The agentic AI market grew from $7.6 billion in 2025 to a projected $10.8 billion in 2026, and Gartner projects 40% of enterprise applications will include embedded task-specific AI agents before the year ends. Yet only 11% of enterprises run AI agents in production. The gap is not a capability problem. It is a selection problem: most teams are picking tools before understanding
Multi-agent AI frameworks are no longer a research experiment. Banks run compliance workflows on them. Manufacturers use them for supply chain optimization. And enterprise teams are making framework decisions that will shape their AI roadmap for years. Three names come up in every serious evaluation: CrewAI, AutoGen, and now the Microsoft Agent Framework, which is AutoGen’s official successor since February
Most enterprise AI projects hit a wall before they ever reach production. The root cause, more often than not, is a tool selection made before anyone properly understood what the tool was supposed to do. According to McKinsey’s 2025 State of AI report, 88% of organizations now use AI regularly, but nearly two-thirds haven’t scaled it beyond pilots. That gap is
SAP’s end-of-life timeline for Crystal Reports is no longer theoretical. Crystal Reports 2016 support ended on December 31, 2024, and Crystal Reports 2020 reaches end of maintenance on December 31, 2026 . For organizations running either version, this directly impacts long-term reporting strategy and accelerates the need for Crystal Reports to Power BI migration. After these dates, there are no
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