iTea Time with Tarun

Early AI deployments often look convincing in controlled settings. The real test begins when systems move into live workflows, where data shifts, exceptions multiply, and accountability becomes unclear.In this episode of AI for the Enterprise, we examine what it actually takes to run AI in production. From hidden workflows and process drift to governance controls, retraining discipline, and user adoption, this conversation moves beyond experimentation into operational reality.If your organisation is moving past pilot projects, this discussion will help you assess whether your surrounding processes are ready to support AI at scale.Featured Enterprise AI Practitioner:Johnson GohFounder, MindhiveJohnson builds AI systems that help fast-growing companies drive revenue growth and cost efficiency. His work focuses on moving beyond prototypes into production-grade systems that must perform reliably inside real business operations.At Mindhive, he works with organisations ranging from SMBs to enterprise clients, developing AI-driven workflow automation, including B2B order processing and operational orchestration, designed to handle exceptions, maintain reliability, and support long-term adoption.For organisations serious about operational AI, this episode offers a grounded look at what holds up once AI leaves the lab and enters daily work.