... Agentic automation utilizes LLM-based AI agents to automate business processes by learning from interactions and making semiautonomous and autonomous decisions. To avoid the hype around everything agentic, applications leaders should identify high-value use cases where AI agents would be justified. ...
Analyst(s): Tad Travis | Frances Karamouzis | Tom Coshow | Saikat Ray
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... GenAI-enabled products still mostly function as assistants, powered by general LLMs, but enterprise clients want AI embedded where the work happens. Tech CEOs can achieve defensible differentiation by building workflow-native AI products, powered by domain-specific models and proprietary data. Overview ...
... controls that need to be implemented at each phase of the life cycle of (1) traditional machine learning, (ML) models, (2) RAG frameworks, (3) fine-tuning LLMs, and (4) agents. When to Use Directions for Use Gartner Recommended Reading Gartner Research ...
... AI, particularly LLM-based GenAI, is transforming both internet search and site search, as well as navigation. Digital commerce leaders must grasp the evolving landscape of search and product discovery and its impact on customer expectations, or risk losing customers to superior experiences. More Detail ...
... retrieval-augmented generation often run into a critical readiness gap. Existing pipelines may not deliver fresh, context-rich enterprise data into their LLM. These insights show data engineers how to rethink ingestion, structure, quality and metadata for RAG-ready data pipelines. Overview Analysis Guidance ...
... Large language models (LLMs) act as a tax on software vendors that robs them of their control over expenses. Chief product officers must master the economics of AI to deliver profitability and sustain the future of their companies and products. Overview Strategic Planning Assumption Analysis Gartner ...
... specific industries, disrupting the enterprise software market in the AI race. CIOs and innovation leaders must understand DSLMs to address generic LLM limitations and decide on their adoption in specialized situations. How to Use This Presentation Gartner Recommended Reading Gartner Research ...
Analyst(s): Dave Aron | Tsuneo Fujiwara | George Brocklehurst
... Context engineering is central to application architects building robust AI applications, regardless of the underlying LLM technology. Strategically managing context for each step of an agentic workflow can help ensure that AI agents are accurate, efficient, and capable of handling complex, real-world ...