Ron Mitchell

Quick summary Autonomous AI agents — software that plans and carries out tasks with minimal human direction — have moved from lab experiments into real business workflows. Companies are now using agents to enrich leads, draft personalized proposals, automate routine reconciliations, and build up-to-date KPI dashboards. The result: faster reporting, fewer manual errors, and more […]

Hook: AI agents — autonomous software that can research, act in apps, and complete multi-step tasks — have crossed a major threshold this year. They’re no longer just R&D proofs of concept; they’re being embedded into sales workflows, reporting pipelines, and back‑office automation. The story in plain terms: – Companies are putting AI agents to

Quick summary AI agents—software that can plan, act, and use other apps on your behalf—are finally moving out of experiments and into real business use. Recent advances in agent frameworks, connector libraries, and enterprise copilots make it easier to automate sales tasks, customer follow‑ups, routine reporting, and process orchestration. Why this matters for your business

Short summary AI agents — persistent, goal-oriented AI helpers that can run multi-step tasks (think: qualify leads, draft proposals, monitor pipelines, or generate weekly reports) — are no longer just experiments. Over the past year we’ve seen more companies push agents from lab pilots into everyday workflows. Improvements in context handling, retrieval-augmented generation (RAG), and

Quick summary AI agents — software that can act autonomously across apps (CRM, email, calendar, reporting tools) — are no longer just lab experiments. Businesses are piloting agents that qualify leads, personalize outreach, update pipelines, and generate automated sales reports. The result: teams spend less time on repetitive tasks and more time closing deals. Why

The story (short version) In 2025 we’ve crossed a practical tipping point: AI agents — autonomous, task-focused AI that can read your systems, take actions, and produce reports — moved from proofs-of-concept into real business use. Companies are no longer just experimenting with chatbots; they’re deploying agents that qualify leads, update CRMs, generate weekly executive

Quick summary – Over the past year major vendors and enterprise teams have pushed AI agents out of prototypes and into real business workflows. Instead of one-off chat experiments, companies are building task-focused agents that connect to CRMs, data warehouses, reporting tools, and business systems to do work — from qualifying leads to generating weekly

Quick takeaway AI agents — autonomous, task-focused AI that can read documents, interact with systems, and take actions — moved this year from experiments into real frontline use. Businesses are using them for lead qualification, automated reporting, order follow-up, and routine operations work. The result: faster decisions, lower costs, and fewer repetitive errors — but

Quick summary – Autonomous AI agents — software that can plan, act, and complete multi-step tasks with little human handoff — have moved from labs into business pilots. Think bots that draft outreach, run data pulls, generate reports, and follow up on leads automatically. – This isn’t just hype. Companies are using agents to speed

Quick summary AI “agents” — software that can act autonomously, chain tasks, and call tools (calendar, CRM, email, dashboards) — have moved from demos to practical pilots. Think of them as smart digital teammates that can: gather data, draft outreach, run analysis, and even trigger actions across systems. Tools and frameworks like Auto-GPT, LangChain, and