Ron Mitchell

Quick summary Autonomous AI agents — AI systems that can act, decide, and run multi-step tasks with minimal human input — are moving out of labs and into real business use. Major platforms now make it possible to build custom agents that connect to CRMs, data warehouses, email, and internal tools. That means companies can […]

Big picture AI agents — autonomous, task-focused AI that can read systems, take actions, and update records — moved from labs into real business pilots in 2023–24. Companies are using them to qualify leads, generate and send proposals, refresh dashboards, and run recurring reports without manual handoffs. That shift is less about flashy demos and

Short summary AI agents — automated assistants that can read your data, take actions across apps, and follow up with customers — are moving from experiments into real business use. Teams are now using agents for tasks like qualifying leads, drafting personalized outreach, summarizing meetings, and automating routine workflows. That makes AI agents one of

AI agents: a practical playbook for business automation and reporting Quick summary Autonomous AI agents — tools that can plan, execute multi-step tasks, call APIs, and learn from feedback — have moved from research demos into real business pilots. Companies are using agents to triage leads, automate routine customer replies, assemble weekly sales reports, and

Quick summary AI “agents” — autonomous or semi-autonomous software that can take multi-step actions (schedule meetings, draft and send sales outreach, generate monthly reports, triage support tickets) — went from experimental to enterprise-ready in 2024–25. More vendors and platforms now offer agent-building tools, and companies are moving beyond point AI features to deploy agents that

Short summary AI “agents” — autonomous assistants that can plan, act across apps, and complete multi-step tasks — have moved quickly from demos into real business use. Companies are using agents to draft and send sales outreach, qualify leads, automate recurring reports, and even triage customer issues. The result: faster decisions, fewer manual steps, and

Quick summary AI “agents” — autonomous assistants built on large language models that can call APIs, read files, and carry out multi-step tasks — have moved from experiment to practical tool for businesses. Instead of a person asking a model one question at a time, agents can run a workflow end-to-end: gather data, update a

Big tech pushed AI agents and “copilot” features into everyday apps this year (think Microsoft Copilot, Google’s Gemini tools, and Apple’s Apple Intelligence). The big change isn’t just smarter chat — it’s agents that connect to your systems, pull private data, and act on your behalf across workflows. What this means for businesses – AI

Summary AI “agents” — autonomous assistants that can read your CRM, pull data, take actions in apps, and draft messages — are moving from experiments to everyday business tools. Thanks to better agent frameworks, cheap access to large language models, and ready connectors for CRM, email, and cloud storage, companies can now automate multi-step workflows

Quick story Autonomous AI agents — software that can plan, act, and follow-up without constant human prompts — have moved from demos into real business use. Over the past 18 months, major vendors and startups have launched enterprise-ready agent platforms and orchestration tools that connect models to CRMs, ERPs, ticketing systems, and internal knowledge bases.