Ron Mitchell

Quick summary AI agents—autonomous systems that can carry out tasks, make decisions, and coordinate across apps—have jumped from lab demos into real business use. Companies are using agents to qualify leads, generate ongoing sales and operations reports, automate repetitive workflows, and summarize client interactions. That shift turns AI from a “nice-to-have” pilot into a tool […]

Big idea (what’s happening) – Over the last year, autonomous AI agents — systems that can plan, act, and use tools without constant human prompting — moved from demos into real business use. No-code/low-code agent builders, better retrieval-augmented generation (RAG), and tighter integrations with CRMs and BI tools mean organizations can now automate complex workflows:

AI story (brief) AI “agents” — autonomous, task-focused AI that can read your data, call apps, and take actions — are moving out of research labs and into everyday business work. Major vendors and automation platforms now support agent-style workflows that can draft outreach, qualify leads, update CRMs, generate regular reports, and even coordinate scheduling

AI story — short summary Autonomous AI agents — small, task-focused AI programs that combine language models with tools (calendars, CRMs, web search, databases) — have moved quickly from experiments into real business pilots. Open-source frameworks and enterprise products now let teams build agents that draft outreach, summarize meetings, run recurring reports, and automate routine

Quick snapshot AI “agents” — software that can act on your behalf, pull data, and complete tasks with little supervision — have moved from experiments to real business projects. Teams are using agents to qualify leads, draft proposals, automate recurring reports, and trigger workflows across CRM, ERP, and analytics tools. That shift is speeding deals,

Short summary AI “agents” — systems that can plan, act, and use tools on behalf of people — are moving from labs into real business workflows. Over the last year vendors and startups have packed these agents with connectors (CRMs, calendars, email, BI tools) and safer guardrails, letting them do tasks like prospecting outreach, meeting

Quick story summary AI “agents” — autonomous systems that can read your CRM, schedule meetings, draft messages, and generate reports — have moved from proof-of-concept projects into mainstream enterprise tools. Over the last 18 months we’ve seen vendors and startups embed agents into CRMs, BI tools, and automation platforms so they can complete multi-step tasks

Quick summary Major AI platforms have made building custom AI agents — often called GPTs or copilots — fast and low-code. These agents can connect to your documents, CRM, calendars, and reporting tools to answer questions, draft outreach, and even trigger automated workflows. Why this matters for business – Faster work: routine tasks like monthly

Quick summary AI agents — purpose-built, autonomous AI assistants that can access your apps, run workflows, and act on behalf of users — have moved from research demos into real business deployments. Over the past year major platforms and startups have made it easier to create agents that do things like qualify leads, prepare weekly

Quick summary AI agents — autonomous, connected AI assistants that can read emails, update CRMs, run reports, and take actions — have moved beyond lab demos into real business use. Major platforms and a wave of startups now offer agent frameworks and “plug-and-play” connectors that let these agents talk to calendars, sales tools, BI systems,