Ron Mitchell

What happened AI “agents” — software that can plan, act, and connect to your tools (CRM, email, calendar, databases) — are no longer just research demos. Vendor platforms and startups make it easy to build agents that do real work: qualify leads, send personalized outreach, summarize meetings, and generate near‑real‑time reports. Companies are moving these […]

Quick summary AI agents — autonomous, goal-driven AI tools that can act across apps, fetch data, and complete tasks — are no longer just research demos. Over the last 18 months we’ve seen major platform vendors and enterprise tools bake agent capabilities into their products (think “Copilot” style assistants, agent builders, and no-code orchestration). That

Short summary AI agents — autonomous, connected AI that can use tools, access systems, and act on your behalf — moved from experiments into real business use in 2024–25. Major vendors added deeper integrations (CRMs, calendars, BI tools) and better guardrails, so agents can now handle recurring work like lead triage, follow-ups, and automated reporting

Short summary There’s been a clear shift: autonomous AI agents — systems that can plan, act, and interact with apps on their own — are leaving research demos and showing up in real workflows. Sales teams use agents to qualify leads and update CRMs. Operations teams use them to run routine reports and trigger follow-up

Quick summary AI agents — task-focused AI that can use tools, access company data, and act autonomously — have moved from experiments to production in more businesses. Instead of only generating text, today’s agents connect to CRMs, calendars, knowledge bases, and reporting tools to run parts of revenue and operations workflows end-to-end: qualify leads, draft

Quick summary AI agents — software that plans, acts, and connects to other apps on your behalf — are no longer just experiments. Major vendors and startups are shipping agent frameworks that let AI interact with CRMs, calendars, email, and reporting tools. That makes it possible to automate multi-step business workflows (lead qualification, order processing,

Quick summary AI “agents” — autonomous or semi-autonomous AI assistants that can read, act, and chain tasks across apps — have moved from demos into real business use. Over the last year, major vendors and startups released agent builders and integrations that make it easier to connect AI to CRMs, calendars, reporting tools, and document

Short summary AI “agents” — autonomous, LLM-driven assistants that can take multi-step actions (research, email outreach, update systems, generate reports) — have moved from demos into real business pilots. Companies are using agents to qualify leads, automate repetitive workflows, and produce near-real-time operational reports without a deep IT project. Why this matters for business leaders

Summary — what’s happening AI “agents” — autonomous tools that can run tasks, pull data, talk to apps, and make decisions — are finally practical for business use. Instead of one-off prompts, companies are combining agent frameworks, secure data connectors, and monitoring to automate whole workflows: sales outreach, monthly reporting, invoice reconciliation, customer follow-ups, and

What happened (short summary) In the last year, AI agents — systems that can act autonomously across apps and data — moved out of labs and into real business workflows. Major cloud and AI providers have packaged “copilot” and agent features into productivity and CRM tools. At the same time, smaller vendors and open frameworks