8 Ways AI will Impact Recruiters and Talent Acquisition

8 Ways AI will Impact Recruiters and Talent Acquisition

Will AI replace recruiters? 

That’s one question recruiters have been asking themselves since day one of the AI boom. 

Yes, there’s no doubt that the AI impact on recruiters has been great. It’s reshaping the recruitment landscape, bringing unprecedented efficiency and effectiveness to the human resources domain. AI-driven tools and algorithms have revolutionized how recruiters source, assess, and engage potential candidates, optimizing the hiring process like never before. But does that mean we will no longer need humans in recruitment?

In this article, we will try to answer this question by delving into the profound impact of AI on recruiters and its implications on talent acquisition. In fact, the views reflected in the article come from Lewis Milford, Director of Talent Acquisition at Microsoft and Kristen Boyle, VP of Marketing at PandoLogic, who also touched upon the topic during our webinar Will AI Replace Recruiters? The future of talent acquisition in the age of AI (watch the full webinar here). 

1. Bias Reduction

No room for bias in this AI-powered party! AI can play a pivotal role in mitigating bias during the recruitment process. By focusing solely on candidates' qualifications and experience, AI can easily remove personal characteristics like names, gender, or ethnicity. This approach fosters diversity and inclusivity, ensuring a fairer evaluation of candidates.

Referring to this, Kristen Boyle notes: “When there's human involvement in decision-making, there's just naturally going to be bias. And even if it's most of the time unintentional but it's based on what you know and your experience, there's bias introduced in that. I think that one of the key benefits of AI is that we are able to mitigate those biases significantly and account for all of the different perspectives by using data.” 

However, getting to this will obviously require lots of effort and consideration. Lewis Milford raises some concerns about the possible invisible “bias in the machine”: “I think that there are so many elements of concern in the place that we are at today with this technology—just across the board and topics around training. So you know how systems are fundamentally trained and through that training are we creating a bias based around using path data to train something that reinforces how we have made decisions in the past?”

In this context he refers to the book called Invisible Women by Caroline Criado Perez. “It is basically about this idea that when you allow a certain group of people to create a function or a process or a technology that creates a disproportionate experience in society,” he notes. 

Lewis cites of the fascinating examples around Scandinavia, specifically how the local councils planned which roads they would scrape the snow off first. The surprising fact was that they decided to first scrape the roads that they were using to get to work. What they didn't take into account was the experience of particularly women with kids who were using lines different from those main commuter ones. So  the roads weren't straight for these people, who were trying to get their kids to school or their babies to child care. 

“And it wasn't an intentional decision: these people weren't unpleasant people who wanted to disadvantage people. They were just making decisions based around the information that they had,” continues Lewis. 

“So I think there's a big concern that comes in there and you know when you look, there are a number of different groups who represent individuals who would be disproportionately represented. So, for example, people who have come out of prison. Will the way that technology is making decisions around things have a disproportionate impact on them versus other people? I think that there's a lot of work still to be done in terms of ensuring that that is an equitable experience as a technology platform,” he concludes. 

2. Improved Candidate Screening

Speaking about AI in the HR industry, it’s important to note that it has transformed candidate screening by automating the initial selection process. Advanced algorithms analyze resumes, cover letters, and application forms, identifying the most relevant candidates for a given role. This automation not only saves recruiters valuable time but also ensures a more thorough evaluation of applicants.

“AI is saving the screening process just in the ability to interact. So I think there's so many use cases there that—even if it's just a small impact on the recruitment process—it's going to make a huge difference when you sum it up. And we're going to just see that grow significantly in five years from now,” notes Kristen Boyle. 

3. More Data Transparency 

With more expanded use of AI in recruitment, the importance of data transparency in decision making will grow. 

That is important to rule out bias, ensure quality and understand how decisions are made. 

“The importance of data transparency is if you have it all in front of you you're able to kind of see the numbers, the data. You can see how decisions are being made and you can train people as much as possible to remove unconscious bias,” notes Kristen Boyle. 

In this context of the AI-driven hiring process, she also refers to the benefits of programmatic advertising, noting that normally recruiters post a job on 5, 10 or 20 job sites, trying to be as all-encompassing as possible and making sure they are fairly reaching the right candidates. 

“[But] programmatic advertising is going to look at hundreds, thousands of job sites, using data. It's that you're getting all that data in front of you and you don't have to wonder how the decisions were made. If we were able to drive this many applicants for this much budget, the ROI is there and the quality or whatever metrics you're looking at.” 

But, according to her, “the beauty of data and AI decision-making is to make it very black and white where it would just be impossible for a recruiter or any one person to have that much purview into all of the different possibilities out there by themselves.” 

4. Personalized Candidate Experience

With the AI tech available, you can now use AI-driven chatbots and virtual assistants to make your candidates feel like the stars of the show. With automated communication, candidates can receive instant responses to queries, updates on the hiring process, and personalized feedback. This level of engagement creates a positive impression of the company, elevating the candidate experience and attracting top talent.

As to the future AI trends in HR aimed at the further improvement of candidate experience, Lewis notes: “There's also a thing in terms of how a technology can actually improve the ability of the jobseeker to be more targeted and focused about what they actually apply for.”

So, according to him, if the candidate is applying for a certain job, the technology system that he applies to could say: “Hey, heads up! You're probably not qualified for this but we would recommend having a look at the professional development opportunities to bridge that gap from where we see you now to where you might be.” 

“That would be just such an amazing experience for the artificial intelligence to provide those very delightful experiences which actually improve the abilities for the people to identify the right opportunities but also just cut down on blanket applications for roles. So I think the opportunity comes on both sides,” Lewis stresses. 

5. Predictive Analytics for Talent Acquisition

Leveraging AI's data-driven approach, recruiters can utilize predictive analytics for talent acquisition. Analyzing historical data, AI identifies patterns and trends, predicting candidates' potential success in specific roles. 

This strategic insight empowers recruiters to make informed decisions, reducing employee turnover and enhancing organizational performance.

Referring to this, Kristen Boyle notes: “The ability to make real-time decisions and learn from previous performance to influence future predictive analytics is really key. Humans and machines can set up some parameters to guide different types of algorithms or decision making but it's the ability for AI to have this machine learning.

According to her, that allows you to learn from the past and inform the future and the future strategy: “I think that is new and that is something that will be more and more at the forefront of recruitment tools. It'll be a tool for recruiters to use to identify patterns and trends and success factors all related to hiring.” 

6. Better and Faster Job Descriptions

With the introduction of ChatGPT, we witnessed how fast and efficient the content creation process can be. 

As Kristen Boyle points out, “ChatGPT is just one tool in the toolbox and that's a big opportunity that wasn't there a year ago.”

In recruitment this opportunity can be translated through different tools, which help recruiters generate compelling and unique job descriptions for any role. The benefit of this AI use case is not only the speed of generating job descriptions but also its quality and unbiased language. 

If you’d like to become a beta tester of such a tool called Mario, which helps recruiters write compelling JDs, do boolean research and much more, subscribe here

7. Emphasis on New Skills, Strategy and Human Side

Whatever future we predict for AI in recruitment one thing is for sure: it will first of all impact the job descriptions for recruiters, expanding their required skills. 

“I think we'll see job descriptions for recruiters change right in the same way that we probably have in the last 15 years in terms of the ability to use technology. And AI is going to be one tool to empower recruiters in the way that they have other tools.  I imagine that there'll be a technical skill capability,” Kristen Boyle notes. 

Elaborating on this, Lewis Milford notes: “If we look at the future, topics around bias and discrimination, topics around transparency, privacy and data security, the technical topics related to Talent Acquisition, I think these are all going to become at the forefront of talent acquisition.” 

However, aside from the technical skills, Kristen thinks there will be even more emphasis on the human part of human resources and recruitment, which, as she notes, “is the fun part” as it’s about candidate relationships and looking for cultural fit. 

What’s more, she thinks that AI will help recruiters improve their strategy: “There's always going to be opportunities for a human to be involved and there's opportunities for strategy. So how can you as a recruiter know when to apply AI in your recruitment workflow and when to not? And how do you audit your tech to make sure you're optimizing your ROI? And you'll have more data at your disposal to be able to share with your stakeholders to show your value. 

According to her, all of that strategy lens so often gets buried because recruiters are in the day-to-day of just all of the tedious things on their to-do list: “That's really going to be allowed to come to the forefront when we have some AI and really advanced technology to make the rest of the process more efficient.” 

Adding to this, Lewis also mentions the opportunity to focus on change management elements: “We love talking to people and we love influencing decisions. I think that change management elements are one area which the recruiters haven't always had the time to really focus on because operationally there's been so much to do. But actually sitting down with the business and rather than saying “where are my CVs, we need to hire this person quickly”, let's take a step back and let's start to look proactively at the current landscape. Let's start to look at our assessment process, let's start to uncover biases in our process and bring those to the forefront and challenge how we're making decisions. 

According to him, ultimately, talent acquisition is a shared accountability between Talent Acquisition and the business who is hiring: “And I think that for us continuing to go on that journey and driving more change management with that partnership is going to be a key part of the talent acquisition in the future.”

Summing up, the need for recruitment as a function will remain: it’s just the specific niche roles within that function that could alter a bit along with job descriptions. 

8. More Legislation & Compliance

The overall state of AI usage control can now be described with one word—uncertainty. 

The wider application of AI will inevitably bring up the need for control. This means governments will have to put in place special legislation to ensure data protection and security. Like in human recruitment that might require certain audits by a special authority to rule out bias and/or other unacceptable practices. 

“I think hopefully that is an activity that more and more are going to adopt over time and will really help kind of streamline the use cases so that they don't get too out of control and that there's proper mitigation of risk in place,” notes Kristen Boyle. 

Referring to the possible auditing procedure, she adds: “We had a third party tech auditing firm come into audit and that's exactly what I'm sure employers will have to do. So again there's just not a ton of guidelines right now and there's so many questions around, well, how do we get started and who's going to audit us. So that's all going to be coming to the light, I'm sure, with a ton more different use cases of this legislation and regulation around AI use for recruitment in the coming years.”

Not undervaluing the need for such legislation, Lewis nevertheless raises concerns that that piece of legislation in itself can create a lot of questions and uncertainty about how we're able to operate the technology, data and compliance. 

As to the latter, he notes: “As a recruiter when you're looking at your systems and tools you know that compliance piece is going to be even more critical. In the last like 10 years we've forced recruiters to get all of their information into the applicant tracking system—the notes, the screening details— whether it's like GDPR disclosure or this kind of stuff.”

Thus, talking about the importance of the data accuracy in recruiter systems and tools, Lewis points out two benefits: “One, it will ensure that you know we're protecting ourselves and our companies from any concerns around data misuse. And two, the more accurate data we have in our systems, the more accurate ultimately the decisions we'll be able to make in the future.”

According to him, the next step obviously is to have that data actually make decisions and support decision making: “If I'm ever going to get to a point where I can say to the computer “Hey, show me the the top 10 HR leader roles in the UK people” and it brings me back that accurate list of people that we've spoken to, that will only be possible because that data is all in the system and it's all tracked and tagged and it's all exist in there.”

Final Words

AI’s integration into the recruitment process has revolutionized the HR industry, optimizing efficiency and talent acquisition strategies. However, that integration is not going to replace recruiters but simply take away some of their tedious tasks, allowing them instead to focus on the communication and relations. 

Thus, balancing human intuition with AI-driven efficiency is crucial for creating a hiring process that is both effective and empathetic. As technology evolves, the future of recruitment will undoubtedly be shaped by innovative AI solutions, fostering a more agile, inclusive, and future-ready workforce. Embracing AI's transformative capabilities, recruiters can elevate their recruitment game and secure top-notch talent for their organizations.

That’s basically how the AI-powered talent acquisition will work. 

Workfully's mission is to create the most trusted recruitment experience in the world, aiming to give everyone their chance to build a better world. We are building a decentralized hiring ecosystem for the talent acquisition industry, where recruiters can independently grow, engage and monetize curated talent pools for the benefit of all.



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