A few weeks ago, I wrote about the dangers of over-optimising AI in social media, arguing that it will undoubtably destroy value rather than create it.
So we have covered, Robots chatting away on social media to other Robots, Robots having their own unique ID cards, and today it’s robots applying to other robots for jobs.
The madness continues.
How AI is Destroying Online Recruitment
Many companies use Applicant Tracking Systems (ATS) to manage, prioritise, and score job applications.
Originally designed to assist HR teams in evaluating candidates, these systems are now driven by artificial intelligence as ATS vendors desperately try to stay relevant and firmly position themselves on the AI bandwagon.
ATS systems broadly work by utilising job-scoring algorithms that evaluate candidates against job descriptions or key metrics that the recruiter defines as desirable in the role, forwarding only the ‘best’ candidates to recruiters.
It sounds great, right?
But here’s the catch: the AI system of course will miss out on candidates who, although lacking a perfect CV, could be incredibly passionate and potentially great hires.
Why?
Because some HR teams, in their laziness or lack of resources, have outsourced critical decision-making to AI, bypassing the nuanced judgment a savvy HR manager would provide.
In this case the concept of “filtering” candidates sounds like a great business case, but as you will see it’s complete BS.
The Problem With AI Recruitment in the ATS Processes
As AI takes over more processes, many people are losing their jobs, this is evident.
People in desperation to find employment are applying for any work on the internet.
How are they applying for as many jobs as possible at scale?
They use Artificial Intelligence to apply.
Now as anyone will tell you, getting hired especially in a crappy market is a numbers game.
Here’s a simplified version of what happens next:
- The job seeker uses AI to find as many jobs as possible, because they are desperate.
- The jobseekers AI Robot reads job descriptions and generates a perfectly tailored CV
- The ATS AI Robot in the hiring organisation scores these as high potential.
- The candidate lands an interview after navigating multiple AI scoring systems.
- It becomes painfully clear they know nothing about the job they are being hired for
- The recruiter has no candidates and struggles to fill roles.
Companies waste resources reviewing unsuitable candidates, and the applicant spends time and energy chasing jobs they’re not qualified for.
Essentially, AI is consuming electricity, only to destroy value rather than create it.
Once again robots are talking utter sh*t to other robots whilst humans and businesses pay through their nose for the pleasure.
The Vicious Cycle
This cycle leads to AI-generated CVs flooding the system, creating more work for recruiters who now have to sift through even more low-quality applications.
The once straightforward process of applying for a job, being interviewed by a human who can see potential, and getting hired has turned into a back-and-forth of AI-generated nonsense, draining the electricity and resources we can’t afford to waste.
As a consequence, many talented individuals have walked away from the online job application process completely.
They’re reverting to the old-school methods of directly contacting CEOs or HR directors, and using personal networks.
LinkedIn has become notorious as a terrible platform for job seekers and recruiters alike. “A waste of time for everyone” was one insight from an HR leader I spoke to this week.
HR managers who once relied on AI and online posts are now drowning in poor-quality applications that their systems incorrectly flag as suitable.
So What Is The Fix?
AI is indeed disrupting the job application process, but in doing so, it’s destroying value.
It is nothing less than a great “enshitfication” of the online job market, expedited in its decline by AI.
Job seekers can now use AI to apply for thousands of jobs they don’t even want, every single day. The model is at best wonky, at its worst broken.
The biggest part of the development budget for ATS platforms in 2025?
**Investing in AI Detection -**to discount AI generated CV’s
The biggest budget allocation in job application software in 2025?
Avoiding of AI Detection - to generate more convincing CV’s
Where is the value?
This AI sh*t-show is now forcing recruiters to return to more traditional methods, recruitment days and networking events, to find real talent are in resurgence.
Certainly in this case over-optimisation has set recruitment back in time.
At least for now, AI is eroding value from both sides of the equation.
The recruiter and the jobseeker are both loosing out ultimately we have over-optimised a once simple and effective process.
Don’t agree? Let me know in the comments.
Who Am I?
I’m Steve, I run a Deep Tech venture studio called WizzWang.
Working with AI, cybersecurity, and quantum start up companies, helping them define and enhance their value propositions.
Further Reading
[AI is becoming indispensable to job seekers]
[ Job hunters flood recruiters with AI-generated CVs ]
[19,167 Cover Letters Generated! with AI ]
Still Here?
The Hidden Costs of Over-Reliance on AI in HR
AI has transformed the HR landscape, especially with the widespread adoption of Applicant Tracking Systems (ATS). Promising efficiency and precision, the reality is more complex.
Over-reliance on AI can strip away the nuanced human judgment essential in effective HR practices. When companies lean too heavily on AI, they outsource to an incompetent robot, overlooking the candidate attributes that a skilled HR professional would recognise.
AI’s Unintended Consequences and Bias
AI algorithms are only as good as the data they’re trained on. Unfortunately, historical hiring data often carries biases that AI systems unknowingly perpetuate and can’t shake free of.
This can lead to discriminatory hiring practices, where certain groups are unfairly disadvantaged, or reverse discriminatory practices where someone with any form of social categorisation gets them the job even though they may be unqualified.
Companies must actively monitor and adjust AI systems to mitigate these biases, ensuring a fair and equitable recruitment process.
Or better still get off them, or use them later in the evaluation process. AI does hold promise in testing, psychometrics and matching - but only if its considering a person. Not another robot.
The Complexity and Cost of AI-Driven ATS Implementation
Deploying an AI-powered ATS isn’t as simple as plugging in a new software tool. It requires significant investment in terms of money, time, and expertise.
Companies underestimate the complexity of integrating these systems into their existing HR processes, leading to inefficiencies and spiralling costs for an inferior end result.
The allure of AI’s potential can often blind companies to the practical challenges of implementation and operation. Failing to think about second and third order impacts of rash decisions driven by a short term strategy favouring financial optimisation over sustainable quality.
Inaccurate Candidate Screening: The Downside of Automation
AI-driven ATS are designed to screen candidates based on predefined criteria. However, these criteria can be overly rigid, causing the system to dismiss candidates who might be a perfect fit if assessed by a human.
The result? Missed opportunities and a talent pool that’s unnecessarily narrowed, all because of an over-reliance on automated screening.
Resistance to AI in HR: A Barrier to Innovation
Despite the potential benefits, many HR teams are resistant to AI-driven changes. This resistance stems from a fear of the unknown, a lack of understanding of AI’s capabilities, or concerns about job security.
Overcoming this resistance requires not just technical training, but also a cultural shift within HR departments to embrace innovation where it ads value while maintaining the human element in recruitment.
Losing the Human Touch in Recruitment
One of the biggest criticisms of AI in HR is that it makes the hiring process feel cold and impersonal. Job candidates often report feeling like they’re just another number in an algorithm, which can discourage top talent from engaging with companies.
A successful HR strategy balances the efficiency of AI with the warmth and empathy that only humans can provide. Use AI to get people to come to your open days, don’t be a lazy ass and use them to screen candidates or you will get a bunch of AI generated applications at the top of your pile not suited to the role.
The Flood of Low-Quality Applications: A New Headache for Recruiters
AI systems make it easier than ever for job seekers to apply to hundreds of jobs with the click of a button. This convenience, however, leads to a significant increase in low-quality applications. Recruiters are now spending more time than ever sifting through irrelevant “shortlisted” applications, which can negate the time-saving benefits that AI was supposed to bring and in many cases increase the costs and lessen the effectiveness.
Data Privacy Concerns: Protecting Sensitive Information
AI and ATS systems require large amounts of personal data to function effectively. This raises significant concerns about data privacy and security. Companies must ensure that they have robust security measures in place to protect candidate information. Failure to do so can lead to legal ramifications and damage to the company’s reputation.
95% of companies don’t have any type of data security within their ATS platform other than that incorporated into the product by the provider.
Navigating Legal and Compliance Challenges
The use of AI in HR isn’t just a technical challenge; it’s also a legal one. Misuse of AI tools can lead to legal issues, particularly around discrimination and bias. Companies need to be aware of the legal implications of their AI-driven HR practices and ensure they are compliant with all relevant regulations. This requires ongoing monitoring and adjustment of AI systems.
Over-Optimisation in HR Processes
In the quest for efficiency, companies can sometimes go too far in optimising their HR processes. Over-optimisation can lead to a reduction in the quality of hiring decisions, as AI-driven processes may prioritise speed over depth of assessment. Companies need to strike a balance between efficiency and thoroughness to avoid these pitfalls.
The Danger of Dependency on AI-Generated Content
AI is increasingly being used to generate CVs and job applications, which can lead to a dilution of the quality of candidates. When AI creates a perfect CV tailored to ATS criteria, it may not reflect the candidate’s true skills or experience. This can result in mismatches between candidates and job requirements, leading to frustration for both parties. My suggestion, switch it off, drive people to meet you at hiring days and events - for important hires go old school and hire a decent recruiter to get the job done for you.
Dehumanisation: The Final Frontier of AI in HR
As AI continues to play a larger role in HR, there is a growing concern about the dehumanisation of the hiring process. The lack of personal interaction and the reliance on whacky and biased algorithms can make candidates feel like they’re part of a production line rather than individuals with unique talents and potential. This dehumanisation leads to a loss of trust in the recruitment process, brand damage to your company and a sh*t reputation very quickly. Be very careful how you use it. Don’t believe the sales hype.
Conclusion: Why Agencies Might Be the Solution
While AI offers incredible efficiencies, it is not a silver bullet. The nuances of recruitment, the need for empathy, and the complexity of human potential is going to pay higher dividends than a 10% improvement in your HR efficiency - for companies struggling to strike this balance, partnering with an HR agency might be the best way forward.
About me
Helping leaders in Cybersecurity, Quantum, and AI drive high-impact growth, stronger valuations, and better exits.
📌 Director of the world’s largest Quantum Cybersecurity community (700+ members), connecting top experts in Quantum, AI, and Cybersecurity.
📌 C-suite executive with a proven track record in scaling tech, finance, and asset finance businesses across EMEA & APAC.
📌 Former network engineer with deep expertise in computational Root Cause Analysis & Causal Reasoning, applied in military and telecom environments.
📌 Member of the Institute of Directors, European Corporate Governance Institute, and Royal United Services Institute for Defence & Security.
