De Facto Automation and You - Jobseeker Basics XII

Greg Wyatt • December 23, 2025

This is a new chapter in the 2026 edition of A Career Breakdown Kit.


I find I've had some cognitive dissonance this year in considering the advice I share that often contradicts the experiences job seekers have. It's not because either of us is wrong - it's because we're discussing different layers in the conversation.


So while the amendments to the book are primarily around technological updates, the additions are around adding substance and reframing experiences, to help readers understand what happens, why they happen, and what can be done differently.


But also why the narrative of 'the ATS is rejecting you' is smoke and mirrors, and why it can set you back from actions that matter, by focusing on the wrong things.


The article remains a work in progress, as I do the final edits before book publication.


Chapter 4 - De facto automated rejection and you


When there’s any discussion over Beat the Bots, job seekers often assume they are unfairly treated, while people from the recruitment profession deny it happens at all - “that’s not how the ATS works”, “we don’t use AI that way”, and so on.


The best objection I see to the common recruiter stance is, “What does it matter how we are rejected, if we were never fairly considered?”


That question is the heart of this chapter, and to answer it, I need to propose a new term:


De facto automated rejection.


Definition: where an element of a recruitment process leads to an application being either rejected or not considered, irrespective of capability, contribution, or potential alignment.


That may sound an awful lot like Automated Rejection, yet it isn’t the same thing.


Examples:


  1. No application after number 100 considered
  2. Illegal discrimination
  3. Legal discrimination - location, salary, industry, qualification, etc - legally permissible decisions driven by assumption
  4. Relying on configured ranking within an ATS to prioritise applications
  5. Not considering candidates who aren't picked up by a Boolean search (sourcing)
  6. Filter questions at advert stage (e.g. do you have a work permit?)
  7. Applying after the vacancy is at interview stage
  8. And many more


All de facto automated rejections have one thing in common, and it isn’t automation - it’s human decision-making, including shortcuts and assumptions.


Some of those examples above are cited when talking about 'genuine' auto-rejects. However, these are all consequences of human intervention and the choice not to intervene.


There is an increasing number of AI products that automate these steps (see The truth about the ATS / Try for yourself), with the requirement of human oversight - I've yet to speak to a recruiter that wholly relies on them, and few who don't view every application.


This is one reason why ATS Compliance and Beat the Bots are a red herring.


The advice fails not because it’s wrong, but because it optimises the wrong layer.


The system is only a component in the process, governed by humans.


If you misdiagnose de facto automated rejection as a technical problem, you’ll keep trying to outsmart systems instead of changing how you’re seen, found, and prioritised by people.


Understanding how recruiters handle their process and giving them what they need in an application has to take priority.


While the same steps that “optimise human compliance” are implicitly system-compliant.


The challenge is that human compliance relies on what makes us individual: our skill level, our insight, our psychology, our biases, our resources and the time available to us. As well as how you navigate these.


Without forgetting that we are people like you, often trying to do too much with too little. It’s no wonder our frustrations mirror yours, with the difference that we earn a salary for our experiences.


Whereas ATS Compliance feels more comfortable, because it gives a clear direction, even if it’s the wrong one.


It is true we use filters and keywords to prioritise how our applications are presented to us. We do the same when we look for candidates, whether on LinkedIn, job boards, our ATS or other means.


All this does is present results in a way that allows us to spend more attention on those that meet the criteria we have set.


When we review those results, the way that information is presented informs whether we progress them or not.


To be human compliant, your application has to be discoverable, then it has to convert interest.


Fail on either front and you’ll either be rejected or you won’t hear at all.


If humans are the reasons you are rejected for reasons unrelated to capability or contribution... well, I think that’s rather more problematic than technology.


Beat the Bots and ATS Compliance aren’t just a red herring - they can actively hold you back.


Because they place the wrong priority by presenting a strategy, rather than simple hygiene. Your wider strategy should encompass far more than applications - getting found, starting conversations, doorknocking, networking and all these other opportunities that can get you closer to a job:


These are fundamentally covered in a human compliance strategy.


I just happened to call it A Career Breakdown Kit instead, and how to do these is covered in Parts 2 and 3 of the book.


I realise this can create a feeling of overwhelm, when you realise there is much more to a better application than the transactional steps of ATS compliance.


Yet these same steps will improve every aspect of your job search and some are straightforward to take - DM me on LinkedIn and ask for the free CV template that is an easy starting point - and others which will improve every aspect of what you do.

By Greg Wyatt • November 11, 2026
I've written many variations on the article below, over the years, and it seems sensible to revisit given the UK government's announcements around salary transparency. On the whole, I'm for it, with the many advantages it brings. But like a lot of things in recruitment, there is a more involved discussion to be had, especially when this fix treats the symptoms, not the rot. That's not to say the fix isn't worth doing, just that it won't fix many of the problems underlying a lack of transparency. This article is a little dated, in terms of the research shared, but I think the points are as relevant as ever. Originally published May 2023 Salary on the Job Description? Yes, the headline is trolling. The question should be ‘salary on the job advert?’ You wouldn’t confuse a job description with an advert, would you? This is a subject rife with disagreement around ethics and practicality, and worth broaching again considering recent campaigns in the UK to increase salary transparency and ban the ‘what’s your current salary?’ question. Let’s focus on some practicalities first, based on UK research I ran last year for my “Accessing a Candidate Short Market” guide:  Job boards can penalise you for not listing salary. As of December 2021, Totaljobs penalises adverts that don’t list salary, and these aren’t sent out as job alerts to candidates (who may be passive). These adverts are considered sub-standard. Unlisted salaries attract fewer qualified applications. This was estimated to be between 20% and 45% fewer, across the job boards I talked to. LinkedIn reported that not only can you expect more applications, you may also expect better-qualified applications when the salary is advertised. My work supporting senior job seekers confirms this - many would not apply to adverts that had no salary or "competitive salary" because they felt this was a waste of their time. There is less emphasis on salary negotiation from the candidate side, due to transparency in pay. This is a key part of equity, relating to gender, race and intersectional identity. According to Payscale 's research, white men are most likely to negotiate the highest salary. It’s simple – if you advertise vacancies and don’t list salary, you risk receiving fewer, less suitable applications. Then there’s the ethical question, where a common argument is that there is ‘no ethical reason that salaries can’t be listed’. Now, while I’m a proponent for advertising salaries, where possible, I think this ethical argument isn’t the right one - ‘can’t be’ is a strong statement. I think a better question is ‘how does this do harm’ when establishing reasons for not listing salary. This balances pragmatism with the most important aspect of ethics. It can be a complicated question too in scenarios like this: How do you establish salary transparency for job families across multiple regions where the local pay is established by HQ in one country? Currency exchange rates and cost of living mean that a fair salary one day may not be the next, therefore flexibility in not listing salary may be ethically the right thing to do if the intent is right. What about new vacancies that serve to solve a business problem and can be recruited at different levels? What about practical situations like recruiting hard-to-fill vacancies during a wider redundancy programme, whereby listing a salary would create concern in unrelated areas of that unsettled business? It's not always as simple a question as we’d like to think. If you’re facing a complex situation in advertising a role, I recommend describing your stance in the advert itself, if you legitimately can’t state the salary. At the same time, as we’ve seen in the US, legislation to enforce salary transparency creates situations such as Netflix apparently advertising a range of $90-900k. Who does that help? The problem with this kind of legislation is that companies can comply while continuing the behaviour that led to the legislation in the first place. It’s palliative, rather than treating unfairness at its root. We should also consider the unforeseen consequence of salary transparency, such as this research which appears to show a reduced link between performance and pay: Influence of Pay Transparency Helping candidates negotiate better pay or terms is a privilege I enjoy. And there's more to understanding someone's existing remuneration than simply establishing whether they can afford to move. Sometimes these conversations reveal that someone is being underpaid. With evidence of what their experience and contribution might command elsewhere, they can go back to their current employer and make the case for a pay rise. That might mean they decide not to move at all. Which is a perfectly good outcome for them, even if it isn't for the vacancy in the short term. It also opens up the counteroffer conversation early. If their employer could resolve the reason they're considering leaving, I'd rather understand that before they accept an offer elsewhere. There's a benefit for prospective employers too. A new employer may budget £52,000 for a role, believing that to be market rate, based on historic data. But if conversations with suitably experienced candidates reveal that their existing remuneration, expectations and other opportunities consistently indicate otherwise, there's good reason to revise either the budget or the requirements. If that budget does prove unrealistic, and it's the same budget other team members are measured against, it can also create the argument to revisit everyone's salaries - subject to affordability, of course. After all, it's cheaper to retain fairly paid staff with all the knowledge they have than to replace them. Of course, conversations with candidates aren't a substitute for proper salary benchmarking. But they can reveal problems that wouldn't otherwise be apparent. There are also situations where understanding the whole package matters. What if someone currently receives a 16% pension contribution and moves to a role offering a 10% pay rise but only a 5% pension? Car allowances, RSUs, tax-efficient packages? Remuneration is a more involved conversation than simply salary. And none of this means someone's existing salary should determine what they're worth to their next employer. If their previous salary was unfair, using it to determine their next salary risks perpetuating that unfairness. And if an employer routinely offers a 15% increase on previous earnings, the new salary may have little relationship to the contribution that person can make. It makes sense to pay commensurately with contribution and capability, rather than what may be irrelevant history. So I understand the reasons for wanting to ban questions about previous salary. They're often used badly. But I think there's an important distinction between asking to establish someone's worth and asking to understand their circumstances. One can perpetuate unfairness. The other can help identify and correct it. If legislation restricts these conversations, I'll adapt how I offer this support. But I'd hope any restrictions recognise the difference between using salary history to determine an offer and voluntarily discussing remuneration to help someone make better decisions. I hope you’ve found these thoughts helpful to start a broader conversation in your business. My thoughts aren’t set in stone, so please let me know your opinions if you disagree. Thanks for reading. Regards, Greg p.s. While you are here, if you like the idea of improving how you recruit, lack capacity or need better candidates, and are curious how I can help, these are my services: Commercial, operational and technical leadership recruitment Manage part or all of your recruitment on an individually designed basis for one client Outplacement support Email me on greg.wyatt@bwrecruitment.co.uk if you'd like to discuss.
By Greg Wyatt • November 5, 2026
It's interesting revisiting this article from 3 years ago, especially now AI products are more embedded in market. If anything my view on AI is more polarised, bringing many new opportunites, brand new problems, as well as the existential angst many are talking about. For me, codifying my experience with AI tools means I can help more people, while freeing up my time to do more human work. It's certainly helped with job seeker support, and increasingly so in my recruitment work. Mainly it's giving me more time to talk to people, and when homogenous AI applications at scale are one new problem, as well as the increasing threat of deep fake interviews, in person conversations might be a necessary exnovation (just googled that - what a great word that I will now abuse at scale). While the article below has dated somewhat, I think the threat it assesses has never been more pertinent. I've said for some time that AI might be the death of knowledge and judgement, even so far as 'meaning', something that this recent research also indicates . Importantly the research doesn't say the recommendations were wrong, just how they were followed. Read that article and think about how AI recommendations on applications relate. I've certainly found them more problematic, so far, than the old school ATS style ranking and filtering - because of the false confidence they convey, especially when dealing with non-traditional applications. Things may improve, or so is promised. And while words might be the first facility of LLM, they are still the core facility, given all it does is determine the most probable answer in its outputs (I know I'm being reductive, some of the developments from AI are amazing). Whereas words should be the consequence of thoughts, lead to the development of thought, and distil ideas in a way you can act on. Much like job adverts should be the consequence of effective job analysis, rather than a polished word that lacks meaning. The greatest risk for me in recruitment isn't so much the answers AI offers, but that we become so reliant we forget to ask better questions. I've edited down the previous article, but if you're curious, you can see it here . September 2023 I’d commented about my hearing on a social media post on deafness. ‘Have you looked into these hearing aids - they’re designed to overcome head shadow’, came the impromptu reply from a hearing aid specialist. Head shadow? Not a phrase I’d heard before, despite having no hearing on one side, which effectively creates a sound-free shadow to my right. See, when I had mumps at 18 months it killed the vestibulocochlear nerve in my right ear and damaged the one on the left. But it was my balance that showed the nursery assistants that something was wrong - I kept falling over for no reason. I expect they thought my slow response was normal naughty-boyness. Balance, intermittently poor audio processing, energy required to maintain attention in noisy environments and that bloody tinnitus - all these issues are far more annoying than not being able to hear in one ear. That and not being able to tell where sounds come from. “Over here, Greg!” is the most useless call on a football pitch. And the head shadow thing? Well, it’s never been an issue - I just turn my head when in conversation. It might look like I’m turning to kiss you, but it’s just a conversation I want honest. Sure I miss out on certain audio cues, but it’s rarely an issue. Anyway, curious as I am I looked into the £4,000 hearing aid that solves head shadow by placing a microphone on the deaf ear and projecting it into the the good ear. Quite the brute force tech solution and one I’m sure some benefit from. But the key issue is one of reverb. While the product is good, it would impact the quality of sound in my good ear, which seems a pointless trade-off for me, when my process of life is more effective than shiny tech. It’s ironic that I consider myself highly excitable when it comes to technology developments, yet I’m never an early adopter. Because I always ask myself, other than giddiness, what problems does this solve and how will it enhance my life. And so it is for AI in recruitment, and the shininess of tech in general. They are positioned as solving problems, and indeed they do, but in many cases, it’s the wrong problem that detracts us from the real opportunities for better processes. Simpler administration, speed and scale are clear benefits. And some of these AI-branded automations are excellent. The Star Trek-style auto-translator makes me giddy. As does the sales bot conversation-as-a-human sales video that’s doing the rounds. But AI for writing? What problem does that solve? For me, it depends on what you consider sales to be. Is sales pitching a generic message and hoping someone will bite? Or is sales laying out the facts so that the right person can reach an objective decision? A decision which might mean getting in touch, or changing their view on what needs recruiting. For the former AI writing seems to solve a problem. The words are certainly better, but the message is even worse. Yes: prompting. But if you can prompt the right message, why aren’t you just writing it, so that you embed that knowledge for use across other mediums - conversations, meetings and so on? While AI writing does not meet the requirements for the second type of sales. You can only do this by establishing the right facts from a briefing, consultation or interview. Then interpret this with meaning to the right people so that it creates the right impact. Sales as data visualisation, if you will. And if AI doesn’t work for sales in this way, why would it work for content or marketing? I think the answer depends on whether you value contextual insight or not. Until AI is better at asking questions that create meaningful conversation, it’s a non-starter for me. I say until because this hesitation will be moot in the next year or so. Because it isn’t what AI is now that’s the opportunity - it’s what’s coming soon. I can’t wait to see what’s next. Until then, AI, for writing, is a question of in one ear and out of the other. Which, if you’re deaf in the one, is quite the problem. Go learn copywriting instead, and listen to how it transforms your approach to recruitment. Then layer tech on top, when it’s ready. Thanks for reading. Regards, Greg p.s. If you like good recruitment and you need help with it in the UK, drop me a line. DM on LinkedIn, email greg.wyatt@bwrecruitment.co.uk , whichever you prefer.