As AI (artificial intelligence) integration in the recruitment process becomes more extensive, value for both organisations and hiring teams is growing stronger. Ethos BeathChapman (EBC), one of Will’s hero brands with a global presence in executive recruitment solutions, is seeing impactful results with this type of technology investment. For EBC, the possibility that recruitment as an industry is well on its way through an AI-driven transformation is becoming a reality. We’ve interviewed EBC Asia’s Director, Hamza Mush, to get more insights as to why AI is considered an accelerator for winning the war for talent.
AI’s greatest attribute for recruitment is its power to process and assess data in high volumes at high speed with minimal error. Sourcing for both active and passive candidates is one of the most time-consuming tasks in recruitment. However, with AI, recruiters can improve their speed when finding top talent without sacrificing quality. For Hamza, it is essential to establish objectives before incorporating AI into the sourcing process. “It’s important not to lose sight of your primary objective when it comes to integrating AI or ML (machine learning) in your sourcing methodology – for us, that is to surface best-fit candidates for our clients and stakeholders as quickly and effectively as possible,” Hamza says. EBC’s ability and capacity to “find and engage the right people with the right skill sets across multiple channels has, in certain cases, increased ten-fold with AI” stated Hamza
AI’s machine learning attribute is enabling the technology itself, in a way, to be more human. Through ML, technology tools develop their systems to mimic and predict human behaviours through statistical models, data patterns and algorithms. But, unfortunately, AI can also learn human biases if not updated properly and responsibly. For example, in 2018, Amazon scrapped its own AI-recruitment tool because of a big issue – the engine operated with unconscious bias against women.
Morally distinguishing right from wrong is one trait AI can’t conceive and achieve on its own. “It is difficult to determine if any AI-model or algorithm is entirely bias-neutral” says Hamza. However, he pointed out that without “hardwired preconceptions,” AI can provide distinct advantages in “eliminating unconscious bias, particularly in the early stages of a selection process.”
Recruiters and hiring managers are responsible for making sure AI is fair when finding and assessing talents on its own. They can accomplish this through the power of data. “AI needs data to work. The right type, volume and quality of data. Hence reviewing our data strategy in relation to each AI use case has been a critical element of our transformation journey,” Hamza shares. Tech tools’ ability to learn human patterns is governed by data, and data can be governed by humans. With this, humans can program and train AI to be unbiased and at the same time analytical and objective during the recruitment process.
AI is present not only in sourcing candidates, these days you can find AI footprints in different recruitment and HR functions.
Some organisations use AI throughout their interview process to better understand candidates and make better hiring decisions. AI records interview sessions and then determines common answers and questions to identify critical challenges professionals face in specific roles or sectors. However, AI lacks that ‘gut instinct’ that can often be a deciding factor among recruiters when interviewing and hiring people.
Learning and development (L&D) is integral in today’s business landscape, with both jobs and skills evolving. The use of AI to improve L&D programs will increase significantly in the coming years. Organisations run agile learning models to provide more targeted programs to support individual learning instead of general-based solutions. AI can help L&D systems design specific programs for employees with different skill sets and years of experience. In addition, key information can be identified during the recruitment process. Recruiters can help candidates better align their careers and then identify avenues for growth and learning for them.
AI can’t predict cultural fit. That is why recruiters must understand candidates on a deeper level to determine if they are a good fit, not just for the role but also for the team and the organisation.
During the hiring stage, recruiters primarily focus on individuals and how they would fit in the job role. Through data analytics and machine learning, recruiters can identify individual characteristics, strengths and key motivators. They can then evaluate how those factors help the individual better collaborate, cooperate and perform within a team. Candidate data can be combined under the right preferences and conditions to generate team data for recruitment, onboarding, team development, skills development and even succession planning.
Other than sourcing and the functions listed above, applications of AI or ML show the possibility to assess for soft skills assessment, programmatic job advertising, database management, chatbots and more, according to Hamza. However, Hamza and the entire EBC team need to keep in mind that AI is not perfect. Hamza learned that when integrating AI in the recruitment process, professionals should embrace the reality that the technology is still “under heavy development” and that there will always be resistance to innovation and change. “Having a clearly thought-out implementation, training and review is paramount,” he says.
“People are wary of new technologies, systems and processes that challenge their existing habits and ways of working. With that, change management and people management has played an integral role when integrating AI,” Hamza states.
In the first ever article I’ve written for Will, I wrote that technology in this journey to organisational transformation is the enabler and humans should always be at the centre and the ones to lead. This rings true to this very day.
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