When a 77-year-old promotional products supplier pushes generative AI from experiment to everyday habit, it’s rarely because of a shiny chatbot. At Gold Bond Inc., a major player in the $20.5 billion promotional products industry, CIO Matt Price centered AI… Read More »Inside Gold Bond’s IT-Led AI Rollout: Why Workflow Integration Beats Chatbot Hype
Meta’s agreement to acquire Singapore-based agent startup Manus for more than $2 billion is not just another headline AI deal. For enterprise AI leaders, it is a clear signal that the center of gravity is shifting from the race to… Read More »Meta’s $2 Billion Manus Bet: Why the AI Execution Layer Now Matters More Than Models
At Microsoft Ignite 2025 in San Francisco, Microsoft and NVIDIA used the conference floor to make a clear argument to cloud architects and IT leaders: the next phase of enterprise AI will be delivered as a tightly integrated stack, from… Read More »Inside Microsoft Ignite 2025: How Microsoft and NVIDIA Are Building a Full-Stack AI Platform
Enterprises exploring agentic AI now face an overwhelming number of frameworks, tools, and orchestration patterns. The choice is no longer simply “which large language model (LLM)?” but “what kind of agent architecture are we building, where do we invest training… Read More »How a New Agentic AI Framework Helps Enterprises Choose Between Training Models and Training Tools
Amid persistent talk of an “AI bubble,” Salesforce’s latest numbers from its Agentforce platform point to a different story emerging inside large organizations: AI agents are quietly becoming production infrastructure rather than experimental side projects. In a single quarter, Salesforce… Read More »Salesforce’s Agentforce Boom Shows Enterprise AI Is Moving Past the Hype
Multi-agent AI is having a moment in the enterprise. From AI “teams” of coding assistants to fleets of specialized financial agents, the implicit promise is that more agents, more tools, and more collaboration will reliably deliver better outcomes. New research… Read More »When Multi-Agent AI Helps — and When It Hurts: Lessons from New Google–MIT Research