Artificial intelligence is advancing at unprecedented rates, and it's becoming a huge talent acquisition trend.
It promises better time-to-hire, reduced costs, and improved efficiency. But there are many cautionary tales floating around that AI perpetuates recruiting bias and leads to unfair hiring.
Organizations now have to weigh the advantages of speedy AI technology against the risk of mis-hires and discrimination.
Or do they?
You can leverage AI in recruiting and talent acquisition ethically and effectively, so you can reap the benefits without harming your hiring process and employer branding.
This article discusses the dos and don’ts of using AI for recruiting, including a list of best practices to use AI for certain tasks and a human touch for the rest.
An AI talent acquisition process is when organizations use artificial intelligence software to perform hiring tasks, such as sourcing and screening candidates.
Many companies are turning to AI recruiting software to improve their talent acquisition strategies, namely to reduce costs and boost efficiency. Using AI in recruitment is essentially like hiring an extra HR employee to handle small tasks but without the additional salary.
AI is advancing at an unprecedented rate, making these tools increasingly more affordable and available.
This sudden rise in artificial intelligence is affecting most of the working world, including the new list of in-demand skills that candidates need to compete. Here are a few of the most popular ones.
Innovation
Empathy
Creativity
Critical thinking
Collaboration
Curiosity
Adaptability
Do you notice anything in this list?
These skills are more human than technical – the rise of AI is changing the most in-demand skills into soft or power skills, such as curiosity and empathy.
This is directly linked to how to use AI in talent acquisition. Use the machines for the technical, time-consuming work, and keep your HR professionals dedicated to the human side of hiring.
For more insights, read our blog on the skills you need as the world changes.
These are two terms that sound similar but have different meanings – let’s define the difference between automation and AI in recruitment.
Automation runs on pre-programmed rules, whereas AI is programmed to artificially think like a human and make its own decisions.
Automation is less risky and prone to bias, which makes it far more common to use in hiring. In fact, we’ve been using automation for much longer. Something as simple as scheduling an email to be sent counts as automation.
But AI recruiting tools can still be used safely and effectively, as long as you make the proper considerations about their impact on employees’ rights.
For more insights on automation, read our blog on recruiting automation.
AI has been sweeping the globe, touching technology, hiring initiatives, creative work, and plenty of headlines.
AI tools for talent acquisition promise increased efficiency, lower costs, and the ability to handle hundreds more candidates than a human comfortably could.
This sudden increase in AI capability has made these tools more than a trend; they’re an opportunity to test the limits of new technology and develop a brand-new hiring process.
Here are the top reasons why the use of AI for recruiting is important to employers:
Facilitates an efficient hiring process: AI is able to create job ads, post them, keep in contact with promising candidates, and even encourage candidates to try again if they were good but didn’t receive an offer. This facilitates an efficient process without excessive work from your recruiting team.
Helps build inclusive job descriptions: Promoting inclusive language creates a better recruitment process, and AI can check for certain coded keywords to avoid, such as “rockstar” or “bossy,” which are gender-coded.
Enables companies to scale faster: With a sudden influx of candidates, hiring managers from small but rapidly scaling organizations can find themselves overwhelmed. It’s lifesaving to have AI recruiting tools handle some of the tedious work.
Reduces costs: A more efficient hiring process means reduced costs, like having less tedious admin work, so your hiring managers can focus on more important matters. Some companies may also hire fewer hiring managers with the assistance of AI.
AI in talent acquisition is also important for the other side: your candidates.
AI recruiting software encourages consistent candidate communication by generating automated responses, making sure no candidate gets forgotten. This is a key part of your candidate relationship management strategy.
A survey from Indeed found 44% of candidates wait at least two weeks to hear back from an employer during the hiring process, and at least 15% wait months.[1]
Even when it’s a “no,” candidates want to hear it. They’re expecting a response, and getting a definite rejection gives them closure.
AI in talent acquisition also speeds up the hiring process. And when an average role takes about 11 weeks to fill, employers and candidates appreciate a faster process.
Consistent communication and a faster hiring process both lead to an improved candidate experience, which, if the person is hired, leads to a good employee experience.
However, even if the candidate isn’t hired, prompt communication and rejection improve your employer branding, and many candidates tell others about the positive experience they had with you.
Using AI in talent acquisition carries many benefits, such as boosting efficiency and reducing time-to-hire.
But the dark side of AI is more often discussed, isn’t it?
Companies need to consider the risks of using AI for recruiting. Here are a few of them:
Can lead to biased hiring decisions (more on this later)
Some stakeholders may not trust AI decisions
Potential legal risks (companies can be held liable even for unintentional discrimination)
However, with the right considerations, you can use AI talent acquisition to benefit your company, steering clear of the potential risks.
We’ll cover how to mitigate these risks later on. But for now, here are the top benefits of using AI in recruitment:
Benefits | Description |
Improves time-to-hire | Streamlining the hiring process improves time-to-hire by helping recruiters write job ads, post job ads, source candidates, and communicate with candidates. |
Improves efficiency | Boosting hiring efficiency not only improves time-to-hire but also reduces mis-hires and improves the candidate experience. |
Reduces costs | Reducing costs is one of the main reasons companies are leveraging AI. Artificial intelligence enables companies to hire fewer workers for small tasks, reducing HR spending. |
Helps candidate sourcing | AI candidate sourcing helps locate qualified candidates from all over the globe. This is crucial during a skills shortage, and it’s necessary because of the increase in remote employees, which gives you hundreds more candidates to look through. |
Helps capture data and metrics | AI in recruitment gives you access to advanced talent acquisition analytics about your hiring process, such as the most successful job boards for finding candidates or the best methods of engagement. |
Leveraging AI in talent acquisition is a great tactic to add to your HR strategy book. When it’s used right, it provides a company with quick, efficient hiring that doesn’t just benefit the organization – it also takes a load off of the recruiter.
So let’s learn how to use it correctly.
AI recruiting tools have the potential to benefit your company, your candidates, and even you – as long as they’re used mindfully.
Our best practices give you the know-how you need to leverage this powerful tactic and improve your recruitment process.
Best practices | Description |
1. Combine AI with skills-based hiring to ensure a fair hiring process | Reduce AI bias by using artificial intelligence with pre-employment tests |
2. Keep candidate experience top of mind | Consider your candidates’ experience by adding customization and welcoming feedback |
3. Use any gained time for delicate matters that require a human touch | Use the extra time gained by AI to add human compassion to the recruiting process |
4. Monitor analytics to ensure hiring bias isn’t creeping in | Keep an eye on AI as it learns and grows to verify it isn’t holding detrimental biases |
5. Combine AI with automation to speed up hiring | Develop a hybrid system using AI and automation in areas they perform best |
6. Educate your employees on AI and your recruiting software | Offer courses and education to help your workforce understand AI |
7. Ensure your AI recruiting software collects only job-relevant information | Monitor your AI recruiting tools so they don’t capture bias-ridden data, like voice recognition |
Toss away your concerns about AI in talent acquisition promoting unfair bias by combining it with skills-based hiring.
Mitigate potential biases from AI by using it in tandem with skills-based practices, a proven method for reducing bias and preventing unfair hiring.
Some AI recruiting tools learn detrimental biases, like the Infamous example of Amazon’s artificial intelligence excluding female candidates.[2]
But skills-based practices, like talent assessment tests, judge a candidate based on their skill set, competencies, and personality traits. You can use machine learning to screen resumes – including AI-generated resumes – but it’s even better to screen skill test scores.
Here’s how TestGorilla’s talent assessments find the most skilled candidate out of all applicants:
Talent assessments enable you to sort candidates by test score and behavioral competencies, ensuring you only shortlist the best candidates and don’t eliminate anyone based on hiring bias.
You can accomplish this by weaving skills-based hiring and AI talent acquisition together. Here’s a sample hiring process:
You write a skills-based job description
Check it for inclusivity using AI
The AI software then posts the job ad on appropriate channels
Candidates apply for the job using skills tests instead of applications
You shortlist your candidate pool using test scores
The AI software keeps in contact with candidates throughout the process
You interview the best candidates
You extend an offer
The AI sends rejection letters to the candidates who were unsuccessful
This way, you benefit from what the AI is best at: speed and efficiency. At the same time, you keep your recruiting process inclusive, fair, and effective.
A quality candidate experience matters. Candidates want the hiring process to be personal, compassionate, and customized.
Too many people have to hear the dreaded “Thank you, candidate…” – and that’s if they hear anything at all.
AI in talent acquisition speeds up hiring efficiency, but it’s still important to prioritize human contact and giving direct attention to anything crucial.
But because increased efficiency and speed themselves improve candidate experience, the key here is balance.
For example, you can customize automatic email templates to insert your candidates’ names and have your AI software send them out to the appropriate candidates, but still handle post-interview rejections yourself (to respect the candidate’s time).
It’s also important to ask for and listen to feedback regarding your hiring process. Proactively solicit feedback with anonymous post-hiring surveys. Do candidates feel like it’s too distant and machine-operated? If so, it might be time to adjust.
It isn’t all about saving time and money. Even the most efficient, affordable hiring process needs to attract job seekers, and a hiring process with a poor candidate experience won’t. Plus, having an efficient screening process and employee onboarding leads to higher retention.
Companies want to benefit from the speed of AI, but you still need the “human” side of “human resources.”
Speaking of the human side of things…
Using AI in recruiting is a game-changer for countless organizations, but it doesn’t mean it should replace every task in your HR department.
In fact, one of the main perks of using AI for talent acquisition is the time it saves. So why not use that extra time to put a human touch on your recruitment process?
Here are a few of the tasks we recommend you use AI for:
Checking job descriptions
Creating job postings
Communicating with candidates
While your AI recruiting software is busy accomplishing these, use your time and effort on the tasks better handled by humans, like responding to high-priority candidates personally or conducting structured interviews.
Some companies are unfortunately trying out “AI video interviews,” where software judges a candidate’s body language and word choice to determine whether or not they're a good match for an open role.
This can quickly lead to detrimental hiring bias surrounding charisma, confidence, appearance, and body language. We talk about this in-depth in our blog on unconscious bias at the interview table.
It’s crucial to focus on people over processes, so use the extra time you gain to put compassion into your hiring process. In the end, it’s these candidates who are going to fill your open role and contribute to your company’s success.
When people discuss AI talent acquisition software and their potential for biases, these algorithms don’t come with them out of the box. AI is designed to grow and learn like a human, so it naturally builds and accumulates biases.
Over time, AI may start to form assumptions about which people are high-quality candidates. For example, your last hiring initiative recruited five White men out of six new hires. The AI might start to assume quality candidates are likely White men.
This means it’s crucial for companies to regularly monitor AI data. Check it for biases and unfair practices that could damage their inclusive hiring strategies. To guarantee nothing slips through the cracks, build this into your HR team’s job responsibilities and schedule regular checks.
Keep an eye on your AI’s data and analytics and ensure it’s still working based on fair parameters, like sending rejection emails to candidates who didn’t qualify during the application stage and not sending rejections to candidates based on personal qualities.
AI hiring bias can be detrimental to your company’s hiring efforts if not handled carefully. That’s why New York has a law requiring audits of AI recruiting tools to check for biases.
This means checking your data for biases not only supports a better, more ethical hiring process – it also might be a legal requirement depending on your area.
This blog is not intended to be taken as legal advice. Please consult a legal professional for guidance relevant to your local area.
As we discussed above, automation and AI aren’t the same thing, but they can be combined to make an efficient hiring process.
For example, you might use AI to post your job ad on job boards that suit the open role, then use automated skills tests to evaluate candidate qualifications. Any candidates who qualify can then use automated interview scheduling to book an interview with you.
After the interview, if the candidate is successful, your AI can inform all the other rejected candidates that you won’t be proceeding with their applications.
Using these types of tech together can ease high volume hiring without solely relying on AI.
Taking time to create a hybrid hiring process driven by automation, AI, and human skill is a keen tactic that’s both efficient and effective.
For more insights, read our blog on how to automate recruitment.
AI is on the rise. Everyone has heard the buzzword, but few people know what it is, how to use it, and even whether or not their company uses it.
One report found 46% of HR leaders don’t know whether or not their companies use AI in talent acquisition – and only 20% know for sure they do.
This is tied to the risk we mentioned earlier: Some stakeholders don’t trust AI decision-making. If your workforce doesn’t know much about AI, it’s difficult to trust it.
But if your workforce is educated on AI and how it works, they’re much more likely to use it ethically and efficiently.
We recommend offering deep technical training to everyone involved in the process to enhance their algorithmic knowledge.
You may also want to offer basic AI courses to employees who aren’t involved. This not only helps them trust the company more, but it can also be beneficial in the future because it’s anticipated many more jobs will involve AI in the coming years.
AI can perpetuate bias when it has access to too much personal information, and the more data it collects, the worse it gets.
For example, an AI talent acquisition tool scans unqualified resumes with included photos from older candidates, so it begins to assume older workers aren’t qualified. This perpetuates age discrimination in hiring.
If you’re using AI to screen potential candidates, ensure it only collects information relevant to the job, like skills and experience.
AI recruiting tools should be barred from information like:
Photos
Facial recognition
Voice pattern analysis
Word choice
This prevents building biases and facilitates a fairer hiring system, increasing the number of diverse candidates you receive.
However, we recommend you screen candidates with skills tests rather than AI and leave smaller, less strategic tasks to your artificial intelligence software.
Now let’s take a look at a few companies that are leveraging AI in talent acquisition successfully.
Companies | Description |
1. Hilton | This company uses AI to answer candidate questions and conduct pre-interview calls |
2. Audible | This company uses AI to boost its recruitment marketing strategies |
3. Siemens | This company uses AI to gather documents and send them to the correct parties |
Hilton uses AI to streamline its recruiting process and provide a better experience for its candidates. This includes:
Using AI for HR chatbots that answer candidate queries and provide personalized feedback
Helping schedule interviews
Analyzing candidate data to predict a good job match
About this last point: Make sure to always use objective methods to make the final decision, such as using skills tests and structured interviews, not just predicted fit.
Hilton also uses AI to conduct pre-interview calls, quizzing candidates on a list of generated qualifying questions.[3]
Using AI tools for talent acquisition, Hilton was able to reduce its 45-day time-to-hire metric down to an impressive five days.
Audible uses AI for candidate sourcing, helping them find the right candidates more quickly to prevent bottlenecks later in the process.
If you start with the wrong candidates, it might be some time before the problem becomes evident.
Audible’s AI recruiting tools place job ads according to its recruitment marketing strategy. It considers factors like diversity targets, bandwidth, and even budget constraints.[3]
Recruitment marketing is an important tactic in your talent acquisition strategy. It gets your job ads in front of the right people, engages passive candidates, and builds brand awareness.
For more insights into this topic, read our guide on recruitment marketing.
Siemens uses AI to help schedule interviews and send relevant information to candidates and interviewers before the meeting.
At Siemens, external and internal candidates receive different information. This means the old process had hiring managers rushing around to find it, verify it was the correct document, and attach it to a message.
On the other side, the same managers had to go through this process with any information the interviewer needed, too.
Siemens has found great success using AI in talent acquisition, saying it's improved the candidate experience overall.
Representatives have stated that they intend to use the extra time they gained to focus on important tasks like candidate sourcing.
AI in recruiting is one of the talent acquisition trends that’s taken the world by storm, and it isn’t likely to slow down any time soon.
AI tools for talent acquisition can speed hiring, improve efficiency, and provide a great candidate experience for your potential hires.
We recommend mitigating AI’s possible risk of bias by combining it with skills-based hiring. Use AI tools for small, tedious tasks like emailing, but ultimately screen candidate quality using proven skills tests.
To learn more about recruiting tech, read our article on data driven recruiting.
If you’d like to browse our database of more than 300 skills tests, check out our test library.
Sources
"How to Write Job Rejection Emails (With Template & Samples)". Indeed. Retrieved July 31, 2023. https://www.indeed.com/hire/c/info/how-to-write-a-candidate-rejection-email
Dastin, Jeffrey. (October 10, 2018). "Amazon scraps secret AI recruiting tool that showed bias against women". Reuters. Retrieved July 31, 2023. https://www.reuters.com/article/us-amazon-com-jobs-automation-insight-idUSKCN1MK08G
"3 Companies That Are Using AI Tools for Recruiting". (November 12, 2021). PandoLogic. Retrieved July 31, 2023. https://pandologic.com/employers/recruitment-industry-trends/3-companies-that-are-using-ai-tools-for-recruiting/
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