There's certainly plenty of room for improvement. Employee referrals, a process that tends to leave underrepresented groups out, still make up a bulk of companies' hires. Recruiters and hiring managers also bring their own biases to the process, studies have found, often choosing people with the "right-sounding" names and educational background.

Across the pipeline, companies lack racial and gender diversity, with the ranks of underrepresented people thinning at the highest levels of the corporate ladder. Fewer than 5 percent of chief executive officers at Fortune 500 companies are women - and there are only three black CEOs. Racial diversity among Fortune 500 boards is almost as dismal, as four of the five new appointees to boards in 2016 were white.

"Identifying high-potential candidates is very subjective," said Alan Todd, CEO of CorpU, a technology platform for leadership development. "People pick who they like based on unconscious biases."

AI advocates argue the technology can eliminate some of these biases. Instead of relying on people's feelings to make hiring decisions, companies such as Entelo and Stella IO use machine learning to detect the skills needed for certain jobs. The AI then matches candidates who have those skills with open positions. The companies claim not only to find better candidates, but also to pinpoint those who may have previously gone unrecognised in the traditional process.