Ron Mitchell

Short summary AI agents—autonomous, goal-oriented software that can read data, take actions, and talk to systems or people—are moving from tech demos into real business use. Companies are using agents to qualify leads, automate repetitive workflows, generate real-time reports, and triage customer requests. That shift is making workflows faster, errors fewer, and teams more productive. […]

Quick summary – Over the last year we’ve seen AI agents — autonomous, task-focused AI that can read, act, and report — move out of labs and into business workflows. Companies are using them to qualify leads, draft outreach, reconcile data, and produce recurring reports without constant human rework. – The change is driven by

Summary AI agents — small, goal-driven AI programs that can call APIs, read systems, and take actions — are moving from experiments into real business workflows. Instead of asking a person to pull a report, qualify a lead, or draft outreach, companies are chaining agents to do those steps automatically: pull CRM data, enrich records,

What’s happening AI “agents” — configurable software that can act on behalf of users to run workflows, fetch data, and make decisions — have gone from demo projects to practical tools. Fueled by custom GPTs, low-code agent builders, and tighter integrations with CRMs and BI tools, companies are now using agents to qualify leads, automate

Short summary Autonomous AI agents — software that can carry out multi-step tasks by itself (think: research, compose, take actions, iterate) — have moved from demos into real business pilots. Companies are using these agents to automate sales outreach, generate recurring reports, triage support tickets, and stitch together data from CRMs and internal docs. The

Quick story summary AI agents — autonomous AI “workers” that can access tools, pull company data, and take multi-step actions — have moved from experiments to practical business tools. Over the last year organizations have layered LLM-based agents onto CRMs, ERPs, and BI systems to automate research, personalize outreach, and produce recurring reports. Major platform

Quick summary AI agents—software that can act autonomously to complete tasks—have moved from labs into real business workflows. Today you’ll see agents qualify leads, auto-update CRM records, generate weekly performance reports, or run parts of customer service with minimal human hand-holding. They combine language models, retrieval (RAG), and automation connectors to do multi-step work without

Summary AI agents — models that can run tasks, call tools, and act on data without constant human prompts — moved from lab demos into real business use in 2024. Major vendors released builder tools and enterprises started deploying agents for lead qualification, CRM updates, automatic reports, and routine customer follow-ups. Open-source frameworks and vendor

Short summary AI “agents” — autonomous or semi-autonomous AI assistants that can take multi-step actions, talk to your systems, and complete tasks — are moving from labs into real business workflows. Tools and frameworks (think agent orchestration, CRM plug‑ins, and integrations with reporting systems) make it easier for teams to automate outreach, generate roll‑up reports,

The story in brief – Over the last year, we’ve seen a clear shift: AI agents — small, goal-oriented AI programs that act on behalf of users — are being used beyond R&D pilots and into everyday sales and operations workflows. – Companies are automating repetitive work like CRM updates, lead qualification, outreach drafts, and