Articles about recruitment

A new survey of 1,000 US HR and recruiting leaders shows teams are struggling to verify skills, assess culture fit, and find qualified candidates and that only 37 percent are prepared for an AI-driven future

The study from TestGorilla finds 58 percent struggle to verify skills on resumes, 47 percent find it difficult to identify candidates aligned with the company culture, and 43 percent cite a lack of skilled candidates in the market.

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Earlier this week we looked at the use of AI in recruiting and retaining staff. But that was from the business point of view. What about the other side of the coin, can you -- should you -- use AI when applying for a job?

The UK government clearly thinks so. New guidelines on the Civil Service Careers website say that tools like ChatGPT, Copilot and Gemini can be used to, “enhance your application and prepare for the process”. However it goes on to caution that AI shouldn’t be used to, “provide misleading or false information at any stage of the application journey.”

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Recruiting, training and retaining staff is very much a human issue rather than a technology one, right? Not necessarily, using data and insights from AI organizations can measure and improve employee performance as well as creating a more welcoming and inclusive work environment.

We spoke with Dr. Serena Huang, founder of Data with Serena and author of The Inclusion Equation: Leveraging Data & AI for Organizational Diversity and Well-Being, to learn more about how data can be used to drive meaningful progress in DEI and employee well being.

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A new report shows that more senior employees are bearing a heavy burden, with IT professionals who have more than 10 years of experience and the Baby Boomer generation experiencing the longest work weeks.

The study from Auvik also shows a generational disparity in the workload is rapidly exacerbating issues around burnout, since as many as 10,000 Baby Boomers will turn 65 and retire every single day between now and 2030, leaving even more work for remaining IT employees.

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Admit it, you have at some time or other exaggerated your skills when applying for a job. But a new survey finds that this is becoming much more of a problem since the advent of AI.

The survey by Capterra of 3,000 job seekers around the world shows that 58 percent say they are using AI tools as part of their job search.

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The cybersecurity workforce grew in 2023 to a record high of 5.5 million people, but the demand for skills is still outpacing growth.

A new guide from the UK's Chartered Institute of Information Security (CIISec) and ISC2 shows that globally, the cyber skills gap grew by 12.6 percent last year, with four million additional workers needed to fill the void, making recruitment more important than ever.

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According to a new report, 93 percent of security leaders say public gen AI is in use across their respective organizations, and 91 percent report using gen AI specifically for cybersecurity operations.

But the study of more than 1,600 security leaders, from Splunk and Enterprise Strategy Group, shows that despite this high adoption 34 percent of surveyed organizations say they don't have a gen AI policy in place, and 65 percent of respondents admit to not fully understanding the implications of the tech.

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Regulations surrounding the hiring of staff are complex, constantly changing and vary considerably between countries. Throw in increased levels of remote working and it becomes even more of a challenge.

To help employers work their way through these regulations, employment platform Oyster is launching an AI-powered chatbot specifically designed to answer questions about global hiring and remote work regulations.

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In the age of data, recruitment is undergoing a seismic shift. Predictive analytics is at the forefront of this revolution, supporting talent acquisition with data-driven insights while facilitating more precise decision-making than ever before. But what is predictive analytics and how exactly can it enhance your recruitment processes?

Predictive analytics (PA), simply put, uses historical data to forecast future outcomes. In recruitment, predictive analytics is like having a crystal ball that provides insights into hiring lead times, future employment needs, potential employee performance, and retention rates.

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