Ron Mitchell

Quick summary AI agents — software that can act on behalf of people (run searches, pull data, send messages, update systems) — moved from lab demos to real business pilots this year. Companies are using agents to automate repetitive workflows, generate and distribute reports, and handle routine customer or internal requests. The result: faster decisions, […]

Quick summary AI agents — autonomous systems that can fetch data, take actions, and run multi-step workflows — are no longer just a lab experiment. Over the last year we’ve seen more companies build production-grade agents that handle lead qualification, daily reporting, customer follow-ups, and routine approvals. Those agents connect to CRMs, data warehouses, and

Short summary AI “agents” — purpose-built models that can take actions, run multi-step workflows, and connect to your apps — are moving from R&D labs into everyday business use. Tools like customizable GPTs, Microsoft’s Copilot experiences, and open agent frameworks (LangChain, etc.) make it practical for teams to automate tasks such as sales outreach, data

Summary AI “agents” are software that use large language models to carry out multi-step tasks on their own — for example, researching a prospect, writing email drafts, updating a CRM, and scheduling meetings. Over the last year these agents have become more reliable because of better models, tools (like LangChain), and enterprise-friendly building blocks such

Story summary AI agents — task-focused “copilots” built on large language models that can access tools, data, and workflows — moved from experiments to real business use in 2023–24. Companies are embedding these agents inside CRMs, analytics tools, and automation platforms so they can draft outreach, generate timely reports, route exceptions, and trigger follow-up actions

Quick summary AI agents — autonomous, task-focused software that can read your data, take actions, and talk to people — are moving from experiments to everyday business tools. Vendors are shipping enterprise-ready agent platforms that connect to CRMs, document stores, and reporting systems. Companies are using agents to draft outreach, qualify leads, auto-update records, and

Step 1 — The story in one line There’s a clear shift: AI agents — tooling that can autonomously carry out tasks like drafting emails, updating CRMs, and generating reports — are moving out of R&D labs and into production across sales and operations teams. Step 2 — Why this matters for businesses – Faster,

Summary AI “agents” — small, task-focused AI programs that can act autonomously (e.g., qualify leads, run follow-up emails, pull data and draft reports) — are shifting from experiments to everyday business tools. Improvements in large language models, secure data connectors, and low-code agent builders mean companies can automate end-to-end work that used to need human

Quick summary AI agents — models that act on behalf of users to complete tasks (think: automated outreach, calendar scheduling, lead routing, and recurring report generation) — went from research curiosity to practical business tools over the last 18–24 months. Companies are now pairing these agents with CRMs, help desks, and BI tools so the

Quick summary – Over the past year businesses have moved beyond experimenting with large language models. What’s changing now: packaged AI agents — pre-built, connected workflows that can read your CRM, calendar, and reports — are being deployed in production to automate tasks like lead qualification, follow-up emails, and routine reporting. – These agents combine