For most organisations, it is becoming more crucial than ever before to ensure a top candidate experience for those who are applying to the organisation. It is a known fact that candidates who have the right skill sets have plenty of job options to choose from. What generally tilts a company in favour of a particular candidate is the candidate experience.

So what exactly is candidate experience?

Candidate experience is how a prospective employee perceives the company’s brand throughout the hiring process, right from the job description to interviews to the onboarding stage. Does a candidate feel welcomed into an organisation? Is the onboarding process smooth and seamless? Are new employees made comfortable with the right mentors for guidance? All these factors and more are important to convince a candidate to not just join an organisation but also stay in the organisation long term.

These days, companies are experimenting with chatbots and virtual assistants (VA) to see how they could help with the candidate experience. Chatbots and VAs help businesses save time and money while increasing the efficiency of the hiring process.

Chatbots and VAs are most often used interchangeably. However, they are quite distinct. Chatbots are software programmes that can simulate human-like conversation. They are built using NLP (Natural Language Processing) technology and ML (Machine Learning). VAs, on the other hand, help with the carrying out of daily tasks like the making of calls. They are AI-driven and their accuracy improves with time. Some of the well-known VAs that many of us have interacted with are Siri, Cortana, and Alexa.

Let us explore some of the areas where chatbots and VAs are making their presence felt!

• Initial engagement and screening:

  Chatbots and VAs have the ability to ask relevant questions to candidates and screen resumes. We are all aware that one of the biggest challenges in recruitment is the unconscious bias that could creep in. Chatbots and VAs remove this bias by evaluating candidates objectively. Thus, all deserving candidates stand a fair chance of getting the job by showcasing their skills and experience!

• Handling frequently asked questions and queries:

  Imagine a talent acquisition professional getting bombarded with questions and doubts from scores of candidates. To top it all, most candidates have the same doubts plaguing them. In such cases, it is a good option to use chatbots that can respond to these questions for the umpteenth time without getting flustered! Chatbots ensure consistency in responses to candidates. Their use also gives talent acquisition specialists the time to focus on more strategic tasks and initiatives without getting bogged down by answering routine queries.
  

• Scheduling interviews:

  VAs can schedule interviews for prospective candidates by syncing the calendars of interviewers and candidates and finding suitable time slots. Even mails to the candidates regarding the time slots can be sent out by the VAs.
  

• Collecting and analysing feedback:

  If you are keen to improve your hiring processes as an organisation, then taking the help of virtual assistants might just be the way to go! They are capable of sending out and collecting feedback forms after interviews. Not only that, they can even analyse vast amounts of data, detect trends and help HR managers to make informed hiring decisions.
  

• Onboarding assistance:

  The time that a candidate takes to become an employee and join an organisation is most crucial. Organisations must ensure that the transition phase for the employee is smooth. There are several steps involved in the onboarding of candidates, right from document collection to reference checking to answering the queries that new hires might have. All these tasks and more can be efficiently taken up by VAs, reducing the possibility of manual errors and improving the candidate experience at the organisation.
  

• Continuous engagement and talent nurturing:

  Employee surveys can be run with the help of VAs. The VAs are capable of understanding the learning and development needs of newly-hired employees and recommending relevant courses that they could take to improve their existing skill sets.

There’s no doubt that chatbots and VAs are making their presence felt in almost all areas of recruitment. They have the ability to deliver a level of personalisation that even humans might not be able to match. Their use is driving efficiency, impact and improved candidate experiences across all areas of recruitment. A Gartner survey revealed that 56% of HR leaders have admitted that their HR technology solutions and strategy do not match current and future business needs. For organisations that have not jumped onto the chatbot or VA bandwagon yet, it is certainly time to do so without further ado!

The jobs, they are a-calling!

Recruitment is a full-time effort for growing companies as they seek to fill their open positions with talented individuals wh-o can contribute their time, energy and innovative ideas that fuel organisational growth. Artificial intelligence (AI) is transforming the world of recruitment by giving recruiters new, cutting-edge capabilities that help them hire the best candidates for open roles. From spotting cheating at interviews to new-age tools for better onboarding, AI is indeed a game changer.

There is an important aspect of recruitment that has been silently pervasive and difficult to root out to date: bias. Bias in recruitment, whether favourable or unfavourable, can mean that the wrong candidate lands up in a position at best. At worst, this insidious trait can hurt organisational growth in the long run.

Yet, bias is inescapable. All of us accumulate biases with every encounter we have with the world at large: biases about situations, people, backgrounds, cities, languages and cultures. We favour something in every instance, or we avoid something. This is because we are all too human.

This is where AI can be useful. Technologists and recruiters have particularly worked together to eliminate human bias during that all-important step of screening. Let’s explore how.

AI-powered resume screening software operates on predetermined criteria, such as specific skills, candidate diversity criteria or certifications, using keywords. Such screening is particularly useful when sifting through thousands or tens of thousands of resumes that land in inboxes from corporate career pages, job boards and college recruitment drives. It is manually impossible for a limited number of recruiters to sift through such numbers without letting biases in, such as recency bias. Even more pervasive are biases such as the similarity bias (where the candidate(s) exhibit some affinity to the recruiter), the gender bias or the halo effect (when some positive trait of the candidate overshadows everything else).

Consider statements such as:

• “The candidate is from XYZ College. He must be a good candidate!”
• “She is in her early twenties. Can she stick on in this job for a few years?”
  
• “There are so many candidates! Let me just pick the last twenty I reviewed.”
  

This can happen in the best of organisations, and AI can mitigate this in one fell swoop. Indeed, automated candidate screening is no longer just a fringe benefit: it is a mainstream feature that can turn into a competitive advantage for many companies!

In a nutshell, AI-powered screening can help the enterprise with value-based recruitment, a strategy that puts the right candidates in front of recruiters and hiring managers. Value-based recruitment is beneficial to the recruiting organisation in many ways: besides burnishing the employer brand, it also contributes to a peaceful environment at work and ensures that more engaged employees are at work, resulting in higher productivity.

What, then, about bias in the AI itself? The lack of transparency within the AI algorithm being deployed, and any resultant biases it brings into the process, has emerged as a significant challenge to hiring bodies. Here are some specific bias mitigation strategies HR leaders must employ:

• Ensure your algorithms train on diverse and representative data.

  AI is only as good as its training data. If the data is skewed in any manner, the resultant algorithm will exhibit bias. HR leaders must tackle this from training data onward.
  

• Perform regular audits and checks of the AI.

  AI is an adaptive technology that learns as it operates on new data. Regular checks on the algorithm and any necessary corrections are imperative to ensure no biases creep in over time.

• Implement transparency in algorithms.

  AI cannot operate as a black box. The candidates whose data AI operates on must be given information on how it operates and what the logic is behind certain decisions. Otherwise, trust gets eroded and this can hurt the brand, besides opening up the possibility that the best candidates may not apply for the vacancies.
  

• Provide adequate data privacy and security safeguards.

  It bears repetition—AI is only as good as its data. The data must be safeguarded. Sensitive candidate information must be handled confidentially. HR leaders must communicate the scope and purpose of any data collection to candidates and seek permission if necessary.
  

Not surprisingly, these very strategies form the bedrock of a fair recruitment and evaluation process that is enabled by AI. Crafting an effective recruitment strategy powered by AI from screening onwards takes time and effort. As discussed above, it is rooted in the pillars of representative data, security, transparency, audits and checks.

When done right, AI-based screening can allow your recruitment to fly, giving you speedy access to the best available talent for your open positions! Talk to HirePro, the new-age AI-powered recruitment platform, to understand our AI-based screening tools. As an ISO 27001-certified and GDPR-compliant organisation, HirePro’s technology is built around the pillars of fair technology-powered recruitment. Let’s make your hiring Fearless!

Candidate screening is one of the most important stages of the recruitment process. Nevertheless, it has been the proverbial Achilles heel for most recruiters. Take a look at these numbers, for instance. Out of 250 resumes received for an open position, nearly 220 are from unqualified candidates, which is a whopping 88%. Recruiters need to spend significant hours just filtering out qualified candidates before they can proceed with further hiring processes. Even though Applicant Tracking Systems (ATS) are used extensively, they still do not solve other problems associated with manual or semi-automated screening. For instance, quality of hire is not a guarantee even if you have a qualified candidate. Sometimes, resume formats may be rejected by the ATS since they do not “fit in” the generic format expected by the tool. Unconscious hiring bias can come into play when human recruiters screen resumes manually. Apart from that, much of manual screening involves recruiter’s expertise and experience, and making sure that hiring criteria are met.

Clearly, manual screening of candidates may result in qualified candidates getting filtered out due to inadvertent errors by humans. Automated candidate screening with artificial intelligence (AI) and machine learning (ML) can transform candidate screening in several ways.

How AI powers candidate screening

Automated screening tools that leverage AI or ML offer tremendous improvements to the candidate screening process.

Parsing and keyword matching:

Resume parsers can extract information from resumes and organise them into a structured format that is more useful. Resume parsers leverage deep learning and ML algorithms and natural language processing (NLP) to break down unstructured resumes into useful structured data. For example, resume parsers would be able to extract personal information, work experience, education and certifications from resumes. Unlike traditional parsing that was rule-based, resume parsers that are based on AI or ML are flexible and scalable. They can handle a wide variety of formats and are useful for high-volume recruitment. They can even understand the semantics, where they are able to determine the relevance of experience or skill for a specific job description.

Similarly, AI-based keyword matching is contextual, which is unlike traditional keyword matching in ATS software. The ability to process natural language means that keyword matching is done in the context of candidate experience and the job posting, resulting in far more accurate and relevant results.

Automated scheduling and workflows:

Automated interview scheduling can save recruiters precious hours during the initial screening process. With the AI tool checking on interviewer and candidate dates and setting the interview at a mutually convenient time, recruiters are free to just do a final check and confirm the interview. AI-based software can scan thousands of databases and repositories for potential candidates who have been passive so far. Automated messages can be sent to such candidates, and they can further be engaged via chatbots or email.

Talent assessments:

With skill-based hiring taking the lead, talent assessments have become the de facto standard to evaluate candidate proficiency. AI-powered skills and behavioural assessments can save companies resources, time and money while giving candidates the flexibility to take the assessments at a time and place of their choice. With automated identity detection and online proctoring, there is the assurance of no unfair practices. Test scores can be calculated and sent to applicant tracking systems (ATS) in the recruitment workflow, thus ensuring that there is minimal manual intervention.

Virtual interviews:

Virtual interviews became common in post-pandemic times. They continue to be used, especially for initial candidate screening. AI adds a new dimension to virtual interviews. AI-based software can detect facial expressions, body language and speech patterns that can be further used to make data-driven decisions regarding candidate suitability for a profile.

There are several advantages to using AI in candidate screening. AI-based screening encourages diversity hiring since there is minimal human bias during the hiring process. With automated scheduling and virtual interviews, candidates can be easily accessed and assessed, which in turn leads to improved candidate engagement and a positive experience. By automating repetitive tasks, recruiters experience increased productivity and efficiency and can focus on other activities that require human intervention. The use of AI in candidate screening leads to data-driven decision-making rather than relying just on gut instinct. Predictive analytics can help determine the likelihood of candidate success, which will result in improved and more efficient hiring.

AI-driven candidate screening has the potential to transform recruitment. Companies must be mindful of ethical AI practices, maintain transparency with candidates and adhere to data privacy regulations. Companies also need to invest in continuous improvement to enhance the effectiveness of AI-driven automation and fine-tune the algorithms. By striking the right balance between automation and human oversight, companies can undoubtedly achieve excellence in talent acquisition.

Can non-living things learn? If you had asked this question to a room full of children in the early 1900s, you would have received an emphatic “no” as your answer. Fast forward to the present day, and the average 10-year-old will respond with a “yes”.

Artificial intelligence (AI) enables machines to learn (a skill previously considered to differentiate the living from the non-living). These machines can learn based on the patterns provided by large datasets to plan, reason, communicate and learn.

 So, it is not surprising that AI is changing our economic landscape and, by extension, the landscape of the workplace. According to a PWC report, AI is already automating manual, repetitive tasks and could soon augment human decisions. The report further says that along the way, by 2030, it will add to global GDP more than the combined current output of China and India. This growth is expected to generate several good jobs and change the way jobs are now being done.

AI has extended its impact on how we recruit our workforce. As leaders, you will need to understand how AI will impact your workforce. You then need to transform your recruitment strategy to accommodate the potential impact of AI. For example, AI can automate much of your administrative processes, like billing, payroll and attendance tracking. Rather than recruiting for rule-based, routine tasks that require accuracy, you will start recruiting for creativity and complex problem solving. You will also see an increase in the use of AI to boost employee recruitment and retention.  

Let us take a closer look at possible avenues where you can leverage the power of AI to revolutionise your recruitment process.

Chatbots to improve candidate engagement

Chatbots can be made available 24/7. This ensures timely responses to all your candidate queries. Through natural language processing, chatbots can understand and respond to your candidate’s questions, guide them through the application process and schedule interviews at their convenience while maintaining consistent positive communication. This elevates the candidates’ experience. Consistent communication from application to onboarding fosters trust in your employer brand and increases your offer acceptance rate.

Improved onboarding experience

AI automates workflows, offering a seamless onboarding experience for your new hire. It personalises your new hire’s learning path while providing continuous feedback and support. Thus, the new hires feel welcomed and empowered, allowing you to harness their skills from day one.

Enhanced ability to determine suitability

The facial recognition technology embedded in your AI-empowered recruitment tool detects and classifies emotions displayed by candidates during video interviews. AI algorithms can also analyse candidates’ posture, body language and gestures during these interviews. AI provides insights into candidates’ emotional intelligence, communication skills and suitability for specific roles. This enhances the efficiency, fairness and effectiveness of the hiring process while ensuring a positive candidate experience.

Predictive analytics for talent acquisition

AI’s ability to learn from data patterns allows it to analyse historical recruitment data. It then identifies patterns and correlations to predict which candidates are most likely to succeed in specific roles. These insights enable recruiters to proactively source, engage and retain top talent, reducing time-to-fill and turnover rates.

The benefits of AI in recruitment are numerous. It increases efficiency while providing significant cost savings. It eliminates the hiring team’s bias and improves the overall candidate experience. But as with any other new technology, you need to keep in mind the challenges involved when harnessing AI to revolutionise your recruitment process. Make sure to maintain an optimal balance between AI-enabled automation and human decision making. There will, of course, be data privacy concerns. Ensure that the processes you set in place will alleviate these concerns. And last, but not least, do not forget that AI is prone to algorithmic bias. Your systems and processes should be built with this in mind.

As the world adapts to AI and its many faces, the next decade or more is going to be interesting. Let’s enjoy the ride!

References:

• elearningindustry.com
• pwc.com
• solulab.com