The AI Revolution Is Meeting Reality

A week with Amazon’s AI team & its partners revealed plenty of enduring optimism, but also a recognition that building effective generative applications takes work.

Nearly two years after ChatGPT’s debut, AI hype is giving way to reality. Companies are eager to build with generative AI, but they’re learning that doing so is hard. They’ve found that AI models are expensive, data conundrums abound, and change management isn’t so simple. To that end, only 21% of companies surveyed by Gartner earlier this year had GenAI in production, with the rest either “piloting” or “exploring” the technology, per data viewed by Big Technology.

Still, there’s almost unprecedented optimism around the tech. Every company with a pulse is examining how to integrate GenAI into their internal operations and external product. They’ve spent billions with Big Tech companies and consultancy firms as they race to figure it out. And they believe all this experimentation will eventually pay off. It better, because the economic future of the current AI wave depends on it. 

I spent a good chunk of the week discussing these ground-level realities with Amazon’s AI team and its partners and walked away with what might’ve been my best picture yet of what’s happening. I was struck by the measured tone of nearly everyone I spoke with. “It's going to feel a lot more incremental than we're probably used to,” Matt Wood, Amazon Web Services’ VP of AI products, told me, while insisting it will add up over time. And I learned about a few surprising products that expanded my view of the cutting edge. Here’s a breakdown of the core obstacles, and what surprised me on the product side: