Ron Mitchell

Short summary AI agents — autonomous or semi-autonomous software that can read documents, take actions across apps, and carry out multi-step tasks — have shifted from lab experiments into real business pilots. Over the last year we’ve seen better agent tooling, more enterprise connectors (CRMs, email, calendars, databases), and easier ways to combine retrieval (company […]

Quick summary Enterprises are no longer experimenting with standalone chatbots. The latest shift is toward AI agents — connected, task-oriented systems that combine language models, company data, and automation to complete multi-step workflows (think: qualify leads, update your CRM, schedule follow-ups, and generate a performance report without manual handoffs). Why this matters for business –

Quick summary AI agents — semi-autonomous assistants that can read, act, and follow up across apps — are no longer just demos. Companies are piloting them for lead qualification, customer support triage, scheduling, and automated reporting. The result: faster responses, fewer repetitive tasks, and more scalable operations. At the same time, organizations are paying close

Short summary AI “agents” — software that can plan, act, and complete tasks across apps — are rapidly moving out of labs and into real business workflows. Instead of one-off chat responses, today’s agents can pull data from CRMs, send personalized outreach, book meetings, and update records automatically. That shift is making automation more flexible

Big shift in plain language: AI is no longer just giving suggestions. Modern AI agents can now take actions — send emails, update CRMs, run reports, and schedule follow-ups — by connecting to the apps your teams already use. Major vendors and startups have pushed these “action-taking” agents into production-ready tools, and companies are starting

Summary AI “agents” — software that can act on your behalf across apps (CRM, email, calendars, BI tools) — are moving from experiments into real business use. Instead of just generating text, these agents can qualify leads, draft and send follow-ups, run daily reports, and flag risky deals automatically. Companies that adopt them are seeing

What’s happening Autonomous AI agents — systems that can plan, act, and follow up across apps with little human supervision — are suddenly practical for business. Advances in large language models, better connectors to CRMs and ERPs, and simpler “agent builder” tools mean teams can automate multi-step workflows like lead qualification, proposal drafting, and recurring

Quick summary AI agents — autonomous, multi-step AI workflows that can research prospects, draft personalized outreach, book meetings, and log results in your CRM — are moving from tech demos into everyday business tools. In 2025 we’re seeing these agents integrated directly into major CRMs and communication platforms, making it easier for sales and ops

Quick summary There’s a clear shift right now: enterprise-grade AI agents and “copilot” features are moving from experiments into everyday business tools. Major vendors and startups alike are shipping agents that can access CRMs, pull financials, draft outreach, run analysis, and even take follow-up actions — all with less human hand-holding than traditional chatbots. Why

Quick summary AI agents — small, task-focused AI workers that act across apps and data — are moving from demos into everyday business use. Vendors and startups are embedding agents into CRMs, calendars, chat, and reporting tools so a single “agent” can draft outreach, update records, pull a weekly sales report, and even trigger follow-ups