Nino is listening to a conversation about CVs, algorithms and new opportunities. Then he asks the question nobody put on the agenda.
“Excuse me, but if AI writes my CV and another AI screens it… do I need to turn up for the interview, or can they sort it out between themselves?”
Everyone laughs. Then a suspicion creeps in: perhaps Nino has spotted the point where efficiency risks becoming a conversation with nobody in it.
Two assistants. One person to get to know.
On one side, a candidate can use AI to make a CV clearer, connect experience to the role and prepare for questions. On the other, employers have tools that help them find profiles, organise information and assess potential matches.
This is more than an imaginary scenario. LinkedIn describes AI-assisted search and hiring agents, alongside tools that support applications and CV preparation. That does not mean every hiring process is automated, or that an algorithm alone decides who gets hired. It means AI can be involved on both sides of the table.
So far, there is no scandal. A poorly written CV can hide an excellent professional. An unfocused search can prevent a recruiter from finding them. Improving those steps makes sense.
The problem starts when the quality of the packaging matters more than what is inside.
The perfect CV can be bad news
Imagine an impeccable application: all the right words, no hesitation, every experience aligned with the job description. Is it the portrait of a capable person, or evidence that someone knows how to optimise a document?
The document alone may not tell you. That was true before AI. It makes looking for evidence beyond the text even more important now.
A project explained precisely. A difficult decision and the alternatives rejected. A mistake acknowledged. A result described without claiming the work of an entire team.
These details are less polished than a perfect formula. They make for a more useful conversation.
Translating your experience does not mean inventing it
For an experienced professional, AI can be an excellent editor. It can help explain a complex career to someone outside the industry. It can make experience built around clients, infrastructure, constraints and difficult decisions easier to understand.
The distinction is straightforward: clarify a result you achieved, or claim a result you did not. The first improves communication. The second creates a debt that the actual job will eventually call in.
If your CV promises a skill, you should be able to discuss it. If it cites a number, you should be able to explain the context. If it describes a responsibility, you should know where yours ended and someone else’s began.
What is the employer actually looking for?
The question applies on the other side, too. Before asking AI to find the ideal candidate, a company needs to clarify what makes someone suitable for the work.
What results will they need to deliver? Which skills are essential from day one? Which can be learned? What transferable experience might a literal reading of the requirements overlook?
A candidate may never have used your CRM, for example, but may have spent years managing complex sales involving technical specialists and several decision-makers. How much does familiarity with the software matter compared with the ability to navigate that complexity? The answer depends on the role. It needs to be decided, not left implicit.
Automating a search without clarifying the criteria can accelerate a poorly thought-out selection process. Speed does not fix a bad question.
The interview needs to add something to the CV
If the meeting merely repeats the document, Nino has a point: the two machines might as well keep talking.
An interview becomes valuable when it explores how someone reasons. A realistic case. Incomplete information. A constraint that changes. Permission to ask questions before answering.
The aim is to understand how the person uses what they know. That can include AI tools when the job involves them. Stating beforehand which tools are allowed makes the exercise clearer for both sides.
This is where experience can become visible: in the problem you recognise, the risk you flag, the answer you choose not to give until you understand more.
In the end, Nino does need to turn up
AI can help you attract attention. The conversation helps establish whether that attention has found the right person. On both sides.
Because the candidate is assessing something, too: the clarity of the role, the quality of the questions and the company’s willingness to look beyond a perfect application.
Nino thinks for a moment. Then adds:
“Fine, I’ll come to the interview. Just tell me whether you want a capable person or a CV that tells you what you want to hear.”
In your experience, what question reveals a skill that a perfect CV can hide?
Keep asking useful questions
The HiTechStories Digest brings you perspectives and tools to stay relevant, think independently and use AI without handing over your judgement. Explore the Digest.
Sources and editorial note
Product sources: LinkedIn: AI agents for job seekers and hirers; AI-Assisted Search & Projects; LinkedIn Hiring product updates, Q2 2025. Consulted on 21 October 2026.
Nino’s questions are a narrative device. The examples are hypothetical: they do not describe a verified company case or imply that every hiring system works in the same way.
Leave a Reply