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Premium Research Aug 2025
... Domain-specific language models are displacing LLMs to deliver relevant solutions that provide tangible business value across many business areas and industries. Product leaders should adopt DSLMs to help clients achieve more benefits from GenAI and to develop domain-specific AI agents to address clients ...

Analyst(s):   Annette Zimmermann   |   Samantha Searle   |   Kanishka Chauhan   |   Alizeh Khare   |   Roberta Cozza   |   Esha Bhatia
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Research Jun 2025
... Access Research Already a Gartner client? An eval-driven development (EDD) approach builds quality into LLM-based applications by surfacing risks of nondeterministic behavior. Software engineering leaders should explore the benefits of EDD to minimize undesirable outputs and hallucinations in GenAI applications ...

Analyst(s):   Manjunath Bhat
Premium Research Oct 2025
... IT systems rely on third-party components and data, from software built on open-source code to LLMs trained on vast public datasets. Proper attribution is essential to maintaining and securing such systems. CIOs can use new tools to validate the digital provenance of code, data, processes and media. ...

Analyst(s):   Arun Chandrasekaran   |   Bart Willemsen   |   Paul Delory   |   Gene Alvarez
Premium Research August 13 2026
... triggers a retry threshold or hits an edge-case reasoning block. Add DeepSeek-V4 to the enterprise open-weight LLM evaluation portfolio. Prioritize non-mission-critical use cases, such as LLM-as-a-judge, synthetic data generation and internal knowledge analysis, to validate performance, cost and governance ...
Announcement March 30 2026
... and transparency in algorithmic decision making. LLM observability solutions monitor, analyze and provide actionable insights into the behavior and performance of LLMs. They go beyond standard IT measurements, such as response times to look at specific LLM metrics such as hallucinations, bias and token ...
Research Apr 2026
... Access Insights Already a Gartner client? 数据智能体正在从概念阶段快速走向落地部署,成为中国数据与分析(D&A)实践中的最高优先事项。通过利用知识与基于大语言模型(LLM)的推理,数据智能体可以自动化复杂的D&A工作流,以面向任务的自主服务替代部分传统工作。D&A领导者必须探索这一趋势,明确适用范围并学习新技能,为未来的采用做好准备。 概述 战略规划假设 导语 详细描述 优势和作用 风险 建议 代表性供应商 证据 Gartner相关推荐阅读 注1:中国的数据智能体用例示例 Gartner Insights Abstract ...

Analyst(s):   Mike Fang   |   Fay Fei   |   Julian Sun   |   Xingyu Gu
Premium Research Jul 2025
... Despite the rapid advancements and widespread excitement surrounding LLM-based AI agents, many AI agent solutions lack the robustness and maturity needed for effective enterprise use. Leaders and executives responsible for AI should review enterprises’ AI agent readiness gaps and act according to recommendations ...

Analyst(s):   Tong Zhang   |   Leinar Ramos   |   Mike Fang   |   Ben Yan   |   Gary Olliffe
Webinar On-Demand
... why it matters and how to future-proof your team and strategy to maintain influence, trust and measurable impact. •Discover how AI-powered search and LLMs will transform PR and earned media — and the strategies you need now •Learn why narrative intelligence is essential for real-time reputation monitoring ...

Analyst(s):   Patryck Allen   |   Amber Gallihar Boyes   |   Michelyne Chavez   |   Emily Earl   |   Iliyana Hadjistoyanova
Premium Research Jun 2025
... DSLMs are outperforming general-purpose LLMs, demonstrating productionized and scalable value. Chief product officers and product leaders must invest in LMOps pipelines that enable parameter-efficient fine-tuning and DataOps that can scale access to new and diverse sources of data. Overview Strategic ...

Analyst(s):   Tsuneo Fujiwara   |   George Brocklehurst
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