By turning artificial intelligence from theory into measurable business value, pragmatic enterprise AI adoption focuses on structured, results-driven integration rather than chasing flashy projects.

Using a sensible enterprise AI adoption approach converts AI from buzzword to strategic driver of measurable business outcomes — and Cohere Inc. is leading the way. This entails going the extra mile to deliver real return on investment, according to Autumn Moulder (pictured), vice president of engineering at Cohere.

Cohere’s Autumn Moulder talks about enterprise AI adoption.

“We’ve really evolved and said, ‘What does an enterprise need to adopt this fundamentally transformational technology?’” Moulder asked. “We’ve evolved from, we build the foundation model to let’s bring in some applications, the North products that we’ve recently developed, to make it easier to adopt AI within the enterprise, to partnering with these companies to say, ‘Hey, we can help you build a custom model. We can help you build a custom agent.’”

Moulder spoke with theCUBE’s John Furrier at theCUBE + NYSE Wired: AI Factories – Data Centers of the Future event, during an exclusive broadcast on theCUBE, SiliconANGLE Media’s livestreaming studio. They discussed the critical role of pragmatic enterprise AI adoption, noting innovations developed by Cohere.

Why strategic partnerships are key to successful enterprise AI adoption

Partnerships are key to enterprise AI adoption. Scaling AI isn’t just about software — it requires aligning technology, talent, data, processes and strategy. With deep expertise in machine learning, NLP, data engineering and AI governance, Cohere is already leading the way, according to Moulder. 

“We very much have focused on that enterprise segment,” she explained. “We see this as a place where we can drive a lot of value and really help people navigate this transition. There’s a recent MIT study that came out about how enterprise partnerships, where you partner with an external entity versus rolling it yourself, [has] like twice the success rate when you’re looking to adopt AI. We’ve really taken that to heart coming from our foundations of building models.”

Pragmatic enterprise AI adoption goes beyond installing software — it demands the right blend of capabilities to tackle real business challenges. Large language models offer adaptability and conversational intelligence, while specialized models deliver precision and domain expertise. Together, they enable versatile, operationally effective AI solutions — something Cohere is uniquely positioned to deliver, Moulder pointed out.

“We focus very much on efficiency, which ties it to this idea of large language models, small language models, what’s the right size model and making sure that we can deliver the point solution whether it’s a small language model for a highly efficient work flow,” she said. “We bring both of those to the table. We see this as an efficiency story and we also see it as a privacy story making sure you can hit both of those pieces.”

Here’s the complete video interview, part of SiliconANGLE’s and theCUBE’s coverage of theCUBE + NYSE Wired: AI Factories – Data Centers of the Future event:

Photo: SiliconANGLE