Interview: AI is changing recruitment. The fundamentals of good selection haven’t.
AI is changing how candidates apply, how recruiters work and how much information hiring teams can process. In a recent interview, Recright CEO Rasmus Nybergh discussed what this means for candidate selection – and why, despite all the new technology, the fundamentals of good hiring remain surprisingly familiar.
Candidates can use AI to tailor applications, prepare for interviews and articulate their experience more convincingly. Recruiters can use the same technology to create questions, process candidate information, transcribe interviews and summarise responses.
The tools on both sides are developing quickly. But does that change what actually makes a good hiring decision?
In the interview with Antti Pietilä on Menestystä Etsimässä podcast, Rasmus explored that question alongside the practical changes recruitment teams are already dealing with today.
Watch the full conversation (in Finnish) →
The process is changing faster than the principles
One of the most visible changes is happening at the very beginning of recruitment.
Recright is involved in tens of thousands of recruitment processes every year, and Rasmus describes how customers are seeing both high application volumes and a higher average quality of applications. AI makes it easy to combine a CV with a job description and produce a polished application.
That can be useful for candidates. But it also means that recruiters face large numbers of applications that are difficult to distinguish from each other.
“The average quality of applications has gone up significantly. But the differences between them have become smaller. Based on the CV and application alone, it’s becoming really difficult to distinguish between candidates.”
Rasmus Nybergh, CEO, Recright
Recruitment teams at Telia Finland and Telia Estonia describe a similar challenge: as applications become easier to polish, the written application alone gives them less information to work with. Their response has been to use structured video screening to gather relevant, comparable information earlier in the process.
Read how Telia uses video screening in practice → (ADD LINK LATER)
At the same time, even relatively unknown companies can receive 150 or 200 applications for a single role. That creates a practical selection problem. You cannot interview 200 people, but you still need enough relevant information to decide who should move forward.
For Rasmus, this makes it even more important to be clear about what information the hiring team actually needs.
Good selection starts with knowing what you’re looking for
Before evaluating candidates, the hiring team needs to define what success in the role requires.
That sounds basic, but Rasmus argues that this work is often done too lightly. A company decides it needs a salesperson, developer or marketing coordinator without fully defining the capabilities and behaviours that matter in that particular role and context.
If those criteria remain vague, the rest of the process becomes difficult to structure. The team collects information from applications and interviews, but lacks a clear basis for deciding which information actually matters.
Rasmus argues for starting the other way around: define the relevant criteria first, then use the recruitment process to collect evidence against them.
“When you know what you’re looking for, you can collect evidence against those criteria throughout the process. That’s when recruitment becomes not only structured, but evidence-based.”
Rasmus Nybergh, CEO, Recright
That evidence can take different forms. A candidate can describe how they handled a specific situation in previous work. Structured video questions can gather comparable information earlier in the process. Later, an interview or practical exercise can explore the capabilities that matter in more depth.
The methods may change, but the principle is the same: define what matters, collect relevant evidence, and use that evidence when making the decision.
AI can make good selection easier to apply
The interesting role for AI, then, isn’t necessarily to reinvent selection. It is to make good selection practices easier to apply.
Historically, collecting richer information from more candidates has been expensive in terms of recruiter time. If 100 candidates remain after the first screening, asking better questions is useful only if the hiring team can realistically work with the answers.
AI changes some of that equation.
It can help formulate questions based on the role, support early candidate interactions, transcribe responses, summarise information and identify what information has been collected or is still missing. That allows recruiters to work with more relevant information without manually processing everything from scratch.
But throughout the conversation, Rasmus draws a clear boundary between using AI to support the process and asking it to make the hiring decision.
“AI can collect, organise and summarise the information. But it shouldn’t decide who you hire. That responsibility still belongs to people.”
Rasmus Nybergh, CEO, Recright
This is an important distinction. The goal isn’t to automate judgement, but to give people better information to work with.
Good selection still starts with understanding what success looks like in the role, collecting relevant evidence and using that evidence to make the final decision. AI can make that process more efficient, consistent and practical at scale.
The tools are changing. The fundamentals of good selection aren’t.
Watch the full conversation
Hear Recright CEO Rasmus Nybergh discuss how AI is changing recruitment and job applications, where AI can support recruiters, and why structured, evidence-based selection still matters.
Watch the full interview (in Finnish) →
Go deeper into Intelligent Selection
Learn how to define what success looks like, collect relevant evidence throughout the hiring process and make more structured, consistent hiring decisions.