Hilke Schellmann, author of "The Algorithm," argues that AI-based tools aren't ready for use in the hiring process. Yet, many large American companies already rely upon them.

Chicago-based A.I. platform VMock operates in two ways: It's both a recruiting platform and an upskilling platform. Its recruiting system is mostly focused on college students and entry-level workers: Candidates upload résumés to the platform and receive, through A.I. analysis, feedback on their résumés and LinkedIn profiles, as well as targeted job recommendations. Its upskilling platform is currently in use at more than 250 higher education institutions, and by Q2 of 2022 will be made available to companies to help train and potentially transfer existing employees. In the latter program, the process is similar: The A.I. platform analyzes résumés to get a better sense of the skills employees already have, and what areas they might be able to better develop.

The use of artificial intelligence has increased productivity and efficiency in the workplace in nearly every industry. As such, a number of companies have turned to AI to improve their recruiting process--a task that once required hours of sorting through resumes, calling applicants and scheduling interviews to find the perfect candidate. Despite these advancements, not all companies are aware of the massive benefits that a more automated recruiting process can offer. Below, a panel of Forbes Coaches Council members share ways AI can improve recruiting and the overall hiring process. Forbes Coaches Council members share key ways AI can improve the recruiting process. AI can make recruiting a seamless, smooth action.

With a focus on building scalable capabilities for generating, operationalising, and measuring data-driven insights for their clients, ZS has a strong advanced data science group within their Business Consulting function. The team focuses on integrating transformative AI-enabled solutions and data products across multiple industries such as healthcare, life sciences, telecommunication, high tech, and retail. As the company leverages deep industry expertise and leading-edge analytics to create solutions that work in real life, the data science team plays a vital role in driving these functions. From foundational research in deep learning, natural language processing (NLP), optimisation, and operational research -- the advanced data science team at ZS works across various solutions. They are involved in developing solutions to full-scale productisation.

With a surge in AI and ML applications to improve business process efficiencies, there has been an increase in data science hiring across companies. It is one of the fastest-growing areas and often requires a robust hiring process to get the best candidates in the team. We got in touch with Sreekant Menon, VP, Data Science at Genpact to understand their data science hiring process. Menon shares that not only their hiring mechanism looks for the best available candidate but also retains them by providing opportunities to improve their skills over time. Menon shared that with years of experience in leveraging data analytics for solving challenges across industries and functions, Genpact has identified the most vital and useful attributes that a potential data scientist needs to have.

Let us paint you a picture. Eric owns a house with a garden he doesn't know the first thing about keeping. What he does know a lot about, though, is how he wants everything to look; the right length of grass on the lawn, the color composition in the flower bed. He just doesn't know how to get there. For the past five years, Bob has been working as Eric's gardener. He understands exactly what Eric needs and wants, he's never late, he comes with thoughtful suggestions, and Eric gets along with him well.

Some of the largest employers in the world are increasingly, and in some cases controversially, relying on AI-based technologies to hire new workers. Companies like Tesla, Accenture and LinkedIn are using technology from Pymetrics to better vet qualified candidates and reduce the time and resources required for what has traditionally been a labor-intensive hiring process. The company, which boasts more than 80 global clients, uses a blend of data science and I/O psychology to create its "people recommendation engine." The Pymetrics platform is designed to improve employee retention while also increasing efficiency and diversity throughout the recruiting process. The results are parsed by AI to generate measurements related to candidates' problem-solving skills, ability to multitask and even their levels of altruism.

As artificial intelligence evolves, we're going to increasingly rely on it for boosting the hiring process. In Life 3.0: Being Human in the Age of Artificial Intelligence, author Max Tegmark asserts that the "rise of AI has the potential to transform our future more than any other technology." So it is, as we already see in hiring. A recent study found that 46 percent of companies struggle with finding and attracting the right candidates for their open positions. AI programs can search online resumes and social profiles to find the best candidates for each job based on specific traits.

Because AI learns from the data sets that it is given, there is always a risk of bias setting in. Bias in these data sets is likely to perpetuate the lack of diversity in global workplaces. In this article, we turn the spotlight on the issue of AI bias in HR, with exclusive insights shared by experts from ADP, AVTAR Group, Plum, Job.com, and HireVue. Your HCM System controls the trinity of talent acquisition, management and optimization - and ultimately, multiple mission-critical performance outcomes. Alongside the rise of artificial intelligence (AI) in different sectors, questions around the possibility of bias have also increased.

The hiring process is an important, but time-consuming, process. It can be exhausting to sort through applications to determine which candidates have the necessary qualifications for your job opening. One time-saving technology recruiters and hiring managers are using is artificial intelligence (AI), which can be especially useful when sorting through a large number of applications. However, there are also some potential downsides to consider when using AI. We asked 10 Forbes Coaches Council members what issues AI raises with increased use in the hiring process, and how you can best work around those challenges.