbing to StackOverflow or ChatGPT during the test.

In this article we’re going to focus on résumé screening and how you can get past AI filters. But first we need to look at how these systems work.

If you search for a list of the most common types of candidate screening software, you’ll find that there are a 

These software offerings vary quite a lot in their use cases and applications, with some being focused around integrations with talent management platforms and CRM, and others being more straightforwardly focused on bulk screening of résumés.

There are two broad classes of candidate screening solutions, though many offerings don’t fit neatly into one box or another.

 which are more comprehensive platforms that manage CVs and other applicant info at a high level, and may incorporate one or both of the screening methods above or broader analytics and insights on candidates and recruitment processes.

What are the most Common Candidate Screening Software Products?

Remember when I mentioned there were a lot of candidate screening tools on the market? That wasn’t an exaggeration. If you look at the top 10-12 articles if you search for ‘most common resume screening tools’ you’ll find there isn’t much in the way of consensus and that the landscape for these types of tools is very competitive. I’ve compiled a small, non-exhaustive list of some of these tools below. 

This isn’t meant to be a “best of” compilation, but rather a representative sample of the most commonly used CV screening software products to give you an idea of what you’re up against. We don’t have space for a detailed, feature-by-feature description of these solutions, but I recommend taking a look at the linked sites for these companies and getting an idea of what they offer employers.

I’ve collected quite a few tips here, and I’ve tried to rank them more or less in the order of importance (though it’s hard to do this objectively). One of the main things I want you to remember is that despite the use of AI everywhere, the fundamentals of a good CV remain the same.

You probably know the fundamentals already, but just in case:

Now that we’ve gotten those out of the way, let’s move onto tips relevant to AI screening.

When reading a job description, you’ll probably recognise some keywords - these are usually the names of specific competencies or technologies that are required for the role. For example a coding language, a tech stack, or a specific software. So if a job post mentions, say, Jira or SQL, and you have experience with those, make sure you include them. Résumé parsers will immediately send you to the discard pile if they don’t detect you have the core competencies for the role. Make sure you spell keywords correctly.

This is related to what we said above regarding the active voice. The more specific your language, the more powerful it is. A generic statement sounds something like this: “I worked with teams in the AI space that worked on SEO integrations” - that doesn’t really tell me anything as a recruiter. In fact, I would avoid words like “worked” altogether. It’s better to list the specific action you performed. Let’s clean up that previous statement, shall we? “I developed product strategy and ramp up plan for two offshore development teams building an AI analytics solution for our SEO layer. The project was completed three weeks ahead of schedule.” Much better! Note how we’ve put a quantifiable metric here (delivering three weeks early).

This is already largely covered by the first item in our list of CV fundamentals above - your CV should be easy to read. Make sure your headings are clear and unambiguous so AI screening tools know where to look - a clear boundary is needed between different types of information. It’s especially necessary to be concise and to ensure you have a section entitled “Skills” (not “Skills Overview for QA Role”, not “My Awesome Skills” – just “Skills”). Avoid using columns.

Look, it’s 2025, and we all probably prefer to read PDFs than word docs, but the fact remains that PDFs can be harder to read for automated systems. In many cases, it won’t matter, but you never know when something can get corrupted or not play nice with some component in a hiring team’s back-end. 

In other words, email recruiters directly. This can be a little bit harder for introverted folks like myself, but many job postings include an email address for the recruiter, and showing the initiative by emailing them vastly increases your chances of getting your CV read by a human. Obviously, you should be judicious about this and avoid spamming, but a polite email with a brief cover letter (”Hello , I’m reaching out to you regarding a job post I saw on XYZ. I would like to submit my candidacy for this role, and I believe I’m well suited because XYZ”). I particularly recommend this approach if it’s a job or company that you’re particularly interested in, or if you have some relevant experience that’s hard to include in your CV.

Tailor your Résumé to the Job Description

We could probably have included this one in our list of fundamentals (and we sort of did when we mentioned relevance), but it bears repeating. You can’t include every single piece of experience you have on two pages, so it’s natural that some of it will need to be trimmed. Make sure you position your CV for the correct role. Keeping more than one CV template can be useful - I’ve worked as a QA engineer, a TPM, and as a Technical Writer, and thus I have three CV templates for each of these domains which I can further tweak to highlight relevant experience. 

If you have LinkedIn or use Indeed (or any other major job platform), ensure that your profile is up-to-date and comprehensive. Many AI tools will cross-reference your CV against LinkedIn and might throw up a flag if there are major discrepancies.

I couldn’t finish this article without addressing the elephant in the room - is using AI to write your CV a good idea? 

It’s a divisive topic, and you will see some mixed opinions on this online. If AI is used to screen CVs, this seems like an obvious remedy - a means of fighting fire with fire. AI-generated CVs (presuming the right tools are used and that they have the correct context) can certainly produce a résumé that looks the part, has the right keywords, and possibly even makes it past an AI filter - that is, presuming the employers don’t automatically check for AI use in the screening process. Moreover, a CV or cover letter that has ‘tells’ that it was written by an LLM, even if it gets past screening, will generally not be viewed favourably by the human who eventually reads it.

The issue is that it’s very hard to give LLMs the correct context - in short, you have to provide an existing CV or work history and a job description for them to be useful. Thus, it’s not really possible to to make an AI CV from scratch (well, okay, it’s very much possible - but not to make a 

 one that actually reflects your experience). Some people may disagree with me (if you’re one of them, please say why in the comments!), but I believe AI résumé tools only really useful for templating and review, not wholesale generation.

That said, I tried out a few free AI review tools with my own résumé and had fairly mixed results, but these remained fairly consistent in my experience:

I definitely felt there was some value in using them, but I maintain a healthy amount of cynicism. But I don’t expect anyone to take my word for it - there’s plenty of AI CV reviewers and builders out there that have a free tier or free trial - I suggest you experiment with a few of them and see if you agree.

As I hope is evident from this article, while AI has changed hiring processes drastically, the fundamentals of what make a good CV remain mostly unchanged. Hiring tools, after all, are designed to help recruiters find the ideal candidate more quickly. Focusing on being the best candidate is always more important than trying to ‘game’ the AI screening system. For the most part, the tips for getting your CV seen by a human are just extensions of the fundamentals of good CV writing that existed long before automated screening.

It’s a hard time in the job market right now, and I know it’s easy to get discouraged or feel hopeless - especially if you’ve been affected by layoffs. But I want to give you one last tip: be persistent, and don’t give up hope. Maybe you’ll need to apply to 100 jobs before you find the right role, maybe 500, but the best thing–the only thing, really– to do is to keep going. Experiment with your CV, tailor it to different roles, reach out to recruiters and network - but keep going. 

Best of luck to all of you out there searching for new jobs.

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