AI’s Potential to Improve Your Recruiting Efforts, Part of the New Talent Challenge Series

This is the third of our series, which takes a closer look at the challenges that businesses are experiencing in regards to talent acquisition during the pandemic. Known as the Up-and-Coming Talent Challenges Series, it intends to explore these complex issues further.

Deploying the right people into vacant roles can often be a challenging task for businesses. One common reason is the shortage of necessary skills or a culture misfit with the organisation.

Finding the perfect candidate can be an arduous task, and it can be even more challenging if the candidate who has made it through the entire recruitment process turns down the offer. Additionally, having hired top talent only for them to leave shortly after joining the team can be problematic.

Personnel strategies can be difficult to manage while also sustaining profitability, especially when employment offers are rejected and resignations are submitted prematurely. This is an inevitable result of HR work, because sometimes job offers are turned down or new hires leave quickly due to unsatisfactory circumstances.

Although it is an inevitable reality, it may be possible to reduce the frequency of such occurrences. Fortunately, AI can be relied upon to offer a helping hand, which is fantastic news.

The Problem with Traditional Selection Methods

The Human Resources (HR) department typically follows a defined process that entails advertising the open position, assessing applications, conducting interviews, and selecting the most appropriate candidate. The recruiter evaluates the applicant’s qualifications in relation to the job requirements before making a final decision. Factors like experience and suitability for the organisation are also considered during candidate assessments.

Since these evaluations can be subjective, recruiters may seek input from subject matter experts to evaluate a candidate’s suitability for a specific role. However, decision-makers must consider a variety of factors, including their personal prejudices and biases. This increases the likelihood of a candidate being offered a job for which they are not entirely suitable, resulting in the possibility of an offer being declined or employee resignation shortly following their employment.

As professionals who actively recruit managers, they are mindful of the potential risks that come with hiring, such as candidates declining offers, submitting resignations, or frequently job-hopping. Nevertheless, evaluating these possibilities is heavily subjective, as it is based on the recruiter’s understanding and interpretation of information which may not always be accurate.

It is apparent that this subjectivity could significantly affect the hiring decision and undermine the overall credibility of the process. On the one hand, recruiters’ subjective assessments may be incorrect (especially if they lack experience). On the other hand, many of these evaluations fail to consider historical data, which could provide valuable insights into the process and identify areas for improvement.

If there is a risk within the recruitment process, it is clear that effective talent management will be difficult. Luckily, Artificial Intelligence provides a solution to this problem.

Clarifying the Function of AI

AI can enhance recruitment efforts by supplying additional context for assessments. Machine learning models have the ability to examine past recruitment data and create a score that reflects the recruiter’s decision-making ability, considering a variety of factors.

Due to their capacity to uncover concealed patterns and behaviours that aid in determining a candidate’s suitability for a job, predictive models are exceedingly beneficial for HR specialists. In addition to this, Artificial Intelligence can be applied in several other aspects of Human Resources Management. Specific ways in which AI can be utilized for excellent results include but are not limited to:

  • Effectively filtering through numerous applications based on a set of criteria
  • Dispensing guidance on the optimal way to align available talent with your organisation’s prerequisites
  • Applying past recruitment data to recognise voids and offer solutions
  • Suggesting ways to improve the onboarding of new hires

Businesses have the opportunity to form engineering teams that meet specific criteria quickly with the assistance of AI, thus generating high-performing teams. Works utilizes Staffing HeroTM, a one-of-a-kind AI-powered solution, to pick out the ideal individuals based on their experience, track record, and client preferences.

Through the use of our sophisticated search technology, we can quickly and efficiently identify and choose the best specialist for each of our clients’ projects from our broad pool of technical resources, enabling us to assemble a delivery team. In addition to client projects, we use this technology to manage our own recruitment procedures.

With the aid of AI, we have been able to unlock the full potential of Staffing HeroTM, which employs big data and state-of-the-art algorithms to generate meaningful insights. Although our human resources staff continue to retain overall control when it comes to making hiring decisions, they can now make informed choices by leveraging data provided by our AI system. Consequently, we have been able to reduce the likelihood of an unfavorable outcome while increasing the probability of a successful recruitment procedure.

Constructing a fitting solution was a challenging task. Creating the algorithm and teaching it to provide the expected outcomes was a major investment in terms of time. However, the outcomes we have attained through Staffing HeroTM serve as evidence that the effort was well worth it, since it has benefited both our recruitment and team development efforts positively. However, it is important to note that introducing AI to the recruitment process comes with its own set of challenges. To achieve the most favorable outcomes, it is necessary to surmount a few hurdles.

The Drawbacks of Artificial Intelligence in Recruitment

Even though AI solutions have the potential to transform the hiring process, they need to be closely monitored to avoid potential hazards. The most common hazards related to AI solutions comprise:

  • AI that is well-educated is required.

    An algorithm that has not been trained properly is more prone to providing erroneous recommendations and skewed insights, which could negatively impact your organisation.
  • Scrubbing the data and verifying the model’s precision are also vital steps.

    In order to properly train these models, it is necessary to utilize a significant amount of data from various origins. However, this presents a new obstacle: the time and effort required to clean up and organize the data for productive use.
  • All of your stages necessitate verification.

    The current recruitment process may have flaws that result in job offers being extended to inappropriate candidates. It might be necessary to reassess the methodology to guarantee that all pertinent elements are taken into consideration when making decisions. To avail of the entire potential of an AI solution, it is crucial to review and adapt the process as necessary.
  • Your team needs to be trained.

    It may be astonishing, but certain Human Resources (HR) departments have yet to embrace new technologies, despite the potential for operational efficiencies. Therefore, it is crucial to provide staff with a thorough understanding of the AI solution, encompassing its goal, the benefits it can provide, and the necessary procedures to achieve those benefits.

To sum up, AI can serve as a useful tool for companies looking to swiftly and effectively identify suitable candidates. Although there are some difficulties associated with using predictive models for recruitment, the algorithms can be improved with the appropriate expenditure of time and resources. Moreover, those who use the AI technology should be trained adequately to obtain the best results. Ultimately, AI has the potential to enhance the recruitment process by minimizing dropouts and rejections.

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