AI Recruitment

What are the advantages of using AI in recruitment?


In this blog post, you will find out about the uses of AI in recruitment. The professor of Global MBA in Digital Business Lilia Stoyanov explains how Artificial Intelligence can help recruiters in finding their ideal candidates quicker. 


Nowadays, recruitment is never a simple Job Ad posting. With the technology reaching its massive heights and the recruiters’ jobs getting tougher day by day, a more prolific approach is sought. The mundane job of resume screening all day and identifying suitable manpower based on more emotions and less logic is curtailed.

With the advent of Artificial Intelligence for recruiting, the process of recruitment is more standardized. Also, the results are promising. Moreover, the approach taken over by the recruiters is changing too.

Recruitment has become more of a relationship-building affair than a candidate filling task. The effectiveness of recruitment is what is expected of a recruitment team. The main HR function is identifying top talent that will thrive in the years to come as ‘’bad hires’’ can be extremely costly both in terms of low productivity and team demotivation. Of course, multiple rounds of interviews shall certainly help you identify promising candidates.

But did you imagine the time taken to accomplish the same? The effect of AI in the recruitment process has surely taken organizations to more powerful levels in terms of business accomplishments and low employee turnover. But, what is it in AI that is helping the firms grow massively?


What is Artificial Intelligence?


The process of identifying the correlations of a huge amount of data by leveraging ML (machine learning) algorithms and predicting the possible outcome to empower the decision-making process is at the heart of AI.

Have you come across the email box smartly discarding the spam emails to the spam folders? You don’t even need to classify these emails as spam each time. It is the user experience the algorithm learns from to do the job automatically.

In a way, it saves you the time of pushing it to the trash box too. Indeed, AI is a smart human-designed approach to ease out your mundane as well as critical tasks. Needless to say, Artificial Intelligence for recruiting saves a lot of time and energy in finding the right resource for your company.


How does AI in recruiting help in making smarter, data-driven decisions?

Granular understanding of the User


This is the smart way to tackle the decision-making process. As such, it might be surprising that your decision is otherwise than the instructed ones. The way you search for a particular item or an object on the web determines your decision-making capacity as well as the choice of preference.

The understanding of your likes and dislikes is assimilated gradually by the intelligent programs and offers you the required ones. The sentiment analysis of the usage of the data shall help you find the right candidates too.

Artificial Intelligence is that technological advancement that any department would look for when it comes to making the right calls for the right situation. For you to know how to use AI in recruitment, you must experience the outcomes.

The touch of human sensitivity is always available as you use the software for the recruitment demands. The set rules shall automatically work at the backend and offer insights to help you identify talented candidates while at the same time, it shall not filter out any candidates.

In its infancy, AI in recruitment was criticized for algorithm bias that in some cases led to discouraging candidates from applying. Some ATS (applicant tracking systems) were based on natural language processing techniques that filtered out all candidates who were not using the exact keywords that were used in the job description. Luckily, the leading workforce management system providers adjusted their algorithms to address this issue.


Smart AI features in modern Recruitment

An AI-driven workforce management system by itself is a tool enabling a seamless recruitment process. A cost-effective and high performing recruitment software shall help you save a lot of effort. More importantly, AI provides data-driven insights to empower the decision-making process.


Impeccable Interview Process


What if the recruiters have all the necessary statistics at a glance all the time? The usual process shall be, calling for the role, sourcing the candidates and arranging a few pre-selection rounds, then sending the candidate for the final interview.

The main aspect of this process is, the involvement of urgency, task accomplishment, and performance as a KPI is more than the urge to find the right candidate for the organization.

The impact of Artificial Intelligence on recruitment puts all the three connected aspects to the parking lot. The urgency of identifying the candidate pool shall never be in the picture at all. AI shall help recruiters in:

AI recruitment advantages

Though the above steps are already available in the manual recruitment process, the time taken to do so leads to each recruiter being able to fill in 6-7 roles per month at a maximum. Also, the quality of these hires is questionable more often than not. AI-driven recruitment software slices and dices the talent pool into various dimensions based on the competencies of the candidates, their prior experience, how they stand against the top-performing employees of the organization, how often candidates having similar competencies and career paths have been selected for an interview in the past, etc. The candidate sourcing is powered by predictive analytics that eliminates the bias to a great extent. The best part is, the number of sourced candidates’ counts is larger and of a higher quality.

That’s how AI shall be used in the recruitment process. The interview process shall not only be saving your time but also be human bias-free. The data drive screening accuracy is much higher and leaves little room for biased decisions.


What the Future Looks Like


The meaningful workflow in recruitment through AI is commendable. As such, Machine learning is a fast-developing technology. The ML algorithms used in recruitment are subject to rigorous user acceptance testing. On top of that, the usage of AI-driven recruitment tools will be more regulated in the near future as the EU Commission is already looking at potential threads, especially excluding some job seekers from the talent pool for ambiguous reasons.

Say, for example, the candidate source pool shall automatically identify the people who are planning to shift jobs and the recruitment software sends an email or a text message to engage them. The development in automation of such aspects is already on. A more dynamic Applicant Tracking System (ATS) is what the organizations will be looking at in the near future and it comes to no surprise that leading workforce management systems, like Transformify, already address these needs. An ATS that has all the attributes of urgency, involvement, and quality hire has a big impact, especially on the recruitment process of fast-paced organizations.

The recruiters in the future shall focus more on developing a cordial relationship with the employees and job seekers. The organization’s headcount turnover shall decrease as well as the cost per new hire. The impact of AI-driven workforce management systems will for sure lead to improved quality and employee satisfaction. Moreover, the KPIs that shall be set to the recruitment team once the team’s daily routine decreases will be oriented towards employee engagement, productivity, and career development.



Jul 25 2019 | byNatalia Kukushkina

Artificial Intelligence is aimed at simplifying and automating an array of business processes. Recently, AI made its entrance in the field of recruiting and instantly got close attention.

The thing is the use of AI for recruiting resulted in significant benefits for both the companies and the candidates. But, as with any other technology, there are certain hidden rocks to keep in mind when implementing AI in your processes.

So what exactly does it do and what kind of benefits it may bring? Let’s have a look.

How does AI help recruiters?

As we said, the Artificial Intelligence technology is capable of automating and simplifying certain tasks that do not require much in-depth analysis.

Now, take resume screening. Just how many resumes does one recruiter have to screen per day in order to find a perfect match? Will it be dozens or hundreds?

With AI, this process can be cut down to mere minutes – and the result will be even more efficient due to the elimination of human error possibilities and highly accurate analysis.

And that’s just one example. As AI developers say, almost any process can be automated – and that’s a perfect chance to bring more accuracy and relevance in the recruitment processes.

What benefits does AI bring to recruiters? 

AI in recruitment key benefits

Process automation sounds good – but definite benefits sound better. Here are the most obvious ones.

# Significant time-saving

Because AI can automate a number of mundane processes, it can significantly save the recruiters’ time and instead, allow them to focus on other tasks.

By automating your workflow, you will streamline the process, thus, making it more efficient. And resume screening is not the only example. Another one can be AI-powered chatbots that provide support for the candidates throughout all hiring process. 

Though seemingly minor, such little things can have a really big impact on the person’s perception of your company.

# Better hiring quality

Due to increased hiring process accuracy, the match between the candidate’s experience and proposed position will improve, leading to mutual satisfaction for both sides.

As well, because of better matching, there will be a lower risk of the candidate’s turnover, which is another important benefit.

# Increased candidates’ satisfaction

Faster resume processing and timely updates on interview status will lead to increased candidates’ satisfaction and a better attitude towards the company.

There is no need to say how important the candidates’ perception of the company is. Candidates that are positive towards a company are more likely to recommend a friend or simply keep in touch with the recruiters, which is a big plus.

What about the challenges?

Artificial Intelligence is quite a demanding technology.

It’s complex, demands a high level of expertise from developers, and has to be implemented by a knowledgeable specialist. As for recruitment, there are a few concerns to consider when thinking about AI implementation.

# Need in data

In order to provide accurate analysis and results, AI needs lots of data to learn on. 

By analyzing the history data, AI technology can build future forecasts and identify certain patterns in the data. So if you want to use AI in your recruitment processes, first, make sure that you have lots of data to feed to the AI model. As well, keep in mind that all this data has to be processed and prepared because AI cannot independently process raw data (like the one with missing values). And for that, you’ll need the help of a Data Scientist.

# Possibility of bias

AI learns on past data – and past data consists of a set of human behavior. So if an AI model sees that you’ve said no to 95% of black men in the past, it may as well learn that such candidates should not be considered at all.

To fix the issue, you will need a Data Scientist to remove all the patterns of bias and make sure AI will learn from non-biased data set.

# Mistrust towards the technology

Since ever, recruitment has been a process of interaction between people. So, as many specialists point out, can we really trust a machine with choosing future colleagues and teammates?

This question is really tricky. On one hand, the use of AI will provide a non-biased and perfect match, but on the other, it will completely exclude such human factors as likable personality, for example. And that’s one issue that every company should think about before implementing AI in its processes.

AI and the transformation of recruiting

If we talk about the specific use cases of AI in recruiting, we can name the following: AI in rectruitment use casesAs we can see, all these processes are aimed at eliminating mundane work and freeing the recruiters in order to let them focus on other things.

The “other things”, in turn, are vital for creating a healthy work environment as they include spending more time with the candidates and establishing relationships with them,  monitoring the candidate and their performance, timely assistance with any issues and identification of any problems, etc. 

There are already a few startups in the industry that provide AI-powered solutions for recruiters. Our top picks are:


cultivate logo

AI-powered tool for managers that analyzes their behavior and communication and provides insights on leveraging the leadership skills

Year: 2017

Country: San Francisco,United States

Funding: $2M



How to Succeed with AI in Recruiting

Sushman Biswas Sushman Biswas Former Editor, HR Technologist
Last Updated: December 16, 2021







Fig. 2. Strategic Impact Areas of AI in Recruitment

In addition to the strategic advantages, AI in recruiting can also help recruiters achieve tactical recruiting goals as well. Remember how we said modern recruiting is about creating bespoke experiences? AI in recruiting can help organizations with end-to-end candidate experience management as well.

Here are 5 Critical Recruiting Tasks that AI can Automate Intelligently:

  1. Candidate sourcing: Candidate sourcing is perhaps one of the most challenging and time-consuming recruitment tasks. While social media and job-boards have made sourcing easier, there is still no way recruiters can achieve personalization at scale using traditional tools. AI enables recruiters to automate their sourcing process, reach a wider talent pool, and personalize candidate interactions at scale.
    “AI is being used to match specialty recruiters, based on their track record by job type, to jobs that need candidates.  By accessing specialty recruiters with proven success and candidate relationships, employers can quickly and efficiently source quality candidates,” says Ken.
    Nimish Sharma, CEO and Co-founder at Workex.AIOpens a new window , says, “Finding the right talent has always been a daunting task for recruiters. With the help of AI, recruiters are now able to automate their sourcing process as well extend their reach to a larger audience. The deployment of AI in recruitment along with automation technology not only helps in finding the right kind of profiles for a job role but also helps them engage with these profiles using conversational platforms.”
  2. Lead nurturing: The next step after you’ve established contact with candidates is to engage and nurture them. Candidate nurturing is fast becoming one of the most critical parts of the recruitment process. Building a talent pipeline with passive candidates brings down recruitment costs and greatly reduces time-to-fill. Here’s where AI can help recruiters create and automate lead nurturing campaigns to deliver hyper-personalized messaging and content to cater to individual candidate needs. Ken says, “CRM and marketing automation systems that nurture leads are integrating AI and ‘chatbots’ with great success. These methods and technologies are also now moving into recruiting for effective lead nurturing, enabling recruiters to spend more time with interested leads versus finding them.”
  3. Candidate screening: AI-powered candidate screeningOpens a new window  solutions are emerging as a key segment in the AI recruiting space. The idea is to make objective, data-driven decisions when evaluating candidates. AI can reduce or even eliminate human bias when assessing candidates. “AI has an opportunity to bring objectivity to talent by focusing its lens on organizations before candidates. Corporations need a mirror to see itself, and AI could be leveraged to filter through the processes and datastreams generated within an organization to reveal problem spots and opportunities early enough for people to take action and create change,” says Sarah Nahm, CEO at recruiting software provider, LeverOpens a new window .
  4. Interviewing: Automated video interviews are probably the best current example of AI in recruiting. This practice goes way beyond standardizing the interview process and saving time. “With automated interviews today, you’ve got much deeper applications such as automated analysis of communications skills and even behavioral analysis of video interviews to predict job performance,” opines Ken.
  5. Onboarding: Personal AI Assistants, or “onboarding bots” can now integrate with HR management systems (HCM and HRIS) and essentially act as a new employee’s personal guide to their new workplace.

Also Read: 

The Rise of the Corporate Recruiter: Job Description, Salary Expectations, and Key Skills for 2020Opens a new window 

Given the massive impact that AI can have on recruiting productivity, speed, and cost savings, organizations that adopt AI in their recruiting processes now will gain a major advantage over their competitors. According to Deloitte’s 2018 ‘State of AI in the Enterprise’ surveyOpens a new window , 42 percent of leaders believe AI will be of critical strategic importance in the next two years.

“Scout has found that employers using machine learning algorithms in a marketplace recruiting setting have consistently lowered their time to fill by over 30 percent, increased their pool of qualified candidates and fill rates by up to 40 percent, and reduced cost per hire by 30 percent,” says Ken.

Key Concerns Around AI in Recruiting: Bias, Diversity, Inclusion, and Privacy

While AI recruiting solutions have certainly matured over the past two years, it hasn’t been smooth sailing all along. One of the major concerns with AI in recruiting has been its tendency to propagate human bias. As a data-driven solution, AI is only as good as the data it has been trained on. When training on historical data, it is likely that AI solutions can pick up patterns that exhibit human bias. If Amazon’s recruiting engine debacleOpens a new window  has taught us anything, it is to identify, measure and adjust for human bias in all AI solutions.

“When AI focuses on identifying talent and matching it to roles, it tends to propagate any bias that exists in the dataset it has been trained on. This means, AI runs the risk of reinforcing the unconscious bias that has existed in recruitment, and possibly even worsening the situation by distancing human judgment even further from the decision,” says Sarah. “Amazon was right to sunset their AI recruiting engine.  This is a great example of how AI is only as enlightened as the underlying data it is trained on.  I don’t believe the technology or data sets are ready for us to try to judge people and flatten them into a score. I do feel optimistic that AI can tell an organization a lot more about its own biases, exactly as Amazon was able to learn in this specific case.”

Interestingly, AI recruitment solution providers acknowledge that AI development is a tricky job, and it certainly needs expert oversight on issues like diversity and inclusion, algorithmic bias, and data security and privacy.

AI-talent assessment platform, HireVue, recently announced the creation of an Expert Advisory BoardOpens a new window  to help guide ethical AI development. “Any time AI technology is being developed for use in a context that can have an impact on people’s daily lives, it’s crucial to be approaching its development with ethical principles in mind from day one. As technology evolves over time, ethical principles should be reviewed and potentially updated to ensure that they continue to be meaningful guideposts,” says Loren Larsen, CTO at HireVue.

He adds, “The main concern with AI in recruiting is that, unless a process is built to prevent this from the beginning, it’s possible for algorithms to replicate, scale, and even institutionalize human bias. However, with rigorous testing processes that our IO psychologists brought with them from the traditional field of pre-hire assessments, HireVue is able to test for adverse impact against protected groups, remove any data points contributing to such bias, retrain the algorithm, re-test, and repeat until bias is mitigated. It’s possible to remove any problematic data points without losing predictive power only because HireVue Assessment algorithms can incorporate up to 25,000 meaningful data points related to job success.”

The real opportunity that AI presents in recruitment is scalability and automation to a practice such as industrial/organizational psychology that once relied on expensive consultation services. The predictability and objectivity of talent data can now be democratized and available to all, not just Fortune 500 companies.

Selecting Best-fit AI-powered Recruiting Solutions

As we’ve explored in the section above, training data integrity and quality are the biggest concerns around AI recruiting solutions. “When evaluating the claims of AI software companies, HR leaders should ask what the training data set is made up from. A tremendous amount of high-quality data is needed for an AI program to be able to provide insights. If an AI program is using resumes and job descriptions, for example, then it’s a pretty poor-quality data set since there’s no inherent validation of that information and most people copy-paste from other sources,” advises Sarah Nahm of Lever.

Loren Larsen from HireVue, believes that gauging vendor expertise in AI-powered recruiting is also essential. He suggests five crucial questions to ask AI-recruiting vendors before investing in a solution.

5 important questions to ask about your AI-powered recruiting solution or vendor:

  1. Does the vendor have deep expertise in the hiring space? Data science capability alone is not enough. AI for hiring relies on a complex set of factors relating to data security and privacy, validation, adverse impact, compliance, and the regulatory environment, accessibility as well as objectivity, and diversity efforts that must be understood in depth in order for a solution to be effective.
  2. Was the product developed solely by hiring and data science experts, or were social scientists involved? Having IO psychologists as part of the development process ensures that proper testing for impact, efficacy, and candidate experience will be central considerations.
  3. Does the tool or solution have a track record of success with organizations of your size? Better to be a partner to an AI vendor, not a beta tester.
  4. What kind of data is being used to train AI models? All training data is not created equal. Some is biased and some is simply not proven by research to be truly predictive of job success.
  5. Does the vendor audit its algorithms for adverse impact (bias)? One of the biggest promises of AI is its ability to make hiring more objective and fairer. That said, AI is like any powerful technology: improperly built and tested, there is the potential for harm. Vendors should be able to provide full documentation around their process for mitigating bias.”

In addition to establishing the efficacy of AI recruiting solutions and ascertaining data integrity, HR leaders must also consider the

business outcomes of deploying a smart recruiting solution. “The most important questions should relate to the impact on your goals and return on investment. For example, if your goal is to improve candidate flow, you’ll want to take a look at the recruiting pipeline, see where the bottlenecks are and determine where you need improvement the most. Then, you can look at the expected improvement of an AI solution against the cost.  Perhaps AI can double your pipeline, but what are the other options and what is the cost of the solution, including implementation, maintenance, etc.?” says Ken Lazarus of Scout Exchange.



Recruitment as we know it, is certainly changing and we’ll see new skill-sets and job roles emerge over the next few years. As the adoption of AI recruiting solutions increases, the accuracy and efficacy of these platforms will continue to improve. As with all other business technologies, there is no one-size-fits-all approach to choosing the best-fit recruiting solution. Most vendors offer unique AI solutions for every business segment and we recommend creating a data checklist before investing in an AI recruiting solution. Lastly, measuring the success of AI is no different than any other business initiative. “It gets back to understanding your objectives and setting measurable goals from the outset. For Scout, that means meeting our own goals of greater numbers of high-quality, satisfied placements happening faster than ever, as well as meeting clients’ goals – typically related to reach, speed, cost, and diversity,” says Ken.

Words to set an effective strategy by!

In the next episode of our “Succeeding with AI in HR” series, we’ll dive deeper into how AI is transforming Human Capital Management, how you can deploy AI-powered HCM solutions and measure the ROI of your AI initiatives.

Read our previous issue: The Beginner’s Guide to AI in HROpens a new window 

how is ai used in recruitment

AI is being increasingly used in recruitment to streamline and enhance various aspects of the hiring process. Here are some ways AI is used in recruitment:

  1. Resume Screening: AI-powered systems can analyze and screen resumes quickly and efficiently, saving time for recruiters. These systems use natural language processing (NLP) algorithms to extract relevant information from resumes and assess candidates based on specific criteria or keywords.

  2. Candidate Sourcing: AI can help recruiters identify potential candidates by searching through vast databases, professional networking platforms, and online communities. AI algorithms can match job requirements with candidate profiles to create a shortlist of qualified candidates.

  3. Chatbots and Virtual Assistants: AI-powered chatbots and virtual assistants can engage with candidates, answer their questions, and guide them through the application process. They can provide immediate responses, schedule interviews, and collect initial candidate information, providing a more efficient and personalized experience.

  4. Video Interviews and Assessments: AI technology enables automated video interviews and assessments, where candidates respond to pre-recorded questions. AI algorithms can analyze facial expressions, voice tone, and language to evaluate candidate responses and assess their suitability for a role.

  5. Predictive Analytics: AI can analyze large volumes of recruitment data to identify patterns and make predictions about candidate success and job fit. This helps in making informed decisions regarding candidate selection and reduces bias in the hiring process.

  6. Employee Retention and Succession Planning: AI can be used to analyze employee data and identify factors that contribute to employee turnover or success. This information can help organizations develop strategies for retaining top talent and plan for future succession needs.

It's important to note that while AI can offer significant benefits in recruitment, it should always be used responsibly and with careful consideration to avoid bias and ensure fairness in the hiring process.

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