A 2024 Workable survey of over 3,000 professionals revealed that ‘nearly two-thirds of participants reported using AI in hiring over the past year.’ As companies recognize its benefits for speeding up hiring processes and cutting costs, the adoption of the novel technology is expected to grow rapidly. However, concerns persist among candidates and hiring managers surrounding the issues of bias, data privacy, and compliance with regulations. Speculating on the exact influence of AI on future hiring practices and whether these concerns will be resolved is difficult to predict. However, we can clearly observe how AI is being used today. Let's explore how AI is currently shaping hiring practices in these four pivotal sectors.
1. Healthcare
Healthcare facilities are grappling with the challenge of aligning staffing levels with fluctuations in patient volume. Patient numbers can fluctuate unexpectedly, resulting in either overworked staff during busy periods or underutilized staff during slower times. Fluctuations in patient volumes can be the result of seasonal illnesses such as the flu, public health events like foodborne illnesses, and environmental incidents such as heat waves – among other things.
Fortunately, AI is now being relied upon to optimize staffing levels by using data to anticipate patient fluctuations with greater accuracy. These advanced models use historical data, patient admission rates, and seasonal trends to improve decision-making around staffing allocations. As a result, healthcare organizations can avoid overstaffing, which leads to increased costs, and understaffing, which leads to worker burnout and lower patient care quality.
2. Retail
Retail businesses today are struggling to adequately staff. In fact, a recent WorkJam study found that ‘46% of retailers report being frequently or sometimes understaffed.’ The most cited impact of insufficient staffing levels is a reduced customer experience, which can damage a company’s brand reputation and negatively affect sales. Adding to the challenge, peak shopping seasons - like Black Friday - place an even greater burden on an already overworked workforce.
Thankfully, AI is being used to forecast peak shopping times and therefore ensure optimal staff levels. By leveraging past sales data, foot traffic and location analytics, demographic insights, and upcoming calendar events, these advanced models can accurately forecast when and where customer activity peaks. Allowing retailers to staff accordingly during high-demand periods and prevent worker burnout.
3. Technology
Technical assessments have long been standard in the tech sector, helping hiring managers evaluate a candidate’s skills. Recently, there has been a growing trend in using AI to make these assessments more interactive and engaging. AI-powered tools can now gamify tasks like coding assessments and simulations, turning them into game-like challenges. Here’s an example of how it works.
Candidates are asked to build a simulated city using programming concepts. They start with basic structures like roads and buildings and progress through levels where they add more complex features such as traffic management algorithms or environmental sensors. AI tracks their coding decisions, evaluating efficiency and accuracy in real-time. Points are awarded for completing tasks and optimizing code, while instant feedback guides candidates on best practices. It’s a win-win for both parties, as candidates can showcase their technical skills in a video game-like environment, while hiring managers assess their abilities in real-world scenarios.
4. Finance
In the finance sector, there's a growing trend towards using stock market simulators to assess the technical abilities of candidates. These AI simulators mimic real-world trading environments, allowing candidates to practice making investment decisions without the risk of actual financial losses. By using these simulations, hiring managers can evaluate how candidates analyze market trends, execute trades, and manage portfolios under different scenarios.
For example, a candidate applying for a financial analyst position might participate in a stock market simulator exercise during their interview process. They would be given a virtual budget and access to real-time market data. The candidate's assignment would be to build and manage a portfolio by making, buying, and selling decisions based on market trends and economic news. Throughout the simulation, AI would track their decisions and performance metrics, such as portfolio returns and risk management strategies. This allows hiring managers to gauge the candidate's ability to interpret financial data, make informed investment choices, and adapt their strategies in response to market fluctuations.
Final Thoughts
AI adoption in hiring is expected to spread beyond just these four sectors. However, these sectors are pioneers, leading the way in integrating advanced technology into their hiring lifecycle. As data volume grows across all sectors, using the technology to find and support the right hires will become more common.
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