Ron Mitchell

Quick summary AI agents — autonomous, task-focused AI assistants that can read your systems, take actions, and report results — are no longer just demos. Over the last 18–24 months major vendors and startups have pushed agent-style tools into CRMs, email stacks, and analytics platforms. That means AI can now do things like qualify leads, […]

Quick summary AI agents—software that can act autonomously to complete tasks, run workflows, and talk to other apps—are moving from experiments into everyday business use. Companies are already using agents to draft personalized outreach, run scheduled reporting, triage customer requests, and even trigger downstream automation when certain conditions are met. Why this matters for businesses

Quick summary Autonomous AI agents — small, task-focused AI programs that can act, plan, and connect to your systems — are no longer experimental. In the last 12–18 months vendors and platform builders have made it much easier to create, orchestrate, and integrate agents for real work: qualifying leads, drafting and routing proposals, generating executive

Summary There’s a clear trend: businesses are moving from standalone AI tools to “AI agents” — autonomous systems that can access data, run workflows, and act on behalf of users. Instead of asking an AI a single question, teams can set an agent to qualify leads, generate weekly BI reports, route approvals, or draft and

Short summary AI “agents” — software that can act on your behalf to complete multi-step tasks — went from research demos to practical business tools in 2023–24. Platforms and frameworks (think AutoGPT-style workflows, LangChain integrations, and vendor copilots) now let companies build agents that pull data from CRMs, run analysis, send messages, and update systems

Timely story (short): AI agents — autonomous software “workers” that combine large language models, APIs, and automation — have moved from experiments to real business pilots. Over the past year more companies and platforms have launched agent-friendly features and connectors that let organizations automate tasks end-to-end: qualify leads, draft personalized outreach, update CRMs, schedule meetings,

Quick summary Major vendors and startups have spent the last two years turning autonomous AI agents — software that can plan, act, and interact across apps — from hobby projects into enterprise-ready tools. In 2025–26 we’ve seen orchestration platforms, stronger API integrations with CRMs and ERPs, and practical governance features that make production deployments viable.

Quick summary AI agents are autonomous software that can carry out tasks across apps — from qualifying leads in your CRM to running weekly sales reports and booking demos. Over the last year we’ve seen vendors and startups push agent frameworks and integrations that make these capabilities easier to deploy without heavy engineering. Why this

Quick summary AI agents — autonomous, task-focused AI that can read your CRM, run reports, send emails, and schedule work — have moved from research demos to real deployments. Over the last 18–24 months the biggest change isn’t better chatbots; it’s agents that can connect to systems, take multi-step actions, and complete day‑to‑day workflows (lead

Summary AI “agents” — systems that can take multi-step actions (browse, call APIs, update systems, and follow up autonomously) — have moved from demos into practical enterprise tools. Over the last year major vendors and startups have packaged agent frameworks that connect to CRMs, email, calendars, and RPA systems, so these agents can actually complete