How to Make Enterprise Gen AI Work

It’s time for organizations to shift from ad hoc employee experimentation with generative AI to honed, measurable, enterprise-aligned efforts such as enterprise knowledge assistants and customer service chatbots. These tools translate generative AI’s open-ended capabilities into applications that address specific, known use cases and include access to more data, standardization across the organization, lower risk because of more oversight, and, in theory, greater ROI because the efforts are targeted and measurable. But the same qualities that make enterprise gen AI systems more beneficial make them difficult to build; integrating high-quality data across complex systems, orchestrating data flows, and aligning outputs with business are huge challenges. By focusing on how business teams can prepare their data and work flows and how business teams and development teams collaborate, companies can address many of these issues—and prepare themselves as they look ahead to agentic AI.