Ron Mitchell

Quick summary AI agents—software that can take actions for users (send emails, update CRMs, schedule meetings, pull reports)—are no longer just a research headline. Over the past year we’ve seen more companies move from one-off pilots to production deployments that automate routine sales and ops work. That shift matters because it turns “AI as a […]

Summary AI agents—software that can act, decide, and carry out tasks across apps—are moving out of pilots and into real business workflows. Companies are using agents to draft and personalize sales outreach, qualify leads, run customer support triage, and automate regular reporting. The result: faster response times, fewer manual handoffs, and measurable time savings —

What’s happening Autonomous AI agents — software that can act on behalf of people across apps, pull live data, and complete multi-step tasks — are moving from labs into real business use. Instead of just suggesting text, these agents can qualify leads, update CRMs, generate weekly sales reports, and even book meetings by interacting with

Short summary AI agents — autonomous, task-focused AI that can act across apps and data — are no longer an experiment. Over the past 18 months we’ve seen companies stitch LLMs, connectors, and business rules into agents that can run sales outreach, create recurring reports, triage support tickets, and summarize meetings end-to-end. That shift turns

Big picture summary This year we’ve seen a clear shift: major AI platforms and enterprise tools are shipping “agents” — AI that can act autonomously across apps, follow multi-step workflows, and connect to your data. Think of an agent that drafts and follows up on sales outreach, monitors orders and escalates exceptions, or generates weekly

Summary AI agents — software that autonomously performs tasks by connecting to data, apps, and people — are no longer a niche experiment. Businesses are using agents to run end-to-end workflows: generate and distribute sales and financial reports, triage customer issues, run outreach sequences, and trigger follow-up actions across CRMs and BI tools. Why this

Short summary AI agents — the automated assistants that act on behalf of users, chain together tasks, and talk to other apps — are no longer just lab demos. Over the past year we’ve seen a surge in no-code agent builders, tighter integrations with CRMs and calendar systems, and more low-latency, multimodal models that let

Summary AI agents — software that can fetch data, take actions, and talk to people or systems — are moving from demos into real business use. Instead of just suggesting text or insights, these agents can qualify leads, book meetings, update CRMs, and generate routine reports automatically. That means less busywork for teams, faster responses

Quick summary AI agents — autonomous, multi-step AI that can research, act on tools, and return results — have crossed from labs into real business workflows. Big vendors (Copilot-style products and CRM-native AI) plus a growing startup ecosystem now offer agents that can qualify leads, draft outreach, reconcile sales numbers, and produce executive-ready reports. Why

Quick summary AI agents — autonomous assistants that read your CRM, send emails, run reports, and trigger workflows — have shifted from demos into real business use. Over the last 12–18 months many vendors added agent-building tools and connectors (CRM, calendar, analytics), and forward-looking teams are using them to speed lead qualification, automate recurring reporting,