Enterprise AI8 min read
Enterprise AI Adoption: From Pilot to Production
Most enterprise AI projects fail not in the pilot phase — but in the transition from pilot to production. Here's what actually happens and how to navigate it.
Read →When to deploy voice agents, when to deploy chat agents, and when you need both
Most enterprise AI discussions focus on the model, the data, and the architecture — but the interface through which users interact with the AI has an outsized impact on adoption and effectiveness. A voice agent in a context where users need to reference documents will fail. A chatbot for users who are driving or working with their hands will fail. The interface decision should be driven by the user context, not the technology.
Voice AI is the superior interface in several specific enterprise contexts:
Conversational chat agents excel in different scenarios:
For many enterprise use cases, the best answer is both. Our deployments increasingly use a handoff architecture: AIKA (voice) handles the initial contact and qualification, then seamlessly transfers the conversation to AIWA (chat) for document-heavy follow-up. The conversation context carries across the channel switch, so the user never has to repeat themselves. This hybrid approach captures the strengths of both interfaces.
See the production AI systems behind these insights.