There is a lot of talks about Artificial Intelligence (AI) lately. If we have to believe some people AI will rule the world in the future. Personally I don’t believe this will happen so fast (and maybe not at all) as we, human like to make tasks more intelligent but have no benefit of creating an artificial human. For example we are creating autonomous cars but not a human like robot who can drive in a car like a human. The scenario of the movie I, robot with Will Smith (see the trailer below this post) is not very realistic because the robots created the intelligence to help people in the housekeeping. Even if there is going something wrong with training for these robots (for example they get wrong training’s data) and become fighting machines against humanity they are not made for the task of management or organisation of other robots, or even only to fight against humanity is far from inefficient so relatively easy to knock down with specialist fighting machines, trained (so feet with trainingsdata) to destroy the housekeeping robots.

Anyway, a nice intro based on some questions, I got from somebody who knew a lot about AI but doesn’t understand how it is working exactly. So back to the future reality, AI in recruitment.

Based on some research, I summarized some blogposts and solutions to illustrate the possible impact on Artificial Intelligence (AI) in recruitment.

The credits for the picture belong to the blogpost 7 Recruiting AI Technology Terms You Need to Know. The post describes AI in recruitment from a more technology perspective. In this post I try to give an view on the possibilities when you apply AI to recruitment.

In the post 4 Ways Artificial Intelligence can change the Recruitment Game the following ways are described:

1. AI facilitates contextual-based search
One of the best-kept secrets to identifying the right candidate is to understand the employer’s context first. This is something that is not achievable via your Boolean searches or archaic candidate screening methods. For instance, recruitment patterns in an organisation that are highly preferred for a particular job profile, work experience of the candidates and competing employers, all form a perfect job hunt scene. Artificial Intelligence although in its embryonic stage is assisting employers and talent acquisition experts to tap in such dynamics.

Fully agree. Here is nice challenge. Deep learning looks a like perfect solution but in practice it seems to be hard to have enough data (accessible). Supervised learning maybe the solution. We are trying to do this in practice within my company ContentForces.

2. Analyses social footprints
AI in order to acknowledge a candidate’s skillsets and expertise taps into several social websites. This is not only limited to social websites, but is extended to career portals, knowledge sharing websites, etc. where candidates tend to update details about projects that they were involved in. The data accumulated is then utilized for validating the skills as mentioned by the candidates to help employers in understanding the kind of projects the candidate was involved in, his/her level of dedication and engagement and what kind of opportunities would interest the candidate in the near future.

Theoretically yes. But in practice you need to get access to the data. In case the candidate provides this, it is much easier but this will be only access to the “good information”. Anyway data is the holy grail.

3. Helps find the right and passive candidates
AI tools by helping to tap candidates with the right set of skills and experience help employers and recruiters to narrow the talent hunt. In addition, it helps to prioritize candidates within the talent pool itself. For example, AI would classify and prioritize candidates, who are willing to relocate for working with the company for long-term? It does it by putting-forth a preformatted set of questions to the candidates. This shall make it a lot easier for HR professionals to shortlist and screen interested candidates minus the clutter saving them time and efforts.

Indeed, it will improve the match and pre-screening will reduce bothering candidates that are not interested in the job at all. The process is very connected to gathering the data. Chatbots may also help a lot (read about it later in this post)

4. Quality hires
Often, recruitment and HR experts look at the candidates-to-employees conversion ratios when it comes to measuring the success of a hiring campaign. With technology like Artificial Intelligence, the gap between identifying potential candidates who will take up the job is set to become narrow. Thus, the shift from quantity to quality recruits.

As mentioned under point 3, recruiters will gain a lot of needed respect.


The second post is about my favorite chatbot (as you may know we are developing a chatbot for recruitment). In ChatBots in Recruiting, the following 3 reasons to use chatbots are:

1. Keep Candidates Interested
CareerBuilder’s data found 67% of job seekers have a positive impression of a company if they receive consistent updates throughout the application process. Yet, when asked how long it took an employer to get back to them about their application, 43% of candidates questioned in a recent Workopolis poll said never.
So a good working chatbot can start and especially keep a personal conversation about the progress. Keeping the conversation, it can ask questions and collect very useful data this way. It can be used as a pre-screening and for the on-boarding process.

It doesn’t always have to be Facebook Messenger or Skype bot that keeps the candidate informed, but better a omnichannel bot that communicates via the users favorites chatapps but also uses more traditional channels like email, apps, website and SMS.

2. Speed Up the Process
Using a chatbot for Q&A and to help candidates through the application process will ultimately produce better quality candidates for the company overall because the most qualified candidate who is likely to have other options will need more questions answered and points clarified throughout the process to help them make a final decision.

With 77% of candidates stating they feel job ads should include more information, these benefits chatbots bring to the table are crucial. Add these to the fact that they would be available 24/7 and could potentially answer questions in all sorts of different languages, these automated systems would be just about any recruiter’s to speed up their time to hire and increase the quality of candidates.

As already explained in the first point Keep Candidates Interested there is more interaction because of the conversation. The conversation helps the recruiter but also the candidate to decide if the vacancy matches. There is a pre-selection for the candiate, as well as for the recruiter. This is speeding up the process.

3. Save Money
The use of chatbots is not a new concept to many industries such as customer service and sales. While completely automating sales and customer service is not possible, as is the same with recruiting, incorporating a chatbot into their processes has shown for some major potential annual savings. A study by the BI Intelligence team found that by using chatbots in customer service, the annual savings could result in about $23 billion a year.

What can I see more: money talks.

And then some examples that (may) work already in practice nowadays

Pomato is a visual assessment and testing tool for recruiters to hire technical candidates. In other words you drop a CV in the Pomato and it tells if it is a suitable candidate. Below the explanation in the movie.

Probably this fits the best in de 1. AI facilitates contextual-based search approach and 4. Quality hires.

From the movie below, it looks like Arya helps with search the best candidates.

On the website Arya mention the following solutions:

  • Automated A.I. Sourcing: create pipeline with the top talent who are the best fit for the job.
  • Candidate Engagement: Leverage extra bandwidth to spend time engaging with candidates
  • Mover Predictor: Pursue quality candidates who are ready to make a change by gauging their likeliness to move jobs — measured by three levels of mover probability: low, medium, and high.
  • Best Fit Identifier: Identify organizational DNA alignment in candidates — taking a look inside their story and discovering the right fit for an organization.

In the perspective of AI in recruitment it fits the best in 1. AI facilitates contextual-based search and 3. Helps find the right and passive candidates.

AI in recruitment is the future (at least that is my vision). If you would like to know more or help to realize this vision, please contact me via the contact form.

Then the promised bonus with the trailer of the bad AI experience movie I, Robot

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