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The more the merrier. And when it comes to AI implementation, it always seems to be more and more and more.
68% of finance leaders said they were currently using AI or planned to do so, per a new Gartner study released this week. The study, conducted in May, found that 39% of the 133 respondents were already using AI or machine learning, while another 29 percent said they planned to.
But there’s a crucial caveat here. While “the most successful AI-forward finance organizations” already “embrace and evangelize AI at the C-suite level,” the greatest chance of success comes “when employees embrace AI as a coworker rather than a threat to their jobs,” Mark McDonald, senior director analyst for Gartner’s finance practice, said in a statement tied to the release.
And to that end, the report’s authors pointed to three key characteristics shared by finance orgs using AI successfully.
First, they understand the need for a long term strategy, and successful orgs acknowledge “transformative results” will take time, so short-term gains aren’t the priority, the authors noted. Next, finance leaders who build successful AI plans know that data scientists, far from being “risky and frivolous headcount” they were once considered, are instead a crucial component of a solid AI plan.
Finally, organizations “with a high level of AI acceptance report a high level of success,” the authors said. “Without the buy-in from knowledgeable process owners, building AI-driven processes that emulate their decisions and actions proves difficult,” they continued.
That’s especially important in light of the AI perception gap: Many employees don’t realize how prevalent AI already is in their orgs, leading to disconnect and sometimes a breach of trust, Hugo Sarrazin, chief product and technology officer at UKG, a workforce management company, previously told CFO Brew. With that in mind, it’s no shocker that orgs with employee buy-in for AI naturally have a leg up.
“These three quite simple factors have an impact on success rates with AI in the finance functions,” McDonald added. “Put the data scientists close to the processes and people that will train AI, make sure those people understand that AI can make their jobs easier and give them the time needed to produce transformative results.”
It’s an easy enough recipe—and finance leaders seem to be following it.