Published on August 25th, 2026 | By: Michal Christine Escobar Moving from simple customer-facing chatbots to autonomous AI agents connected directly to PMS, POS, and CRM systems changes an IT team’s risk profile entirely. Read the full article here.
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Published on August 18th | By: Alexei Alexis Despite positive signs on the revenue front, AI adoption has yet to translate into significant operating-margin gains, the study found. Read the full article here.
Published on August 12th | By: Aditya Soni MSR client Larridin speaks with Reuters about the future of American AI models, China’s influence in AI, and how American AI models can capitalize on a new opportunity. Read the full article in Reuters.
Published on August 3, 2026 | By: Aditi Bharade Getting good returns on AI spending is the hottest enterprise topic of the day, and AI consultants have a neat cost-saving hack. Read the full article in Business Insider.
Published on July 230, 2026 | By: Joao-Pierre S. Ruth Frothy AI trends, such as tokenmaxxing, pushed many teams to the sudden realization that the check comes due for AI resources. Listen to the full episode in Information Week.
Published on July 26, 2026 | By Nicholas Gordon It was, perhaps, the worst-kept secret in the AI community. Read the full article in Fortune.
Published on July 17, 2026 | By Nicholas Gordon On Thursday, Moonshot AI, a Beijing-based AI startup, unveiled the latest version of its Kimi large language model, which promises performance close to Anthropic’s Fable 5—perhaps the most powerful publicly available model today—at a fraction of the cost. Read the full piece here.
Published on July 10, 2026 | By Meredith Shubel AI coding agents make it easy to pump out code, but leaders say that’s not real productivity. Read the full article on The New Stack.
Published on July 1, 2026 | By Harold Byun AI capability continues to accelerate. Models are becoming more powerful, more autonomous, and more deeply integrated into enterprise workflows. Read the full piece on Techstrong.ai.
Published on June 30, 2026 | By Ameya Kanitkar For over a decade, engineering leaders have relied on frameworks like DORA and SPACE to understand developer productivity. These models brought rigor to a field that once relied heavily on intuition. They helped organizations improve deployment frequency, reduce failure rates and build stronger cultures. Read the… View Article