What I like best about OpenAI, as someone building internal AI agents, is how quickly we can go from a concept to something real that people can use. The APIs are straightforward, the documentation is good enough to get up and running fast, and there’s a wide range of models and features to choose from. That combination of ease of integration and depth of capabilities lets us experiment, iterate, and then standardize on the patterns that work across the business. Once things are in place, our teams end up using these AI-powered workflows constantly because they’re embedded right into the tools they already work in. Review collected by and hosted on G2.com.

From an enterprise admin perspective, the main friction points are around control and operational overhead. The core APIs are easy to integrate, but getting to a fully production-ready setup, prompt design, evaluation, monitoring, governance, and cost management takes real effort. The feature set is rich, but that also means there’s a learning curve to choosing the right models and configurations for each use case. Support and guidance have improved, but I’d still like more opinionated best practices and examples geared specifically toward larger teams rolling out multiple agents across the organization. Review collected by and hosted on G2.com.