Ron Mitchell

Short summary AI agent platforms — think autonomous, task-oriented AI that can access your apps, pull data, and take actions — are moving from labs into real business use. Major vendors and startups are shipping tools that let these agents qualify leads, update CRMs, run recurring reports, and automate multi-step processes without constant human prompting. […]

Quick summary Lately, autonomous AI agents — software that can plan, act, and connect across systems with minimal human prompting — have moved from research demos into real enterprise pilots. Teams are using agents to triage leads, run routine data analysis, generate executive reports, and orchestrate cross-system workflows that used to need manual handoffs. Why

Summary — what’s happening now Autonomous AI agents — tools that can perform multi-step tasks with little human prompting — are moving from labs into real business use. Think agents that draft personalized outreach, reconcile CRM data, generate weekly sales reports, or triage customer requests automatically. Builders today use platforms like LangChain, Microsoft Copilot frameworks,

What happened – Over the past year, AI “agents” — models that carry out multi-step tasks and connect to tools and data — have moved out of labs and into real business workflows. – Vendors and startups increasingly offer agent integrations with CRMs, calendars, document stores, and APIs so the AI can act (not just

Short summary AI “agents” — autonomous, task-focused AI that can act across apps and systems — have moved from prototypes into real business use. Companies are now wiring these agents into CRMs, help desks, and reporting pipelines so a single AI assistant can find leads, qualify them, update records, and generate a sales report without

Summary A new wave of AI agents — purpose-built virtual assistants that read your systems, run tasks, and answer questions — is moving from experiments into real business use. Major platforms and enterprise vendors have made it easier to connect agents to CRMs, databases, ticketing systems and dashboards. That means employees can get instant, context-aware

Quick story summary Autonomous AI agents — systems that can take multi-step actions on your behalf (think: read emails, update CRM records, schedule calls, run analyses, and follow up) — have moved from research demos to real business pilots. Big cloud vendors and startups are offering agent frameworks and integrations that make it far easier

Quick story AI agents — autonomous assistants built on modern large models that can use tools, search company data, and act across apps — have moved from demos to real business pilots. Over the last 12–18 months vendors and startups have made it much easier to create “task-specific” agents that schedule meetings, update CRMs, generate

Short summary AI agents — autonomous, task-focused AI that can use tools, look up data, and carry out multi-step workflows — are moving from demos into real business use. Companies are using them to qualify leads, auto-generate customer reports, route work across teams, and automate repetitive sales tasks. The result: faster response times, fewer manual

Short summary Major AI vendors and startups have been rolling out agent-style tools and enterprise copilots that can take multi-step actions — not just answer questions. These AI agents can schedule meetings, pull and summarize cross-system data, create reports, and even run simple workflows across apps. The result: businesses can automate complex, repeatable tasks that