AI Ready… or Not?

Automate workflows. Improve productivity. Enhance relationships. The CHRO knew what she wanted out of artificial intelligence. The problem was figuring out which tool worked best for her company’s needs.

According to the most recent data, the number of US startups focused on AI is astounding: 15,000 and counting. Globally, it’s even higher, with each new company implementing specific services that they know full well their competitors are either considering—or already using. As firms move from strategy to implementation, experts say, some have already wasted millions of dollars on the wrong technology and human-resources tools.

“History shows us that picking applications misaligned with what the firm is trying to accomplish can cost a lot,” says Chris Cantarella, a Korn Ferry senior client leader and global sector leader in its Software practice, pointing to the miscues some companies made around cloud-based applications and software during the early stages of digital transformation as examples.

In all, companies are expected to pump nearly $100 billion into AI this year, with that figure projected to grow to $2 trillion by 2030. Experts say CIOs and CTOs are being pressured by their CEOs and boards to make quick decisions they can take back to analysts and investors.

This “shoot first, aim later” approach has created issues. Already, some companies have had proprietary data and other information inadvertently made public after uploading it to an AI platform, for instance. Others have been sued over data privacy, copyright infringement, or bias. Many more have been embarrassed for failing to double-check incorrect information or called out because of ethical concerns around job loss and social impact.

Selecting the right tools depends on the company’s strategy, says Paul Fogel, professional search sector leader for software at Korn Ferry. “Do you just want to take advantage of the efficiencies automation provides, or do you want to be an AI-led organization?” he asks. To be sure, Fogel says, when leaders talk about AI, they use it as a catchall phrase when they should really be distinguishing between the different types and tools.

Some smart firms are implementing a strong AI-governance framework to help guide leaders in deciding on the best strategies and investments. Others are focusing on identifying and developing AI-leadership talent, says Jamen Graves, global co-leader in the CEO & Enterprise Leadership Development practice at Korn Ferry. In a recent survey, 40% of C-suite leaders said their workforces have insufficient AI-related knowledge or skills. As companies seek a rare combination of market vision and technical know-how, Graves says, “there is a race for talent with leadership potential.”

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