How Will AI Transform the Hiring Process?

Artificial Intelligence. AI. We have all heard about it or read an article detailing how it is going to change the way we work or even live.

There is also a degree of fear: will machines learn too much and decide to replace us? Watching Terminator will do that to you.

But today’s AI is both more complex and much less advanced than self-conscious, freedom-seeking robots.

We had a stand at Unleash London – a HR Tech conference and show – a few weeks ago and were really excited by the great applications of AI for HR that we discovered there.

Cronofy’s real-time scheduling technology is a great complement to many of these tools and we had discussions with several providers on the benefits of calendar sync for AI tools.

AI is a hot topic and many industry sectors are investing in it.

But AI is also a bit of catchall term.

AI can refer to things like robots or self-driving cars.

It can also take the shape of a chatbot.

It means applying computers’ ability to learn and solve problems to many challenges by using and analyzing historic hiring data to make more intelligent decisions.

Making smarter decisions and automating tasks can save businesses thousands of dollars per employee every year, and improve the life of employees at all levels.

It comes as no surprise that many HR software providers are already working to leverage the benefits of early stage artificial intelligences.

Various AI-based technologies are already changing how businesses and candidates interact with each other. As these services become more widely adopted and integrated into Applicant Tracking Systems (ATS) and Human Capital Management (HCM) solutions they help transform every step of the hiring process.

Here is a list of AI use cases for the hiring process and the benefits they can provide to recruiters, candidates, interviewers, and businesses in general. We have also added some suggestions of how Cronofy’s calendar sync API can be plugged into these tools to offer an even richer experience.

Job postings optimization

The key to hiring a great candidate is – believe it or not – to meet the talented people you want to join your team. This is why posting an attractive job ad is a critical part of recruiting.

If you have visited a job board recently you will also know that this critical part is often ignored. Businesses can forget that they have to sell themselves and the position if they want qualified applicants to submit their resumes.

Writing a good job ad that will attract exactly the type of candidates you want is much harder than it sounds though.

With AI it is possible to let software create the perfect job adverts that will get candidates started on their journey and build a strong employer brand for your company.

By analyzing the copy of successful job adverts a machine can detect meaningful language patterns and write the job ad that will attract a diverse and qualified cast of candidates.

The beautiful thing with machine learning is that the more job ads are analyzed and the more results are entered into the software, the more refined the job postings will be.

Constant learning and predictive analytics are a winning combination when it comes to crafting impactful copy. The better the job posting, the more qualified candidates will apply to fill vacancies. This can give businesses a competitive advantage and help them grow. But they still have to make the correct hiring decisions and offer a great experience to the candidates.

Resume screening

Great job postings mean that a lot of candidates will send their resumes through. But between 75% to 88% of the resumes received don’t match the requirements of the role.

To decide which candidates to interview, recruiters would traditionally spend hours parsing through resumes, most of the time only scanning the pages for a few keywords before deciding who will progress to the phone screening or face-to-face interview stage.

Analyzing hundreds of resumes is a time-consuming task. It is also a basic task that highly-paid recruiters shouldn’t be focusing on.

52% of talent acquisition leaders say the hardest part of recruitment is identifying the right candidates from a large applicant pool. There is only so many hours in the day and candidates need to be contacted and kept informed of how their application is progressing.

AI can help automate high-volume tasks such as these. Machines can be tasked to search for specific keywords and elements of language that will have historically been used on successful applications.

Machine-learning software needs a lot of data to work well. And they will only get better as the AI providers acquire more clients, completes more hiring processes, and improves their filters for a variety of roles.

It therefore becomes important for businesses to keep track of their hires so that the AI tools can learn who went on to be a successful hire and which employees left the business quickly. This will help refine the resume screening criteria going forward.

It can even be used to parse through the database of resumes received for other vacancies and assess if there are matches for a different job opening. With AI businesses can optimize their resources so talent isn’t missed.

All this helps give time back to recruiters so they can focus on preparing for interviews and engaging with candidates.

AI recruiting assistants (chatbots)

Chatbots are already used to answer support questions, engage website visitors, and help employees book their paid time off in a matter of seconds. The use cases for chatbots during the recruiting process are also numerous.

When chatbots are synced to the calendars of the interview panel, they can be used internally to help recruiters find an interview time that works for everyone based on their real-time availability.

A simple question or command is enough. And if they need to find a meeting room, the recruiting assistant can take care of that as well. All the applications and software used by businesses can be integrated into a chatbot, from HCM platforms to meeting room management systems and group chats.

Interviews or tests can be scheduled in an instant, and a booking link sent to candidates almost immediately. This is less disruptive and stressful for everyone involved. The times agreed to by the members of the interview panel can be shown to the candidate, who picks the most convenient one for them. Meetings and meeting rooms are booked and calendar invitations sent to everyone.

Chatbots can also be used to communicate directly with the candidates. For example, when a candidate applies to a vacant position it could be used to ask screening questions. They can also be used to answer questions that the candidate might have about the interview or the company itself.

AI recruiting assistants help reduce the time to hire and improve the employer’s brand by developing deeper relationships with candidates.

Candidate testing and ranking

It is more and more common for employers to ask candidates to complete tasks before or during interviews to assess their skills and base their hiring decisions on facts, not just the impressions of recruiters.

These tests often happen through video interviewing technology. AI has a role to play in this, too.

A risk of not doing these tests in person is that candidates might be able to cheat. Google is only ever two clicks, away after all.

AI software can detect any abnormal behaviour and notify the recruiter, such as if the response time was particularly long for a question.

They can also be used to analyze facial expressions and voice intonations to detect signals that indicate if a candidate could be a good match.

With calendar sync, all these tests can be scheduled in instantly no matter how many candidates have applied for a position. If an interviewer needs to be present, a booking link can be shared so that candidates can pick a time when they are available.

Once the tests and interviews are completed, candidates need to be ranked on their performances and skills. Well-constructed AI software helps to eliminate bias from this crucial decision.

Humans are biased beings. Studies have proven that humans are bad at making good hiring decisions mainly due to the inherent bias that inhabits all of us. Be it a preference for candidates coming from a similar social background or who are graduated from the same college, a lot of factors can impact a hiring decision.

By taking the ranking of candidates out of the hands of the interviewers, AI can help foster a more diverse working environment by focusing on the hiring the right person for the job.

When the quality of hires increases, it leads to employees who stay longer with their employer and are generally happier and more productive. It’s a win-win for everyone.

Automated candidate engagement and nurturing

After spending a lot of time and money sourcing resumes and interviewing candidates, many businesses forget to use this data once the position is filled. Creating a database of all the resumes of qualified candidates who weren’t offered a job is a great way to get a head start on the next recruitment process.

AI can help keep the information contained in the candidate database up-to-date by looking for changes in social media profiles. Companies can also keep passive candidates engaged by sharing company news or upcoming vacancies.

If a candidate has found another position, predictive analytics can be used to notify your ATS when they are likely to be ready to be contacted about a new opportunity.

With AI-powered candidate engagement platforms recruiters always have access to a dynamic pool of pre-qualified candidates who already know about the company.

The bias question

It is impossible to avoid the question of bias when discussing AI.

The idea pushed by the supporters of AI is that if hiring decisions are made by machines they will inherently be fairer and help companies hire a more diverse workforce. After all, standardized methods mean that everyone starts on an equal footing.

But this forgets that software is built by individuals who all have inherent and subconscious biases.

It also ignores the fact that no technology is more susceptible to replicating existing bias than AI based on machine learning.

If machines learn what success looks like by studying existing patterns, how can they change a model that is currently unfair?

For example, if a business is looking to hire a new software developer and is using an AI software to screen resumes, it is important that all applications are considered in the same way.

But if the development team is mostly male, the AI could favor the resumes of male developers. Or it may develop a preference for resumes that use more masculine words.

It is the role of the AI providers to be aware of existing biases (of which there are over 150). It is also their job to build safeguarding mechanisms to ensure that AI doesn’t acquire the same bias as the humans who built it.

That’s is why software needs to be tested and refined all the time, which is something only humans can do. Before choosing your AI provider make sure you check with them what they do to prevent bias from being replicated.

Parting words

The benefits of using AI to improve the hiring process are numerous. Machine learning and problem-solving software can be used to reduce the time to hire. They can also ensure that the quality of hires improve, which leads to happier and more productive employees.

When bias is taken into consideration and solutions implemented, AI can promote a more diverse working environment by removing human decisions that are sometimes based more on feelings than facts.

But to say that we fully understand the potential of AI for recruitment would be a lie. Every year there are new applications for it.

What we do know is that the future of recruitment centers around a better use of AI to attract, develop, and nurture candidates.

We can’t wait to see what’s next as the role of recruiters is transformed. Real-time calendar sync is sure to be a huge part of it.

And, for now at least, the final decision to offer a job to a candidate still rests in the hands of recruiters and managers. But the benefits of putting more decisions into the hands of controlled technology can’t be denied.

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