What capabilities should enterprises look for when selecting an AI service provider?

Can they understand real-world business operations? An enterprise AI service provider must first understand the specific industry, workflows, and organizational constraints. Providers that merely showcase the capabilities of general-purpose models often struggle to handle the complexities of internal enterprise requirements regarding permissions, data, approval processes, and compliance. Can they ensure successful engineering implementation? AI applications require stability, monitorability, maintainability, and auditability. A provider must go beyond simply invoking models; they need to manage data governance, API integration, access control, logging, and exception handling. Can they support long-term upgrades? Enterprise business needs evolve, and AI models and tools are constantly updated. Therefore, AI services should not be a one-time delivery but should encompass operational reviews, performance assessments, and continuous iteration. If you are evaluating AI service providers, consider validating their capabilities through a small-scale pilot project.