Yet, difficulty successfully deploying generative AI continues to hamper progress. Corporations know that generative AI could transform their businesses—and that failing to adopt will leave them behind—but they’re faced with hurdles during implementation. This leaves two-thirds of business leaders dissatisfied with progress on their AI deployments. And while, in Q3 2023, 79% of firms said they planned to deploy generative AI projects in the following 12 months, only 5% reported having use cases in production in May 2024.
“We’re just firstly of determining find out how to productize AI deployment and make it cost effective,” says Rowan Trollope, CEO of Redis, a maker of real-time data platforms and AI accelerators. “The fee and complexity of implementing these systems just isn’t straightforward.”
Estimates of the eventual GDP impact of generative AI range from slightly below $1 trillion to a staggering $4.4 trillion annually, with projected productivity impacts comparable to those of the Web, robotic automation, and the steam engine. Yet, while the promise of accelerated revenue growth and value reductions stays, the trail to get to those goals is complex and infrequently costly. Corporations need to search out ways to efficiently construct and deploy AI projects with well-understood components at scale, says Trollope.
