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Appier Research Unveils Agentic Ai Breakthrough: a Risk-Aware Decision Framework
Appier's framework quantifies large language model reliability in high-risk enterprise AI, addressing hallucinations and decision accuracy to boost autonomous AI adoption.
- On March 11, 2026, Appier announced in Singapore a research introducing a Risk-Aware Decision-Making framework, integrating findings into its Cloud platforms to improve AI reliability, according to Appier.
- According to a 2025 McKinsey survey, 62% of organizations are experimenting with AI agents while inaccuracy remains the top risk as enterprises move from AI copilots toward autonomous AI agents.
- Skill Decomposition splits decision-making into three steps and the Risk-Aware Decision-Making framework defines structured risk parameters to convert large language models' choices into expected reward metrics.
- The research finds a strategic imbalance in many leading LLMs, over-guessing in high-risk settings and refusing too often in low-risk scenarios, which limits enterprise AI autonomy and safety.
- Appier will continue leveraging its AI research team, proprietary data assets, and industry expertise to advance Agentic AI innovation and translate findings into enterprise-ready methodologies and product capabilities.
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26 Articles
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Quantifying LLM Reliability Across Risk Scenarios for Trustworthy Enterprise AI
Appier unveils risk-aware decision framework for agentic AI
SINGAPORE, March 11, 2026 /PRNewswire/ -- Appier today announced new research advancing the reliability of Agentic AI systems. To expand the impact of its research and development efforts, Appier's AI research team continues to focus on frontier topics in Agentic AI and Large Language Models (LLMs), exploring forward-looking technical challenges that push the boundaries of marketing technology innovation. In its latest paper, "Answer, Refuse, or…
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Total News Sources26
Leaning Left5Leaning Right3Center7Last UpdatedBias Distribution47% Center
Bias Distribution
- 47% of the sources are Center
47% Center
L 33%
C 47%
R 20%
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