At Manchester Digital, we regularly shine a light on our members to understand more about their roles and their work within Greater Manchester’s digital and technology community. This week, we’re speaking with David Berwick, Co-Founder of Adria Solutions.
What are employers finding most difficult about managing AI-assisted job applications right now?
One of the biggest challenges is that applications are starting to look very similar. AI has made it much easier for candidates to produce polished CVs and tailored cover letters, but that can make it harder for employers to distinguish between applicants.
It is also contributing to higher volumes of applications. Candidates can now tailor and submit applications much faster, meaning employers may receive significantly more CVs for a single role. More applications do not necessarily mean more suitable candidates, so hiring teams are having to spend more time filtering through them to identify genuine matches.
AI is also helping candidates articulate their experience in ways they may struggle to do themselves. That is not necessarily a bad thing, but it can sometimes create a disconnect between what is written on the CV and what the candidate can confidently discuss during an interview. The result is that employers need to spend more time understanding the person behind the application rather than relying on the document alone.
How can hiring teams tell the difference between a strong application and one that has simply been polished well with AI?
A CV should always be treated as the starting point, not the final decision. Rather than trying to determine whether someone has used AI, hiring teams should focus on whether the experience and skills presented on the CV stand up to further questioning.
At Adria Solutions, we train our consultants to look beyond the application itself. We cross-reference information with LinkedIn profiles, ask detailed questions about projects and achievements, and explore the context behind someone's experience. A strong candidate should be able to explain what they did, their individual contribution and the decisions they made. Those conversations can quickly reveal whether there is genuine experience behind a polished application.
Ultimately, AI can improve how someone presents their experience, but it cannot replace the experience itself. For employers dealing with high application volumes and without the time to carry out this level of qualification at scale, a specialist recruitment partner can add significant value by doing that initial screening and validation on their behalf.
What risks should employers be aware of when using AI-detection tools or automated screening methods?
AI detection tools should be used with caution. They are not 100% reliable and should never be the sole basis for rejecting a candidate.
The quality of any automated screening is also heavily influenced by the criteria being used. If employers rely on overly rigid filters or poorly defined prompts, they risk overlooking talented people who simply present their experience differently.
Where automation tends to work best is when it is filtering for clear, objective requirements. For example, if a role requires commercial C# experience, using AI to identify candidates who genuinely have that skill can help reduce application volumes with relatively little room for error. That's very different from asking AI to judge whether someone is the "best" candidate based on subjective factors such as communication style or overall suitability.
Technology can help streamline recruitment, but it should support human decision making rather than replace it.
For high-volume roles, especially early careers or graduate positions, what are the most effective ways to manage large numbers of applications fairly and efficiently?
The first step should actually happen before the role is advertised. For high-volume recruitment, employers need to be clear about what they are looking for and decide in advance how applications will be assessed. That means identifying the essential requirements, separating them from the nice-to-haves and agreeing objective, role-relevant criteria that can be applied consistently to every applicant.
Once applications start coming in, those criteria can be used to filter effectively. That might include qualifications where genuinely necessary, relevant commercial experience, right to work or specific technical skills. Structured screening processes can also help maintain consistency, provided they focus on factors directly related to the role rather than characteristics that could introduce bias.
For graduate recruitment in particular, employers should be careful not to make the CV or previous employment the main measure of suitability. Many strong candidates will have limited commercial experience but can demonstrate potential through placements, university projects, extracurricular activities or transferable skills.
Ultimately, managing high application volumes fairly is much easier when the assessment process has been designed before the first CV arrives, rather than deciding what a good candidate looks like once you are already reviewing hundreds of applications.
What practical steps can employers take to reduce the admin burden of screening without missing strong candidates?
The biggest opportunity is to automate the administrative parts of screening without automating the hiring decision itself. ATS filters, application questions and clearly defined knockout criteria can help remove candidates who do not meet genuine requirements, such as right to work, location or an essential technical skill.
Employers can also reduce unnecessary applications in the first place. A clear, specific job description that explains the skills actually required, salary, location and working arrangements can help candidates self-select before applying.
From there, short structured screening calls can often tell you far more than spending additional time analysing a CV. For high-volume recruitment, recruiters can add value here by managing the initial screening, validating experience and presenting employers with a smaller group of genuinely relevant candidates.
Are there particular parts of the recruitment process where human review is still especially important, despite advances in AI tools?
AI is good at processing information, but recruitment still involves judgement, context and motivation, which are much harder to assess automatically.
The initial conversation with a candidate remains one of the most valuable stages of the recruitment process. A CV can tell you what someone has done, but it cannot tell you why they are looking to move, what motivates them, how they communicate or what they are genuinely looking for from their next role. Those are things that only really come out through conversation.
This early qualification can also save employers significant time further down the line.
Understanding a candidate's motivations, career goals and level of commitment can highlight potential risks early. Are they actively interviewing elsewhere? Would they consider a counteroffer? Are they genuinely interested in the opportunity, or simply testing the market? It can also uncover concerns that might otherwise result in someone withdrawing late in the process or backing out after accepting an offer.
Recruitment is ultimately a people business. AI can make parts of the process faster and more efficient, but it cannot build trust or fully understand the factors influencing whether someone will accept an offer, perform well and stay in a role. Human insight remains a crucial part of making successful, long-term hires.
What advice would you give employers who want to improve their approach to AI-generated applications, and where can specialist recruitment partners add the most value?
Keep an open mind. AI is becoming an increasingly useful tool for candidates and employers alike, but it is not a replacement for good recruitment.
The organisations seeing the best results are those using AI to improve efficiency while keeping people at the centre of the process. Technology can help reduce administration, organise information and speed up screening, but the final hiring decisions still require judgement, experience and meaningful conversations.
Many employers are rushing to adopt new AI tools without fully understanding their limitations. A balanced approach, combining technology with human expertise, is far more likely to deliver successful hires.
This is also where specialist recruitment partners can add real value. They provide the human assessment that technology cannot, helping employers understand not just whether someone can do the job, but whether they are the right person for the role and the business.
Thanks David!
To find out more about Adria Solutions, click here.
