Ron Mitchell

Short summary In the last year we’ve seen AI agents move from experiments to real business tools. Major platform vendors rolled out agent features and companies are connecting those agents to CRMs, ERPs, and internal documents. The result: faster reporting, fewer manual tasks, and better follow-up on leads — not just flashy demos, but measurable […]

The trend (short summary) – Over the past year we’ve seen a big jump in practical AI agents — systems that can read your data, run tools, and take multi-step actions with little human prompting. – These agents are being used for things like qualifying leads, generating proposals, automating recurring reports, and handling routine customer

Quick summary Over the past year we’ve seen a wave of announcements from major vendors and cloud platforms that put AI agents and low-code “copilot” builders into the hands of business teams. These tools can connect to your CRM, calendar, docs and BI systems to automate routine outreach, qualify leads, generate proposals, and create up-to-date

Quick summary Over the past couple of years, “AI agents” — autonomous, task-focused systems built on large language models — moved from research demos into real business pilots. Cloud vendors and open-source projects made it easier to connect these agents to CRMs, ERPs, calendars, and data warehouses so they can act (not just answer). Companies

Autonomous AI agents — software that plans and steps through tasks on its own — are no longer just lab experiments. Over the last year many businesses have put agents into real workflows: qualifying sales leads in CRMs, auto-scheduling meetings, generating weekly performance reports with retrieval-augmented generation (RAG), and reconciling invoices. Those pilots are showing

Quick summary AI agents — autonomous, task-focused AI programs — moved from demos into real business use in 2024. Companies are combining agent frameworks (LangChain-style toolkits), vector databases, and retrieval-augmented generation (RAG) to give agents access to company documents, CRM records, and live systems. That lets agents do things like draft personalized outreach, generate weekly

What happened Autonomous “AI agents” — programs that can carry out multi-step tasks on their own — have moved beyond research demos into real business use. Companies are embedding agents into workflows for lead follow-up, contract review, scheduling, and automated reporting. Improvements in orchestration platforms, safer guardrails, and integrations with CRMs and data warehouses have

Story summary Over the last year we’ve moved from “chatbots” and one-off pilots to AI agents that can act across systems — read CRM records, query finance tables, create reports, and take actions like sending emails or updating tickets. Major vendor toolkits and prebuilt connectors have lowered the technical barrier, so companies can now build

Short summary AI “agents” — task-focused versions of large language models that can take multi-step actions (research, draft emails, update systems, pull reports) — are no longer just lab experiments. Over the past year we’ve seen platforms and vendors make agents easier to customize and connect to business systems (CRMs, ERPs, reporting databases). That means

Summary AI agents — purpose-built software that can carry out multi-step tasks with little human hand-holding — have moved fast from demos into real business use. Teams are now using agents to qualify leads, update CRMs, generate repeatable sales reports, and run follow-up outreach across channels. The result: less busywork, faster decision-making, and clearer pipeline