Many current predictions assume that enterprise employees will interact with all systems through a single conversational AI interface. However, operational reality shows that this "one-size-fits-all" model does not reflect the complex needs of different departments. Each department, from finance and data analytics to customer service, operates under entirely different constraints and objectives.
Diễn biến chi tiết
According to VentureBeat, the history of cloud migration shows that organizations rarely adopt a new technology uniformly across the entire system. Instead, each department modernizes on its own timeline based on practical work priorities. The current adoption of artificial intelligence (AI) is following a similar trajectory as businesses evaluate new technology through the lens of existing processes. Many organizations realize that the value of AI sometimes lies in under-the-hood process improvements rather than a flashy chat interface.
Phân tích kỹ thuật & Công nghệ
In terms of technology, two approaches to enterprise AI are coexisting. The first is embedded AI, integrated directly into existing workflows to automate repetitive tasks where users barely notice a new interface. The second is connecting operational data to external Large Language Models (LLMs) through services like NetSuite AI Connector Service or the Model Context Protocol (MCP). Supporting the MCP protocol allows enterprises to securely query confidential data, creating virtual assistants capable of conversing directly on top of internal databases.
Ý kiến chuyên gia & Nhận định
Sloan Session, CFO at Dura Software, shared how humans and machines collaborate: "The agents handle the pull. The humans handle the judgment and the personal touch." Meanwhile, Berry Carter, CEO of S&B Filters, emphasized the importance of data governance, warning that if a user cannot access specific information within the core system, they must not gain access to that same information through an AI assistant.
Tác động & Tương lai
This shift reshapes how Vietnamese and global enterprises approach digital transformation with AI. Instead of trying to build a single AI portal, tech leaders need to identify clear business objectives and specific workflows to apply the right solutions. The future of enterprise AI will be a flexible mix of hidden automation tasks and intuitive conversational tools, where data governance and permission security play a decisive role in success.