Ron Mitchell

AI story (short): Autonomous AI agents — software that can perform multi-step tasks, talk to systems, and make decisions — are moving fast from labs into real business tools. Instead of just answering questions, these agents can follow up with leads, update CRMs, generate weekly sales reports, and even coordinate simple approvals. Major vendors and […]

Quick summary AI agents — autonomous, task-focused AI that can search, act, and follow up — have moved from labs into everyday business tools. Today, low-code platforms and major enterprise apps are embedding agents that can handle things like qualifying leads, triaging support tickets, and generating executive reports. That shift means companies can automate more

Summary AI agents — autonomous, task-focused AI that can read systems, act, and report results — have moved rapidly from proofs-of-concept into real business use. Companies are using agents to draft proposals, run targeted sales outreach, auto-summarize meetings, reconcile reports, and trigger workflows across CRM, ERP, and analytics tools. The result: faster sales cycles, fewer

Quick summary AI agents — autonomous, goal-directed AI that can act across apps and systems — have moved from lab demos into real business pilots. Over the last year we’ve seen platforms and vendors make it easier to build agents that: – run sales workflows (lead research, outreach sequencing, CRM updates), – automate reporting (pulling

Quick summary AI agents — autonomous workflows powered by large language models — are moving from experiments into real business use. In recent months more companies have begun connecting these agents to CRMs, calendars, and reporting systems so they can qualify leads, create sales reports, summarize meetings, and run routine follow-ups without constant human direction.

Short summary AI agents—autonomous, task-focused AI assistants that can read systems, take actions, and learn from outcomes—have moved fast from researcher demos to commercial tools. Companies are now using agents to qualify leads, auto-compose outreach, run routine finance reconciliations, and generate recurring performance reports. That shift matters because agents can cut manual work, speed decision

Brief summary Autonomous AI agents — tools that can research, draft, run workflows and talk to your systems with little human direction — are crossing from experimental pilots into everyday business use. Vendors are shipping tighter CRM, analytics, and workflow integrations, and teams are using agents for prospect research, automated reporting, and routine process work.

Quick summary AI agents — autonomous, goal-driven software that can read, act, and interact with tools — are moving from tech demos into real business use. Modern agents combine large language models with connectors to CRMs, databases, calendars, and email so they can draft outreach, update records, build reports, and even triage customer issues without

Quick summary Major cloud vendors and enterprise software makers are rolling out—or making it easier to build—AI agents: autonomous, task-focused AI that can connect to your calendars, CRM, databases, and apps to complete multi-step workflows. Unlike single-response chatbots, these agents can run sequences of actions, fetch and verify data, create reports, and hand off or

Hook: Autonomous AI agents — tools that can perform multi-step tasks by themselves — are moving quickly from experiments into real business workflows. Sales teams are using them to qualify leads; operations teams are auto-generating reports; finance teams are automating reconciliations. This shift matters for every business leader thinking about cost, speed, and accuracy. What’s