The AI Match Game

The firm’s general counsel was under pressure from the CFO to demonstrate how the legal function was using AI. He knew experimentation with ChatGPT wasn’t going to cut it, so he started hunting. But for what? There are literally hundreds of AI tools on the market for the legal profession, from litigation-analysis platforms to case-management and document-drafting applications to everything in between. It all seemed so daunting. And using the wrong one could hurt the firm’s bottom line.

With so many AI tools out there, and their slight differences in functionality and design, it’s hard for people to figure out which is the right one. Think about all the decisions that go into ordering coffee nowadays, and multiply that by a hundred, and you get the idea. But from a corporate perspective, deploying the wrong AI tool can put the company far behind competitors, or hurt the bottom line by limiting the potential efficiencies of the right tool. And then there is this: Even if companies find the right tools, how can they be sure their workers are using them?

For now, Jamen Graves, global leader of CEO and enterprise leadership development at Korn Ferry, says the major challenge for leaders is to connect AI platforms and tools across the organization. “The wide range of AI tools out there don’t speak to one another,” says Graves, “but are designed to support a particular function.”

To be sure, picking the wrong tools is already costing firms tens of millions of dollars: Only 21% of AI projects scale to a level that generates meaningful return on investment. And it’s only going to get more challenging for leaders. Data shows AI startups are on track to receive more than half of all venture-capital funding this year, with the $1.93 billion invested to date supporting, among others, enterprise-level large language models and platforms for work integration, specific applications for industries like healthcare and manufacturing, and practical tools for marketing, finance, and other functions. “Every AI tool comes with costs, security implications, and ROI expectations,” says Dexter Winters, an associate in the AI Strategy and Transformation practice at Korn Ferry.

Winters says matching the right AI tools to the right people and functions requires leaders to “have a hands-on understanding, education, and a bit of imagination to connect the dots between what’s possible and what’s valuable.” Whereas past technological advances were essentially plug and play, Winters says, the new tools require leaders to decide whether to centralize around one generative platform or allow different parts of the business to choose tools that fit their needs. “Both routes come with trade-offs,” he says.

But even if the firm does figure out which tools to use, it may face a more difficult challenge: making sure employees are turning to these tools too. Adoption and training are two of the biggest obstacles to AI transformation. Roughly 80% of employees still don’t use AI for work tasks, and only one-quarter report taking company-sponsored training. Winters says leaders need to ensure there is alignment between the people who select the tools and those accountable for creating business value. Jerry Collier, leader of assessment and succession for Europe, the Middle East, and Asia at Korn Ferry, agrees. “It’s about creating a clear process for moving from hundreds of experiments to enterprise value,” he says.

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