This may be one of the most important articles we’ve written. To do it justice, we have dedicated five times our regular budget for an article, and it took about nine times longer to produce. And we sincerely hope you read it with that level of attention.
Let’s talk about how AI is changing the way you get jobs…
TL;DR: The Old Rules No Longer Apply
Make no mistake: going forward, every aspect of every interaction between you and a potential employer will have some element of AI integration.
This is a massive deal, and it’s going to impact you in ways you might not expect.
Good News: Hiring Pipeline Won’t Be Completely Replaced by AI
Yes, you’ll still get to talk to and interact with people, meaning, everything we’ve taught you will continue to give you a clear competitive edge.
This is because, despite the rapid adoption of AI (artificial intelligence) and ML (machine learning) in recruitment, the hiring pipeline won’t completely turn into a bot filled customer service call center. Recruiters and HR professionals – in order to preserve their job security – will find many ways to justify their involvement in the hiring process.
Human involvement will also remain crucial in later stages of the hiring process, particularly when it comes to final decision-making and cultural fit assessments. AI will assist, but it won’t replace the hiring pipeline.
Bad News: Every Aspect of Your Job Search Will Get Worse
The downside? Every other part of the job-seeking process is about to get more difficult!
AI is designed to optimize efficiency for corporations, not to make your life easier. From the way your resume is screened to how your interviews are conducted, AI will introduce new layers of complexity, impersonality, and challenges.
Let’s be crystal clear… There’s absolutely NOTHING coming down the pipe that benefits workers or professionals – only more ways for companies to leverage technology to their advantage and make the job market significantly more competitive.
Prepare yourself: The recruitment landscape is shifting, and it’s not in your favor…
The New Reality: AI-Driven Recruitment
Artificial Intelligence (AI) and Machine Learning (ML) in recruitment are sold to us as “modernization” and “efficiency.” Furthermore, these technologies are also presented as tools to remove bias, improve hiring outcomes, and enhance the candidate experience.
Of course, all of that is narrative control (some are outright lies as you’ll learn below), not the primary drive behind the AI revolution in recruiting…
The primary drive behind why companies are adopting AI in recruiting is simple: to save money.
The Real Motive: Cost-Cutting, Not Candidate Care
It’s fundamentally about reducing expenses, which actually makes the AI takeover of recruiting unstoppable – corporations have always, and will always, cut costs whenever they can get away with it.
By automating tasks that were once handled by humans – such as screening resumes, scheduling interviews, and conducting assessments – companies get significant cost savings, particularly if they are dealing with high volumes of applicants.
All other factors being equal, this type of cost savings by AI upgrade would have been fine. Unfortunately, all other factors are not equal..
The Dark Side of AI-Driven Recruitment
These AI systems, despite their tall promises and genuine efficiencies, also come with their own set of problems…
They are opaque, meaning even those that wrote the software might not definitively know how decisions about your application are being made. (A fundamental limitation of neural networks.)
The algorithms can also be error-prone, potentially discarding qualified candidates due to poorly understood criteria, bias in the training data or even flawed interface inputs.
Let us not forget, they are also a privacy and a data security hazard for applicants – how would you like the video recording of “that one time you performed poorly on a job interview” to influence all your future job prospects, because the AI company shares “common telemetry” between their clients or creates permanent candidate profiles?
The Pervasiveness of AI in Recruitment
Before we keep going, let’s get one thing straight…
We cannot blame corporations, especially larger corporations handling thousands of resumes, for using AI. This type of automation is not just a convenience, it’s a necessity. And as a result of this necessity, AI has become pervasive.
In fact, nearly 99% of Fortune 500 companies filter candidates through a major Applicant Tracking System (ATS) like Workday, Taleo, Jobvite, Greenhouse, or Lever (source).
These systems are often deployed throughout multiple stages of the hiring process, including everything from skill appraisal to personality assessments, to even monitoring your body language during an interview or reviewing your social media accounts. (We’ll explain each in detail below.)
What This Means for You
Going forward, you’re not just applying to a company; you’re applying to an algorithm.
This means you need to be more strategic about how you present yourself, ensuring your application materials are capable of outsmarting AI systems and that you’re aware of the digital footprint you leave behind.
Of course, we still recommend you bypass these HR gatekeepers including all AI systems altogether.
But if you have to interact with AI, it’s best to know how to do it right…
And in terms of doing it right, the devil is in the details…
Let us first go over why companies love using AI in their recruitment and HR pipelines. This will give you insights about their motives and what they really care about, giving you clear discrimination around what is important and what can be ignored.
Once you understand the motives behind this AI takeover, the specific ways in which companies use AI will make a lot more sense, and you’ll naturally understand what to do about it, and even how to use these changes to your advantage.
Why Companies Love AI: It’s Not About You
There are a number of deeply ingrained as well as structural reasons behind this AI revolution in recruiting…
The Good: Saving Money & Managing Labor Shortages
The main attraction for companies? Of course, as we already mentioned, it is cost savings.
AI can significantly reduce recruitment expenses by automating routine tasks that human recruiters used to handle. From screening thousands of resumes to scheduling interviews, AI can do it faster and cheaper.
But there’s another potential benefit that’s harder to dismiss: AI also helps companies connect with talent they would have otherwise missed…
Imagine applying to a company where you’re a great fit but you’re applicant #1143. A human recruiter would never get to your application. An AI system, however, will process it, and if you’re truly a strong candidate (or more accurately, a candidate that AI sees as strong), it will put your application right at the top.
(Pro Tip: This means, if you have a high-value track record, if you use the Language of Value, or if you have an impressive pedigree, your options are going to expand, especially with large and successful organizations.)
The Bad: AI Bubble and Hype
There are a lot of AI peddlers, eager to sell their products, while promising companies they can revolutionize their hiring process. This bubble, and overzealous marketing campaign is one of the major reasons behind the AI takeover of recruiting: vendors are saying exactly what companies want to hear.
But… Many of these promises are, as one would expect, oversold.
The reality is that not all AI systems are created equal, and some are downright ineffective or misleading. Companies are buying into the idea that AI is the future without fully understanding the limitations or potential downsides.
Regardless, since companies are operating as if the hype is objectively true, we also need to analyze it as such…
Here’s what companies think they are getting by using AI:
The Motive: Behind AI Adoption
- Cost Reduction: Already covered..
- Speed: AI can process thousands of applications in minutes – something no human recruiter could ever do. Companies want speed, because they believe good job seekers stay on the job market for merely 10 days.
- Control and Surveillance: AI gives companies the ability to monitor and analyze employee behavior and performance data at scale.
- Bias Reduction: Companies love the narrative of AI reducing bias and people buy it.
- Profit, Profit, Profit: The AI bubble is lucrative. Getting corporate SaaS clients is a goldmine, and companies have swallowed the story hook, line, and sinker. According to Forbes, 84% of business leaders believe AI will be the best way to acquire talent going forward.
- Lazy HR: Don’t be confused – using AI in recruiting is not necessarily about doing it better, it’s about doing less. HR departments don’t want to sift through resumes or make tough decisions. AI lets them outsource these responsibilities to a machine. And even better: when things go wrong, they can just point to the algorithm and say “The robot said we should hire him, how could we have known that he was going to show up drunk one weekend and delete the server?” It’s the ultimate cop-out.
Now that you understand the motives behind this rapid adoption, we can go over how specifically this adoption is unfolding…
How Companies Are Using AI Tools in Recruitment
Here’s how companies are using AI tools to transform – and in some cases, undermine – traditional recruitment practices.
Eliminating Busy Work for Recruiters
1. Writing Job Descriptions
AI tools can now generate job descriptions based on a few keywords and a basic understanding of the role. While this might save time, it can also result in vague or overly generic postings.
2. Job Postings
AI also plays a significant role in publishing and distributing job postings. Recruiters can use AI to post jobs to broader audiences, and do so faster.
3. Data Entry and Administrative Tasks
AI is also used for data entry and administrative work. For instance, AI tools can predict the salary range from a job posting (source) or automatically populate databases with candidate information, cutting down on tedious tasks that recruiters would otherwise have to manage manually.
All in all, the usage of AI for eliminating busy work for recruiters is a win for everyone, and does not hurt candidates. Unfortunately, we can’t say the same about the rest of our examples…
Candidate Sourcing & Surveillance
1. Candidate Recommendations
One of the primary uses of AI in recruitment is “candidate sourcing,” where AI systems recommend potential candidates to recruiters.
These recommendations are based on algorithms that analyze vast amounts of data, including resumes, professional networks, and job boards. The idea is to surface candidates who might not have applied but are a good fit for the role.
While this can help recruiters discover hidden talent, it also means that candidates who don’t align perfectly with the algorithm’s opaque criteria might never get a chance to be considered, no matter how qualified they are. Just as algorithms determine what you see on social media, algorithms are now determining if your applications get considered.
2. Predictive Analysis
Predictive analytics, a form of AI that uses data mining and modeling techniques, analyzes a candidate’s resume, work history, and other data points to estimate their fit for a position. By comparing a candidate’s profile to data on “successful” employees in similar roles, AI can flag candidates who are statistically more likely to perform well.
This, on the surface, saves recruiters time and effort, but it also raises concerns about how much a candidate’s future potential can be accurately predicted by past performance and how much valuable context might be overlooked.
3. Social Media
AI-driven tools scan social media platforms to identify potential candidates who match the job requirements. These tools analyze profiles for relevant skills, experience, and even personality traits that align with the company’s needs (source).
While the visibility of talent is a plus… This type of AI usage also means your social media is under constant surveillance, whether or not you realize it.
Make no mistake: the same AI technology used for sourcing candidates from social media is also employed for screening and gatekeeping. And even if a company doesn’t find you through social media, they will – manually as well as through AI – analyze your profiles for any red flags. (Problem being: while manual misses things, AI doesn’t miss anything.)
(Pro Tip: This makes it all the more important for you to sanitize your online presence, as we emphasize in Launch Your Career. What you post online could make or break your chances of getting your dream job.)
Applicant Screening
1. Cover Letter Filtering & Sentiment Analysis
AI reads cover letters and other written materials to gauge the overall tone of the text. Sentiment analysis can determine whether your cover letter is positive, negative, or neutral, and this can influence whether you make it to the next stage.
If the AI decides that your tone isn’t sufficiently enthusiastic or doesn’t align with what the company is looking for, you could be eliminated before a human ever sees your application.
2. Resume Filtering
AI also plays a significant role in resume filtering. These systems go beyond scanning resumes for keywords. They can identify relevant experience and qualifications that match the job description.
3. Chatbots & HR Emails
Those friendly back-and-forth emails you have with HR? Chances are, you’re no longer talking to a human but to a chatbot.
AI-driven chatbots are increasingly being used to handle initial communications with candidates, answering questions, and providing updates.
(Pro Tip: Our Warm Application Process is designed to get you interacting directly with the hiring manager. If you’re applying through or interacting with AI-driven gatekeepers, you’re setting yourself up for failure.)
4. Online Interviewing
You record your answers to pre-set questions, and instead of a human evaluating your responses, AI algorithms analyze everything from your word choice to your body language and facial expressions.
These AI-based video assessments are literally designed like lie detectors, scrutinizing your every move to determine if you’re a fit for the role. This technology is used to measure not just what you say, but how you say it – your expressions, tone, and even micro-expressions that might indicate nervousness or dishonesty (source).
Skill Assessment
AI has also expanded its reach into skill assessment, where it promises to provide a more objective and data-driven approach to evaluating candidates.
Of course, the effectiveness and accuracy of these AI tools are far from guaranteed. While they offer a sophisticated veneer, and a solid “cover your ass” alibi against hiring mistakes, the reality is that AI’s ability to truly understand and assess human skills – especially soft skills – remains unproven.
Regardless of these facts, some companies are selling, and other companies are buying the following skill assessment services.
1. Capability & Qualification Assessment
Companies like Eightfold.ai claim to use billions of profiles, global data points, and over 1 million unique skills to offer data-driven insights into a candidate’s abilities. They promise features such as “AI-powered talent intelligence to drive retention” or “Widen the talent pool and hire faster.”
If we strip the corporate-speak, what they are selling is AI driven skill analysis of individuals, both for recruiting (outside of your company) and for managing (inside of your company).
Meaning: AI models are going to analyze your skills and determine your “capabilities”.
2. Soft Skills and Personality
AI also attempts to evaluate soft skills and personality traits, as well – aiming to match candidates with job descriptions and company cultures. Systems like Talentprise use online assessments to measure competencies and personality traits, presenting them as objective evaluations. (They sell “AI Headhunting” to employers and “Endless Job Vacancies” to candidates.)
Here’s the problem: Humans already struggle to clearly define, measure and assess soft skills and personality traits accurately, and AI is no better. Further complicating the matter, AI is a black box that spits out results based on algorithms trained on data that might not even be relevant to the role or the specific situation!
Think of it like this: If your lead recruiter comes to you and says “this sales director candidate is too much of an introvert for this role”, you’d ask them “why do you think that” and expect a clear, objective, measurable, falsifiable explanation.
With AI, you don’t even get to see the candidate, let alone ask it “why do you think this candidate is a bad fit?”. And you’re definitely not getting a worthwhile, objective, measurable, and falsifiable justification to it’s choice. All you get is a list of candidates the AI likes, and many lists of candidates AI discards – which you never get to see.
Wasting Applicant Time
All of the above is bad enough… But we’re not done yet!
One of the most troubling trends is the significant amount of time wasted by job seekers due to AI in the recruiting process. Since AI driven time waste does not cost anything to companies (such as recruiter time), it gets out of control.
In fact, it is so out of control that we posit: Any collective time savings that AI might provide is not only offset but entirely overwhelmed by the excessive amount of time applicants are forced to waste navigating these additional artificial hurdles. (Imagine: Jenny in HR saves 100 hours per year due to AI shortcuts, while all the applicants collectively waste an additional 7000 hours – that’s bad for humanity.)
Here’s how it works…
1. Chatbot Chatter: The Illusion of Engagement
Recruiters claim that AI can keep qualified candidates engaged by offering constant contact through chatbots. They argue that this helps build relationships even with passive candidates, as chatbots send personalized messages at various stages of the recruiting process. According to Recruiter.com, these automated interactions are also marketed as a way to free up recruiters to focus on “essential issues.”
But let’s be clear: this “engagement” is a one-way street, designed to make applicants feel like they’re getting attention when, in reality, they’re just generating data points for the company’s AI systems. In practice, candidates are left talking to machines, wasting their time on back-and-forth exchanges that ultimately lead nowhere.
(Pro Tip: And yet again, this is why the Warm Application Process becomes crucial – if you’re relying on AI-driven interactions, and interacting with gatekeepers, you’ve already lost. You’re wasting your time and energy.)
2. Gamification: The Newest Time Sink
A particularly insidious development in AI recruitment is the use of gamification in candidate assessments.
And no that’s not a joke!
They unironically pitch gamification of the hiring process as a “fun” and “engaging” way to attract and assess candidates, turning the job application process into a supposed “game”. In fact, organizations point to gamification as the future of recruitment, with candidates being asked to participate in games that supposedly assess their skills and fit for the role. Companies also claim that these games promote their employer brand and offer insights into what the role is really like.
However, the reality is that gamification ends up becoming just another way to waste your time…
These “games” assess arbitrary skills that may not be directly relevant to the job. They can also be incredibly stressful, requiring candidates to perform under pressure – without any pay or compensation – in a format that feels more like an arcade game than a professional assessment.
Even the instructions given by companies to “take time to understand what is being assessed” and to “find a quiet place to focus” when going through their “games” is telling…
It reveals how much responsibility is placed on the candidate to jump through these hoops just to prove they are worthy of consideration. Meanwhile, recruiters sit back, letting the AI and gamified assessments do the work for them, further distancing themselves from the human element of hiring.
OK. OK… You get the idea…
We have a very low opinion of this AI revolution in recruiting, both in terms of the corporate intent, as well as, in methodology.
But… At the end of the day, we live in a capitalist system seeking ever improved efficiency (and with good reason), so…
Before jumping to any conclusions, we should consider if these new applications of AI are making a difference in hiring outcomes…
Does AI Actually Improve Recruiting?
Let’s dive into the claims about AI’s supposed improvements and see if they hold up under scrutiny.
More Attention to Qualified Candidates? Yes.
Companies like Starbucks, Hilton, and Audible have reported a 10% increase in the number of qualified candidates applying for positions after integrating AI into their recruitment processes. According to Talentprise, this improvement is largely due to AI’s ability to weed out unqualified candidates, allowing recruiters to focus on those who are more likely to succeed in the role.
Not bad… AI looks like it can help with the filtering problem.
However, this measurement is one sided and there’s definitely hidden opportunity cost…
While AI-driven systems will filter unqualified candidates away, in that process, they will inevitably exclude potentially great candidates who don’t perfectly match the algorithm’s predefined criteria. Especially individuals with non-traditional backgrounds or unique skills that don’t fit the typical mold (reducing the diversity and creativity within teams is bad for the bottom line).
This is not to say that qualified candidate filtering doesn’t work. It does. And it will get better in time.
But this is to say that, qualifications, pedigree, and traditional assessment of candidate capabilities will experience a premium over the next few years…
Better Turnover and Reduced Attrition? Perhaps.
Another claim made by proponents of AI in recruitment is that it leads to better employee retention and reduced turnover.
AI tools like those from Interviewed and SkillSurvey gauge a candidate’s fit and predict their behavior on the job before their first day. These tools analyze a candidate’s responses to behavioral questions and compare them to data from past hires to predict turnover rates and performance.
Whether this is working or not, is… Inconclusive.
Bias-Free Recruitment? Not So Fast…
The promise of bias-free recruitment is also one of the more appealing aspects of AI-driven hiring systems. In theory, AI should be able to eliminate the prejudices that human recruiters might bring to the table.
However, the reality is far more complex, and often, these systems end up perpetuating the very biases they were designed to eliminate!
It’s Not Actually Bias-Free
The world is filled with news about AI mishaps…
A striking example of this was when AI systems, including those used by major tech companies, infamously misclassified images of Black people as gorillas – a terrifying reminder of the racial biases that can be embedded within AI algorithms. This incident, reported by the Wall Street Journal, illustrates how AI is as good as the data it’s trained on. And as of today, the data it’s trained on… well…
It’s the Internet!
By the way, these types of bias issues are not happening because of racist companies. Far from it.
In fact, even companies like Google, which are explicitly anti-racist and invest heavily in diversity, are not immune to these problems. Google’s efforts to foster an inclusive environment are well-documented, as seen on their Belonging page.
The AI companies are not racist. The data is.
The datasets used to train AI systems are often riddled with the same biases present in the broader internet and society. As AI systems learn from this biased data, they inevitably carry those biases into their decision-making processes.
The exact same process happens in AI tools used for recruiting.
Research published by the National Bureau of Economic Research (NBER) has shown that AI systems can discriminate against job applicants with Black-sounding names. And a study covered by Forbes confirmed these findings, demonstrating that resumes with Black names are often subject to bias during the hiring process.
Perhaps the most famous example of AI failing to deliver on its promise of bias-free recruitment is Amazon’s failed experiment with a machine-learning hiring tool. Amazon discovered that its AI system was downgrading resumes from women: The system had been trained on resumes submitted over a decade, during which men were more frequently hired than women. As a result, the AI learned to favor male candidates, effectively reinforcing the gender bias it was supposed to eliminate.
Not good at all. In fact. Outright bad.
A Long Road Ahead
The harsh truth is that AI-driven recruitment is still in its infancy when it comes to eliminating bias. It will likely take years, if not decades, to refine these systems to the point where they can truly offer a bias-free recruitment process.
By the way, this doesn’t mean companies will stop using these tools!
Until these issues are fixed, companies and HR executives – many of whom lack the technical expertise to even discern these issues – will continue to grapple with AI’s limitations and the unintended consequences.
In other words: AI is just sufficiently good enough for their bottom line – that companies will use it more and more, regardless of the externalities…
What then are those externalities?
The Dark Side: How AI in Recruiting Harms Job Seekers
AI-driven recruitment systems can introduce new challenges and exacerbate existing ones, leading to significant harm for job seekers.
1. It Makes Applications Much Harder
Probably the biggest impact is that AI makes your job harder…
AI-driven recruitment significantly raises the bar at every stage of the application process. These systems require you to tailor your resumes and cover letters to align perfectly with what the algorithms are programmed to recognize. Keywords, formatting, and even the structure of your application become critical factors that can make or break your chances of getting noticed.
AI also introduces heightened scrutiny of your digital footprint. Many AI systems now crawl through your social media profiles, online portfolios, and other online information to assess you. This means that offhand comments, old photos, the games you play, or even the pages you follow will be analyzed and used against you. The digital traces you’ve left behind – whether intentional or not – become part of your application. Something you said years ago could come back to haunt you…
(Again, learn to sanitize your social media presence so that nothing you’ve posted is held against you by an algorithm that lacks context or nuance.)
Ultimately, AI creates additional hoops for applicants to jump through, making the process more arduous and less transparent.
Speaking of transparent…
2. Lack of Transparency
One of the most significant issues with AI in recruitment is its inherent lack of transparency.
By the way, it’s not like traditional recruiting is transparent. Try asking why you got rejected after applying to that Fortune 50 company, and you’ll experience the literal definition of “lack of transparency”.
Here, we’re not talking about external – job seeker facing – transparency. We are, in fact, talking about transparency internal to the company…
As mentioned earlier, AI systems are “black boxes,” meaning that even the developers and operators of the AI cannot fully explain how decisions are made. The opacity of these systems leaves everyone in the dark, where HR and hiring managers only get to interact with a set of “AI approved” candidates, without knowing exactly how that approval takes place.
This should sound alarm bells on a normal day, and that’s before you start considering malicious uses… (Think spots sold on the dark web so that your application bypasses all AI gatekeepers via backdoors, or using malware to subvert hiring across entire industries.)
3. Wild West Development
It is also worth noting that the development of AI recruitment tools is akin to the Wild West – largely unregulated and lacking independent oversight.
While software vendors are technically responsible for testing their tools and establishing guardrails, this process is often superficial and biased by commercial interests. As we explained earlier, for instance, while vendors claim that AI reduces discrimination in hiring, reality highlights “different facts”.
Forget about regulation; without, at the very least, rigorous independent testing, there is no way to guarantee that these tools aren’t perpetuating known and unknown problems…
4. Bias In, Bias Out
AI systems are trained on historical data, which is often riddled with the same biases that have plagued human decision-making for decades. The result is a system that reinforces existing inequalities such as prejudice against women, ethnic minorities, or people with disabilities (that discrimination is literally baked into the data.)
What’s worse is that these AI tools give companies a legal cover to employ such discrimination in their hiring practices! (We weren’t being bigots, the AI tool ignored all those resumes! We didn’t know. It just gives us candidates. We didn’t build it…)
You can see where this is going…
5. Dehumanization of the Hiring Process
At its core, recruitment is about understanding an applicant’s capabilities, potential, and cultural fit for a role.
Of course, AI tools are not capable of any of this.
Instead, AI-driven systems strip away this human connection, reducing candidates to mere data points. This dehumanization leads to a cold, transactional process where the nuances of individual applicants are lost, and genuine talent gets overlooked.
Before you get any chance at fostering a meaningful connection, AI requires you to jump through its mechanical, impersonal hoops, which can be both demoralizing and time consuming.
What to Do About It – Navigating the AI Recruitment Nightmare
As AI systems become more prevalent in the hiring process, it’s crucial that you adapt your approach to stay competitive. Understanding how these tools work and leveraging their limitations can significantly impact your job search success.
- (If You Are Sending Resumes) Prepare Your Resume for AI: Ideally, you should never send a resume prior to receiving an invitation to apply, which you get using our Warm Application Process. But… If you are somehow stuck and have no other option, it’s worthwhile to get your resume AI ready. Customize your resume for each application, and use the assistance of AI tools like ChatGPT to formulate your resume.
- We recommend using AI to give your resume a “job match score”, and modify it to get the highest job match score you can get. You do this by feeding your resume and the job description to AI, and asking it to score your resume in terms of how well it matches the job description from an “AI’s perspective”. Seeing how well a Large Language Model (LLM) interprets the proximity of your resume to the job description is useful. It leverages the common underlying architecture of AI systems, and it helps you “give the HR AI what it wants to see”.
- Also, avoid fancy layouts that can confuse AI parsers.
- Network Aggressively: Getting noticed is harder than ever. A personal referral can bypass the AI entirely, getting your application directly to a human decision-maker. Attend industry events, connect with recruiters, and don’t be shy about asking for introductions.
- Leverage Social Proof: Ensure your LinkedIn profile is up-to-date and aligns with your resume. AI often scrapes social media profiles to cross-verify information. Recommendations and endorsements on LinkedIn can act as social proof, adding credibility to your profile. Of course, LinkedIn is the bare minimum. To properly start playing the game, learn about personal branding.
- Prepare for AI-Assisted Interviews: AI is increasingly used in interviews, analyzing your facial expressions, tone of voice, and word choice. Practice speaking clearly and confidently, maintain good posture, and be aware of your body language. Here are a few crucial tips:
- Research the Technology: Before your interview, find out which AI software the company uses. Look up the program’s website and familiarize yourself with its features and requirements.
- Prepare Your Environment: Choose a quiet, well-lit space for your interview. Make sure your background is neutral and professional.
- Practice Your Responses: Focus on clear, concise responses and maintain a confident tone. Many AI systems assess not just the content of your answers but also your delivery, so rehearse until you’re comfortable with your answers.
- Dress Professionally: Even though the interview is virtual, dressing as you would for an in-person interview helps set a professional tone. Make sure you read the “Present Yourself Professionally” section of our interview guide for recent graduates, which covers everything starting from the basics.
- Don’t Underestimate the AI: Avoid treating the AI-assisted interview as a less important task compared to a traditional interview. The technology is often sophisticated and can assess your responses, tone, and even body language.
- Don’t Ignore Instructions: Pay close attention to any instructions provided by the AI system. These might include specifics on how to answer questions or how much time you have. Ignoring these can result in a poor evaluation.
- Be Aware of Data and Privacy: Before engaging in AI-assisted interviews or submitting personal information, seek clarity on how your data will be used, stored, and shared. Specifically, try to discover the following:
- Duration of Data Retention: How long will your video recordings and other personal data be kept?
- Access Control: Who has access to your data and video recordings?
- Third-Party Sharing: Will your data be shared with external entities?
- Consider Opting Out: This is a delicate dance, as asking to opt out when you have very little leverage and zero power could get you rejected. So.. It’s worth thinking this through… Regardless: You can request that your data and video recordings be deleted after the immediate hiring process concludes. Make it clear that you do not consent to having your data used for training AI models, marketing, or other purposes beyond the scope of the current recruitment. Whether you do this before or after the interview, before or after you receive an offer: we cannot give you definitive instructions because it really needs to be determined on a case by case basis. Be wise.
- Be Skeptical of “Fairness” Claims: When a company boasts about its AI-driven “fair” hiring process, take it with a grain of salt. Remember, these systems are only as fair as the data they’re trained on – and that data is far from perfect.
Conclusion: Adapt or Perish
AI and ML in recruitment are not going away.
They’re definitely here to stay, reshaping the job market in ways that may be beyond our control.
For job seekers, the key is to be vigilant, adapt, and whenever possible, outsmart the system.
By understanding the motivations behind AI adoption and finding ways to avoid jumping through AI hoops and interacting with hiring managers directly, you can navigate this new landscape without falling victim to its pitfalls.
In a world where companies prioritize profit over people, you have to look out for yourself.
Stay informed, stay vigilant, and never take the AI-driven hiring process at face value.
Your career depends on it.