How is AI impacting how we source talents?

In recent years, artificial intelligence has revolutionized many sectors, from marketing to health to finance. AI in recruitment: just a trend, or a real opportunity? Let's see what algorithms can bring to this aspect of human resources.

In this article, we will explore:

1. What is Artificial Intelligence?

2. The main benefits of AI

3. The limitations of artificial intelligence in recruitment

4. What problems does AI solve in recruitment?

5. On which recruitment tasks is AI optimal?

6. Optimized searches thanks to AI

7. Artificial intelligence serving HR

What is Artificial Intelligence?

Artificial Intelligence (AI) is a computer program capable of performing a task that usually requires human intervention.

Smart solutions have been part of our daily lives for several years now. Their recent evolutions mainly come from machine learning.

This type of program is capable of "learning" to perform a task by identifying regularities in data.

This innovative technology is commonly used in many cutting-edge fields. For example, in medical imaging. The principle is simple, the AI is given images and the associated diagnosis. It undergoes a learning phase from this data. It is then capable of giving reliable diagnoses.

Today, the use cases of AI are varied. Thanks to their experience, AI researchers have been able to identify tasks where AI is highly efficient and others where its use is particularly inefficient.

To understand how and when to use it in recruitment, let's look at these edge cases.

The main benefits of AI

After several years of use, artificial intelligence researchers have identified tasks where AI excels:

→ Analyze a large amount of data AI is capable of processing a huge amount of data with high precision, in record time.

→ Compare data across multiple factors Once the data is analyzed, AI is capable of comparing different pieces of information, then recognizing patterns and trends in the data that would be difficult, if not impossible, for a human to detect.

→ Perform automatic tasks Once patterns are spotted, AI can perform repetitive tasks more quickly and accurately than a human, while being less prone to errors. This may include tasks such as sorting and filtering applications for a position, scheduling interviews, sending follow-up emails, and much more.

→ Predict outcomes Finally, once the patterns are observed, AI can help predict future outcomes and suggest informed decisions based on these forecasts. For example, AI can give you an estimate of how long a future employee will stay on the job based on observations from previous situations, provided there is enough representative information.

The limitations of artificial intelligence in recruitment

Even the best tools require a learning curve. To effectively use this type of software for your recruitments, you need to avoid these common mistakes.

Poor quality data

Data serves as the raw material for machine learning algorithms. Its quality has a direct impact on the results obtained.

In recruitment, we distinguish two types of career data.

✅ Standardized data: name, current company, education...

This type of information is processed without a problem by an algorithm.

❌ Non-standardized data: job description, cover letter

This information is not usable as it is.

But this is not an unsolvable problem. Thanks to automation tools and appropriate processes, an HR service can standardize the data incorporated into the ATS as much as possible. Thus a good quality of information is maintained and the artificial intelligence operates optimally.

Biases and Discriminations

AI mimics the human behavior it is taught. If the chosen data presents biases or discriminations, the algorithm will automatically reproduce them. It could, for example, favor or disadvantage talents based on their gender, age, level of diploma, ethnicity, etc.

Therefore, it is essential to control the information provided to the AI and ensure that it does not contain any bias or discrimination.

All-powerful algorithms

At Lymia, we see AI as a tool. Humans should remain in control and set it up as they see fit.

For its part, the software should present the results in a clear and understandable way.

In this way, the recruiter benefits from the advantages of intelligent automation (time savings, qualified profiles, atypical suggestions) but remains in control of decisions.

That's why Lymia does not incorporate candidate scoring. Assigning a score to a profile doesn't seem appropriate to us. How can we reduce the complexity of personalities and careers to numbers? Furthermore, this practice tends to give a form of authority to the recommendation of algorithms.

We then find it difficult to avoid the black box effect since the calculation of the score remains mysterious. A big no go for Lymia.

What problems does AI solve in recruitment ?

We won't argue otherwise, artificial intelligence is an impressive tool. But, it's not the miracle solution to all recruiters' problems.

Here are 3 problems currently facing the recruitment world and possible solutions with AI:

👉 Falling candidate response rates

You probably don't always respond to a proposition received on LinkedIn.

Candidates too! The more they are solicited, the less they respond to job offers or interview proposals. Especially if they don't know the recruiter contacting them. The worst rates are recorded on LinkedIn "cold messages". (5-20% according to an Evaboot study)

✅ With AI, you can easily find qualified talents with whom you and your teams have already exchanged. You multiply your chances of getting a response, despite a tense job market.

👉 Inefficient search functions

Internal or external databases like LinkedIn incorporate search engines (boolean, keywords).

Unfortunately, their operation is often simplistic and poorly suited to the needs of recruitment teams. They do not allow for all the necessary factors to be taken into account for a precise search. The tool proposes a list of profiles of no interest for the considered position, which then need to be sorted one by one.

Guaranteed time loss!

✅ With AI, all your criteria are taken into account. The intelligent algorithm even suggests other interesting paths.

👉 Underused databases

Companies have interesting databases but they are often underused.

The candidate profiles added to the ATS are very numerous, and rarely optimized. Due to lack of suitable technology, recruiters then lose the opportunity to interview qualified candidates. This is all the more regrettable if these talents have already shown interest in the company.

✅ Thanks to AI you can identify dozens of interested and highly qualified profiles for your search in just a few minutes.

What recruitment tasks is AI optimal for?

As we have just seen, AI performs well on certain recruitment problems. Now let's see what its advantages are compared to traditional tools and the tasks on which it is optimal.

The advantage of AI over traditional tools

You know from experience, the stages of sourcing and shortlisting are particularly time-consuming.

The reason? Traditional tools are not very efficient. As a result, many companies do not capitalize on valuable work: The collection of talents and information already carried out or the human relationships already created with candidates.

Even worse, to compensate for this lack, recruitment officers spend more time and additional budgets. (LinkedIn, recruitment firm, etc.)

It goes without saying that these precious resources can be used more strategically. Does AI solve these recurring problems?

The most adapted phases

The recruitment process is often represented by a funnel. A large number of candidates enter, a selection is made at different stages, until the best talent for the given position is hired.

This funnel consists of 4 main stages, 3 of which are the responsibility of the recruiter.

Stage 1: Sourcing

The recruiter identifies potential candidates from an existing base (ATS, LinkedIn, applications from job offers.)

Stage 2: Shortlisting

The recruiter selects the best candidates for the position to be filled, according to defined criteria: skills, experience, degree, soft skills, etc.

Stage 3: Interviews and decision

The candidates are contacted, then a series of interviews leads to a final opinion. The most promising talent is hired.

💡 Artificial Intelligence is an ideal tool for sourcing and shortlisting. A recruiter already selects candidates automatically (search engines, filters). Thanks to AI algorithms, they can go further in optimizing these two phases.

While AI offers many applications, it should be avoided for making contact, one-to-one exchanges, or video analysis. The human dimension is central to the success of these tasks.

This point is particularly important if you are looking to take care of your candidate experience and your employer brand.

Optimized searches thanks to AI

Here are 3 areas where AI can help you multiply your results.

👉 Reduced search time

Thanks to automation tools like Lymia, you apply your search criteria in a few clicks and get dozens of highly qualified profiles in your ATS in just a few minutes.

✅ You do not waste valuable time on talent sourcing.

👉 A selection of relevant talents

Thanks to its advanced analysis capability, an AI recruitment solution like Lymia offers you a list of talents much more relevant than your traditional search tools.

For example, if you are looking for an experienced HRD, a well-thought-out algorithm selects profiles with +5 years of experience as HRD rather than others whose CV mentions HRD several times, without necessarily having held this position.

✅ The entirety of the talents proposed is relevant and qualitative.

👉 Increased results

Because AI search is more flexible, algorithms suggest profiles that a human would not typically include in their selection.

For example, if you are looking for a talent graduated from school A or B, the AI also suggests graduates from school C or D just as relevant but less known.

✅ You no longer miss potential employees rarely highlighted.

Artificial intelligence at the service of HR

AI should be at the service of the recruiter, this is the whole concept of "augmented recruiter".

Its principle? While technology optimizes operational processes, the recruiter focuses on decisions. This approach is a real opportunity for companies. They can gain in efficiency and quality of recruitment, while reducing costs.

You got it, augmented recruitment solutions by artificial intelligence are fantastic tools, provided certain constraints are respected.

👉 Limit their use to sourcing and shortlisting phases.

👉 Data must be standardized and updated regularly.

👉 The recruiter is in control and can quickly explore why AI recommendations, then make his choice.

👉 No black box algorithm that makes authority.

👉 The analysis must focus on complete career data rather than counting keyword occurrences.

And voila, you are now equipped to identify the best AI solution to optimize your recruitment!

At Lymia, we are committed to applying all these good practices and much more. Our intelligent solution allows our clients to facilitate their recruitment, without wasting unnecessary time.

But since a demo is worth a thousand words, we propose you to see our tool in action.