We are entering a new phase of artificial intelligence—one defined not by generating content, but by taking action. Agentic AI represents the next frontier: systems that can operate on our behalf, orchestrate multiple tools, and make decisions in context. The potential is enormous, but as Seth Earley explains in his latest article for CustomerThink, most organizations are not ready for this level of intelligence.
The problem is not the technology. It is the lack of structure, understanding, and context that underpins it. Large language models alone cannot deliver a competitive advantage because they do not know your business, your products, or yourcustomers. Real results come from clean, structured, and well-governed data—supported by Retrieval-Augmented Generation (RAG), curated knowledge sources, and thoughtful orchestration across multiple systems and models.
Seth explores why 40% of agentic AI projects will fail by 2027, how to avoid the common traps of over-automation, and what it truly means to embed context into intelligent systems. He argues that agentic AI must begin with human understanding: mapping processes, defining decisions, and aligning automation with real business value.
For organizations eager to lead in this new phase of AI, the message is clear: you cannot automate what you do not understand. Success depends on strong information architecture, disciplined governance, and the right balance between autonomy and human oversight.
Read the full article on CustomerThink to explore the foundational work required to make agentic AI successful—and sustainable.
🔗 [Read the article on Customer Think]