Ron Mitchell

AI story summary AI “agents” — autonomous, multi-step AI tools that can act on your behalf — are moving from labs into real business use. Big vendors and open-source projects now make it easy to connect agents to CRMs, ERPs, calendars, and analytics. Instead of one-off prompts, agents can run workflows: qualify leads, create tailored […]

Quick summary AI agents — software that can act, decide, and run tasks automatically using large language models — have evolved from experimental demos into reliable tools companies are using to automate work. Instead of only answering questions, modern agents can pull data from your systems, run multi-step processes (like lead qualification or monthly close

Quick summary AI “agents” — customizable, task-focused AI assistants that can read systems, run workflows, and take actions — moved from demos to real business pilots in 2024. Platforms like custom GPTs, Copilot-style builders, and agent frameworks let teams connect AI to CRMs, ticketing systems, spreadsheets, and BI tools. That means an AI can now

Quick summary AI agents — autonomous, goal-driven software that can read your data, take actions, and talk to systems — are moving fast from experiments into real business use. Modern agent platforms connect to CRMs, calendars, email, and internal knowledge (via retrieval-augmented generation), so they can research prospects, draft personalized outreach, update records, and even

Quick summary AI “agents” — models that can run multi-step tasks, call APIs, and act with minimal human prompts — have moved from demos into real business pilots this year. Companies are using them to qualify leads, draft and send personalized outreach, automate routine CRM updates, and generate on-demand reports. The result: faster responses, fewer

Quick summary AI “agents” — autonomous AI that can read, decide, and act across apps — have moved from demo stage into real business use. Modern agent frameworks (think LangChain-style orchestration + retrieval-augmented generation) can connect to CRMs, ERPs, calendars, and reporting databases to run end-to-end workflows: clean sales pipelines, generate weekly performance reports, open

Summary Over the past year we’ve seen a clear shift: AI agents — autonomous systems that can run tasks, coordinate across apps, and act on goals with minimal human input — are no longer just research demos. Companies are using them for lead qualification, automated reporting, order tracking, and simple decision workflows. These agents plug

Quick summary AI agents — autonomous, task-focused AI that can research, act, and report — are no longer just a tech demo. Businesses are using them to qualify leads, update CRMs, generate weekly sales reports, and automate recurring operational tasks. The shift is driven by better integrations (APIs + CRM connectors), improved prompt engineering, and

Quick story Big cloud and CRM vendors have moved from “AI features” to full-fledged AI agents and copilots that can run multistep business tasks. Microsoft, Google, and Salesforce (among others) now offer tools that can summarize meetings, update CRM records, qualify leads, generate tailored outreach, and pull together pipeline reports — often automatically and in

Quick story AI agents — software that can carry out multi-step tasks autonomously (think: gather data, analyze it, and take action) — are no longer experiments. Over the past 12–18 months, companies across industries have begun shipping agent-driven workflows for things like automated reporting, lead qualification, CRM cleanup, and routine customer follow-up. These agents combine