A Candidate’s Guide to AI in the Hiring Process

You submitted your application three days ago. No response. No confirmation beyond an automated email. Somewhere between hitting submit and waiting for a callback, your resume passed through a system you never saw, was evaluated by criteria you were never shown, and may have been filtered out before a single human ever read your name.

If that feels opaque, even a little unfair, you’re not wrong to feel that way. AI is now embedded in nearly every stage of modern hiring, from the moment your resume is uploaded to the moment an interview is scheduled, and most candidates have no idea how it works.

Below, we’ll explain what AI hiring tools actually do, what they’re evaluating, what they’re not, and crucially, how responsible AI can actually work in your favor. We’ll also tell you what questions you have every right to ask during the process.

Where AI Shows Up in the Hiring Process

AI doesn’t just live in one place in the hiring funnel. It can appear at multiple stages, sometimes without any indication that it’s there. Here’s where you’re most likely to encounter it:

Resume Screening

This is the most common use of AI in hiring. When you apply for a role, an AI tool may scan your resume before a recruiter ever opens it. It’s looking for job-relevant skills, experience signals, and keyword matches against the role’s requirements. The goal is to rank or filter a high volume of applications quickly.

What this means for you: the way you describe your experience matters. Mirroring the language in the job description, not copying it word for word, but using the same terminology for skills and tools, helps ensure the AI recognizes what you’ve done.

Pre-Hire Assessments

Many employers now use AI-powered assessments as part of the application process. These evaluate job-relevant skills, including both hard skills like technical ability and soft skills like problem-solving approach, work style, or communication. The best assessments are validated against real performance data, meaning the questions are specifically designed to predict how someone will actually perform in the role.

What this means for you: these assessments aren’t looking for a “perfect” personality type. They’re measuring fit for a specific role. The goal of a well-designed assessment is to find candidates who will genuinely thrive, not to trick you. Answering assessment questions authentically helps you land in a job that will lead to your success and happiness. While we all want to land our next job quickly, faking answers to fit what you think the ideal is could lead to lower satisfaction in your new role and starting the job hunting process all over again sooner than you hope for.

Video Interviews

Some hiring processes include AI-assisted video interviews, where your responses are recorded and scored. How those responses are evaluated varies significantly by tool. The most responsible tools evaluate only the substance and relevance of your answers, not how you look, your accent, or your facial expressions. This distinction matters enormously and is worth asking about.

What this means for you: Before completing a video interview, find out what the AI is evaluating. If the employer or platform can’t tell you clearly, ask. You have the right to know whether your appearance or tone is being analyzed. If you’re using a platform backed by responsible AI, which is one that evaluates content only, focus your energy on the clarity and substance of your answers, not on how you look on camera.

Interview Scheduling and Communication

AI is also commonly used for the more administrative parts of hiring: scheduling interviews, sending status updates, and managing candidate communications. This is largely behind the scenes and has the least direct impact on your evaluation.

What this means for you: Automated scheduling and communication tools are generally there to make the process faster and more consistent for both sides. Respond promptly to scheduling requests and confirmations, delays can affect how engaged you appear in the process. If something goes wrong (a scheduling conflict, a missed message), don’t assume a human saw it. Follow up directly with a recruiter or hiring contact to make sure nothing slips through.

What AI Is Actually Evaluating and What It Isn’t

AI hiring tools can vary in quality, methodology, and transparency. Not all AI is created equal, but knowing what they should and should not evaluate can help you determine the quality of the screening process you are engaging in and can help inform whether or not you’d like to continue with the process.

What responsible AI hiring tools evaluate:

• Job-relevant skills and competencies tied to the specific role
• Behavioral indicators that predict on-the-job performance
• Hard skills assessed through structured, role-specific questions
• Soft skills measured through validated psychometric methodology

What responsible AI hiring tools should NOT evaluate:

• Your name, gender, age, or demographic markers
• Your physical appearance or facial expressions
• Your accent or tone of voice
• The prestige of your university or employer
• Anything that correlates with protected characteristics

The distinction is critical. Poorly designed AI tools can inadvertently (or deliberately) use proxies that disadvantage candidates unfairly. A tool that screens resumes based on patterns from historical hires, for example, may replicate whatever biases existed in those past decisions on a massive scale.

Responsible AI tools are specifically designed to prevent this. They remove demographic information before scoring, use validated criteria tied to job performance rather than pedigree, and are regularly audited for adverse impact across protected groups. When AI is built this way, it can actually level the playing field, evaluating you on what you can do, not where you went to school or what your name sounds like.

Can AI Be Biased? The Honest Answer.

It depends. AI is not universally biased, and it’s important to understand why.

AI learns from data. If that data reflects biased hiring decisions from the past, such as fewer women hired in technical roles, fewer candidates of color advancing past screening,  a model trained on that data will learn to replicate those patterns. This is called algorithmic bias, and it’s a real and documented problem in hiring AI.

But here’s what’s equally true: human hiring is also deeply biased, consistently, and often invisibly. Interviewers make snap judgments within the first few minutes of a conversation. Affinity bias causes hiring managers to favor candidates who remind them of themselves.

The gold standard: AI hiring tools that hold a patent for bias mitigation, conduct regular adverse impact audits across protected groups, and can explain exactly how every candidate was scored, are meaningfully more equitable than the unstructured, gut-feel processes they replace.

The question isn’t whether AI introduces bias, it’s whether it introduces more or less bias than the human process it’s replacing, and whether it’s been designed and tested with fairness as a genuine priority. 

When evaluating whether an employer’s AI is built responsibly, the key is transparency. A trustworthy tool should be able to tell you what it measured and why.

How to Perform Well in an AI-Assisted Hiring Process

The good news: if an employer is using a well-built AI tool, you don’t need to “game” it. You need to show up authentically and clearly. Here’s how to do that:

• Mirror the job description’s language. AI resume screening tools look for signals of relevance. If the role requires “project management” and your resume says “managed projects,” you may be underselling yourself. Use the terminology the job description uses.
• Be specific about skills. Vague claims like “strong communicator” or “team player” don’t give AI tools or human reviewers much to work with. Describe what you did, what tools you used, and what the outcome was.
• Take assessments seriously. Pre-hire assessments are not box-ticking exercises; they’re often the most predictive data point in the process. Treat them with the same preparation you’d give an interview. Read the instructions carefully and answer thoughtfully.
• Answer video interview questions directly. If your video interview responses are being scored on content, structure your answers clearly. Use the STAR method (Situation, Task, Action, Result) to give AI tools and human reviewers concrete signals to evaluate.
• Don’t try to outsmart the system. Keyword stuffing your resume or giving answers you think the AI “wants to hear” typically backfires. Well-designed assessments are built to detect inconsistent or inauthentic responses.

Questions You Have the Right to Ask About AI in Hiring

As a candidate, you have more rights in an AI-assisted hiring process than most people realize,  and those rights are expanding as legislation catches up with technology. Here are the questions you’re entitled to ask:

• Does this process use automated decision-making tools, and if so, at what stages?
• What criteria is the AI evaluating me on?
• Has the tool been tested for bias and adverse impact across demographic groups?
• Can a human review my application if I’m screened out by an automated system?
• How is my data being stored, used, and protected?
• Will my data be shared with third parties or used to train AI models?

In jurisdictions with active AI hiring legislation, including New York City, Illinois, and others, employers may be legally required to disclose when AI is being used in hiring decisions and to provide audit results on request. Even where it isn’t yet legally required, any employer using AI responsibly should be willing to answer these questions directly. If an employer can’t or won’t explain how their AI tools work, that’s worth knowing before you invest more of your time in their process.

What Responsible AI Looks Like

Not all AI hiring tools are built with candidates in mind. Many are designed primarily to reduce recruiter workload, and candidate experience, fairness, and transparency are afterthoughts.

Responsible AI evaluates candidates based solely on job-relevant skills and validated competencies, never appearance, demographic signals, or pedigree. Every score comes with a clear explanation of why, using transparent rubrics that hiring teams define and approve before the process begins.

That transparency isn’t just good for candidates, it’s good for employers. When hiring decisions are explainable and grounded in validated data, they’re more defensible, more consistent, and more likely to result in hires who actually succeed in the role.

Our Takeaways

AI in hiring is here to stay, and for candidates who understand how it works, that’s not necessarily bad news.

When AI is built responsibly, validated against real performance data, tested for bias, and designed to be explainable, it removes some of the most entrenched unfairness in traditional hiring. It doesn’t care what your name sounds like, which school you attended, or whether you remind the interviewer of themselves. It measures what you can do.

The key is knowing which tools meet that standard and which don’t, and asking the questions that separate the two. You’ve put time and energy into your application. You deserve to know what’s evaluating it.

If you’re a candidate and would like to learn more, make sure to check out additional screening trends, the soft skills to master, and what we expect to see in the future.

If you’re a recruiter, please consider sharing this piece with your candidates to help them navigate the hiring process as it has evolved to include AI. 

Frequently Asked Questions

Does AI replace human decision-making in hiring?

In responsible hiring processes, no. AI is designed to support human decision-makers by surfacing relevant signals, scoring assessments, and ranking candidates, but final hiring decisions should always involve human review. If an employer has removed humans from the process entirely, that’s worth asking about.

Can I ask to opt out of AI screening?

In some jurisdictions, yes, and regardless of local law, you can always ask. Some employers will offer an alternative process. Others may not. Knowing your rights in your specific location is worth researching, particularly if you’re applying in New York City, Illinois, or other states with active AI hiring legislation.

Does AI screen out candidates automatically, with no human review?

It depends on the tool and the employer’s process. Some AI tools are used to rank and prioritize candidates for human review; others are set to automatically advance or reject based on scoring thresholds. This is one of the most important questions to ask a prospective employer.

What if I think AI screened me out unfairly?

Start by asking. Request information about the criteria used and whether a human review is available. In jurisdictions with AI hiring regulations, you may have additional recourse. Documenting the interaction by asking what tool was used and at what stage you were screened out at is useful if you believe the process was discriminatory.

How is my data handled after I apply?

This varies by employer and tool. You have the right to ask how your data is stored, how long it’s retained, whether it’s shared with third parties, and whether it will be used to train AI models. A reputable employer using responsible AI tools should be able to answer all of these questions clearly.