Apply. Wait. Disappear.
How Technology is negatively impacting recruitment & Talent management for candidates.
The role looked right. The right level, the right sector, the kind of organisation where the work would mean something beyond a quarterly target. I clicked Easy Apply. Uploaded the CV. Filled in the fields. It took less time than making coffee.
Then I waited.
I left a senior technology role to find something with genuine purpose. I was not in a hurry. I had work to keep me occupied — writing, advisory work, things worth doing while I looked. I applied selectively, for roles I was qualified for and genuinely wanted, because that is the sensible approach. Apply where you can add something real. Don’t spray. Be considered.
But the response rate does not match the logic. Applications go out. Acknowledgement rarely comes back. Not rejection — silence. The market has not said no. It has said nothing.
Two things are happening that I could not see from where I was sitting.
The first is volume. The systems handling most of these applications are processing hundreds of them, sometimes thousands, per role. A significant proportion are not written by the people submitting them. Other candidates, knowing the odds are poor, are using AI tools to auto-generate CVs, pattern-matching the job description in thirty seconds and applying to everything that moves. The platforms make this easy. Volume feels like effort. The tools assist.
The second is screening. Before a human reads any of these applications, many will pass through an AI screening tool. The ICO’s March 2026 report into automated decision-making in recruitment found that many employers using these tools do not acknowledge they are using them at all. The employer may not fully understand it either. The tool was purchased. The default settings were left on. Decisions are being made about people without those people knowing what criteria were applied.
What the screening model is working from, trained, in part, on data from the flood it is now trying to sort, is not good signal. It is noise taught to look like signal. My application, considered and specific, written by a person with thirty years of direct experience, looks like text. The AI-generated application also looks like text. The filter has no mechanism to tell the difference.
Here is what this has become: a market designed to serve the platform rather than the candidate, in which that design has created a feedback loop now breaking it for everyone, including the employers it was supposed to help.
The problem is not that candidates are using AI to apply, or that platforms are collecting data. The problem is that neither was governed before it scaled, and nobody is governing it now.
The consent moment is embedded in that click. What pressing Apply actually sets in motion: my CV held indefinitely in a database I cannot access or audit. My profile data used to train AI models. That data shared with third parties whose names are not disclosed. LinkedIn’s AI training default, enabled by default from November 2025, covers both profile and resume data. Opting out is possible. Finding the setting takes effort. Understanding what has already been contributed takes more.
The frictionlessness is not incidental. It is the design.
Between August 2023 and May 2024, the ICO audited AI recruitment tool providers. Nearly 300 recommendations came out of it — all accepted or partially accepted. The findings were not edge cases. Tools were scraping LinkedIn and social media to build candidate databases without candidates’ knowledge. AI was inferring gender and ethnicity from names and photographs without lawful basis. Tools were allowing employers to filter on protected characteristics. Data was being retained indefinitely after roles closed.
The companies were not required to stop operating during remediation.
In February 2026, the Data (Use and Access) Act removed the blanket prohibition on fully automated hiring decisions. Employers can now screen entirely by algorithm, provided they disclose this and allow candidates to challenge the outcome. The ICO’s March 2026 report found that many employers do not disclose this. The challenge route exists in legislation. In practice, for most candidates, it does not exist at all.
What this means: the silence that follows most applications is not a market that has seen you and decided against you. It is a market that may not have seen you at all. Your application stopped somewhere in a chain of automated systems, none of which will tell you where. That is not the candidate’s failure. The candidate followed the instructions. I followed the instructions.
The system I have been participating in was presented to me as a talent market. What I have actually been doing is feeding a data market.
Does it help me find the right role? Not in any functional sense. It gives me access to listings in exchange for data — profile data, CV data, behavioural data — and provides no feedback that would make the next application more effective. The platform benefits from my participation regardless of whether I get a job. I do not.
Does it add something that was not there before these tools arrived? The proposition was that AI screening would find better matches faster. What it has done instead is enable a flood of low-quality applications assembled by other AI tools, contaminate the training data the screening models run on, and produce filters that are getting worse, not better. More tools. Less signal.
Does it respond to me — to my specific experience, the roles I have actually held, the thing I can offer to the right organisation? It does not. It cannot. The system processes my application identically to the one assembled in thirty seconds from a job description. It applies the same parameters to a senior leader applying selectively and a graduate running an auto-apply script. The silence that follows both is identical.
The individual is invisible to the system they have paid with their data to access.
Finding a new role in today’s world has fundamentally changed. Technology is an integral part of the end-to-end, but it should not be the entirety - you are hiring people not technology so make recruitment and talent management a human first & human led business activity.
Think about:
The last time you pressed Easy Apply, did you know where your CV went, and for how long it would stay there?
If an AI tool screened your application before any human saw it, would you know? And if you knew, could you do anything about it?
If candidates are flooding the market with AI-generated applications, and platforms are using AI to filter that flood, what is left of the signal the whole system was supposed to find?
Is the right response to a broken market to apply harder? or to ask who designed it this way and why?
The recruitment market will not fix itself. The incentives running it — data maximalism, volume, frictionless extraction — are working exactly as intended. Candidates are paying the cost of a system that was not designed with them at the centre.
That is what The Next Evolution is about. Not that technology is bad. That the design question, who is this actually for, in whose interests does it operate, almost never gets asked at the moment it matters, which is before the system is built and scaled.
You’re reading The Next Evolution by Neil Catton, articles that explore the human world and the intersection of technology, they try and ask difficult questions - not to scare - but to inform. If someone forwarded this to you, you can subscribe free at neilcatton.substack.com.
Neil Catton is the author of The Next Evolution, The Cognitive Crucible and The Shadow System - available on Amazon, and writes at the intersection of technology, ethics, and human purpose.