Written by Amanda Teti, Senior Consulting Associate, Daniel Messinger, Consulting Associate, and Megan Why, Consultant
Using AI tools for talent acquisition is becoming more of a trend in 2025. While some companies have established policies and guidelines on the use of AI tools for hiring processes, others are still navigating its implementation. Regardless, AI is becoming more prevalent and has begun to reshape traditional hiring processes. This emphasises the importance of learning how to leverage AI as an HR professional, especially when it comes to hiring decisions and processes. It is important to understand the future impact of AI hiring tools to ensure their ethical and effective use in hiring decisions.
AI hiring tools: 3 areas of focus
Most people are familiar with AI when it comes to chatbots, web search suggestions, and, more recently, ChatGPT and self-driving vehicles. However, the use of AI tools for hiring is still a very new concept within the world of HR. When you think of a traditional talent acquisition process, there are many steps, but traditionally the three most important stages are candidate screening, assessment, and interview. Let’s take a look at how AI hiring tools will impact each of these.
1. AI in screening
For the screening process, AI tools are used to help recruiters review high volumes of applications quickly, making it more tempting to use. When used correctly, it can reduce human bias as well. However, before incorporating AI into your selection process and decision-making, it’s a good idea to explore the benefits and potential drawbacks that can occur. Below are a couple key insights to consider when using AI tools for screening purposes:
Efficiency
A research study on ethics of AI in recruiting processes was conducted by Hunkenschroer and Luetge in 2022. Their research highlights that AI tools efficiently sort through hundreds of CVs using predefined criteria, ultimately selecting the most suitable candidates. This is a benefit because it reduces time spent on manual screening and gives recruiters time back to focus on other important aspects of the interview.
However, a drawback that was found was the possibility of qualified candidates being overlooked because of certain keywords not matching the criteria. That not only results in a missed opportunity for the candidates but also for the company. It’s preventable though! Recruiters can ensure that the key words or phrases in the job descriptions are flexible and allow recognition of transferable skills expressed in different ways to reduce the risk of overlooking a qualified candidate.
Bias
According to Hunkenschroer and Luetge, bias is the “most-discussed topic in extant literature on AI-enabled recruiting.” Another benefit discussed is the reduction of human bias, as AI tools can eliminate bias-prone judgments from recruiters and focus solely on the skills and qualifications required for the role. This can promote a fair recruitment process, but only if the algorithm is designed properly. If it’s not, then algorithmic bias can come into play and that can be considered as another drawback.
If you’re wondering what algorithmic bias is, it’s essentially a bias embedded in AI through its programming. In order to design an algorithm, human perspective is the original source of creation which is how algorithmic bias can lead to unintentional discrimination. Fortunately, algorithmic bias is often easier to detect and correct than human bias. As a way to be proactive on this issue, algorithms should be regularly audited, revised, and tested for biases to ensure a fair recruitment process.
2. AI in assessment
To date, AI has been used sparingly in pre-employment assessments. Although AI can make a substantial impact on the way assessments are used, companies are still evaluating the practical, legal, and ethical implications of it. A few AI-powered assessments have been explored, but we’ve barely scratched the surface of AI’s potential in this arena. Now that AI is advancing exponentially, the possibilities to enhance pre-employment tests are endless. It’s up to us to determine how we can use AI tools for talent acquisition from a practical and ethical standpoint.
Picture this. AI analyses hundreds of hours of videos showing employees working a particular job. That AI then creates a customised assessment to measure the skills needed in the job. Personality tests, technical knowledge tests, and even virtual reality (VR) simulations are created by AI based on what’s most relevant. As candidates go through the process, all of the information is synthesised by the AI so that it can make a final recommendation for that particular candidate. Although this technology does not exist quite yet, these types of things will be possible sooner than people realise.
As these things become possible, we must ask critical questions such as:
- How do we ensure that AI is not biased for or against certain people?
- How do we know if these AI hiring tools are measuring something relevant for the job rather than unrelated factors?
- At what point is AI ‘good enough’ to introduce it into the assessment process?
- Where do we need human involvement to protect against mistakes or legal liability?
For now, there are more questions than answers when it comes to AI in assessment. Because of this, business leaders need to continually monitor and adapt their approaches as the technology progresses.
3. AI in interviewing
While the questions remain around the use of AI tools regarding assessments, there has been a significant amount of technology built around using AI interview tools. In an AI-driven process, candidates interact with technology by answering questions via video or text and then are analysed against algorithms customised for the job and the organisation. A report of the candidates’ results are then presented to the recruiter with minimal candidate interaction on their part.
AI interview tools can be especially helpful when screening candidates and for high volume hiring situations. It allows the recruiter to see more candidates than they would if they had to interview each one without AI. This can also remove some of the biases that are often associated with interviews to give every candidate a fair chance.
While it’s easy to think of some of the benefits of using AI tools for interviews, interviews should also heavily focus on creating a positive candidate experience to be successful. Many companies understand that a candidate’s perception of their organisation and their experience in the hiring process can affect how their organisation is perceived. Some candidates who are more comfortable interacting with technology may appreciate a high-tech process where they can complete it on their own time from their chosen location and do not feel the pressure of an in-person interview. Others, however, may prefer to be able to show their personality in an in-person setting where they can build rapport with their interviewer and get specific questions about the role and organisation answered.
The rise of AI tools for talent acquisition
Organisations will have to decide if they want a high-tech or a high-touch hiring process. In 2025, organisations may be looking to insert more high-tech processes into their talent organisation through the use of AI, but they will also need to determine where the high-touch process is still valuable and desired by the candidates.
As we become more and more comfortable with AI hiring tools, we can expect to see these trends emerging in various HR processes. Despite this increase, human involvement and oversight will still have a place alongside AI tools for talent acquisition and their role in helping organisations make hiring decisions for the foreseeable future.
About the authors: Amanda Teti, Senior Consulting Associate, B.A., provides consulting support primarily for automotive and manufacturing clients. She manages and supports the hiring processes for these clients, contributing to the development and implementation of assessment solutions. Amanda also provides training and exceptional customer service, ensuring clients use the tools effectively to meet their day-to-day needs. Currently pursuing an M.A. in Industrial-Organizational Psychology, her expertise includes entry-level hiring, employee selection, pre-employment assessments, analysis, customer experience, and training and development.
Daniel Messinger, M.A. provides client support and assists consultants with client deliverables. He plays a key role in project management and implementation of screening assessments. Daniel often assists with data collection and reporting, project planning, job analysis, validation, and assessment implementation and monitoring.
Megan Why is a Consultant who manages client implementations that involves project planning, job analysis, validation, and provides ongoing support to clients through adverse impact analysis, reporting/monitoring, and process improvement suggestions. Her areas of expertise include workplace safety, high volume manufacturing hiring, interview training, and pre-employment selection assessments.
