Ron Mitchell

The story (short) Over the last 18 months, “AI agents” — autonomous or semi-autonomous software that can act on your behalf (e.g., triage leads, draft messages, pull insights) — moved from demos into real business use. Big vendors embedded these agents into CRMs and productivity suites (think Copilot-style features in Microsoft and Salesforce, plus custom […]

Short summary AI agents — autonomous software that can run tasks, make decisions, and connect to your tools — moved from labs into real business use in 2024–25. Big vendors and startups added agent capabilities to CRMs, help desks, and analytics platforms, letting teams automate multi-step processes (for example: qualify a lead, update records, schedule

What happened (short summary) AI “agents” — AIs that can act across apps, follow multi-step instructions, and make decisions — have jumped from research demos into real business pilots. Companies are using them to qualify sales leads, generate and deliver routine reports, automate order and ticket triage, and run recurring data checks. The shift is

What’s happening Autonomous AI agents — systems that can take multi-step actions (write outreach, pull data, update CRMs, generate reports) without constant human prompting — have moved from experimental demos to practical tools. Low-code platforms, better retrieval-augmented generation (RAG), and tighter API integrations mean agents can now connect safely to business systems like CRMs, calendars,

Short summary AI “agents” — autonomous, task-focused systems that combine language models, data retrieval, and workflow automation — have shifted from experiments to real business pilots in 2024. Companies are using agents to qualify leads, update CRMs, draft personalized outreach, and run recurring sales reports without manual intervention. That means less time on repetitive work

Quick summary AI agents — autonomous systems that can use apps, call APIs, and carry out multi-step tasks — have recently shifted from tech demos into enterprise-ready tools. Companies are now using agents to run routine workflows: qualify leads in CRM, pull and summarize sales and finance data, automate order processing, and generate regular performance

Quick summary AI agents — autonomous software that can read, decide, and act across apps — moved from demos into real business pilots in 2024–25. Companies now deploy agents for things like lead qualification, scheduling, order tracking, and exception handling. The difference vs. traditional automation: agents can combine language understanding, process logic, and connectors to

Quick summary – Over the last 12–18 months, more companies have moved from experimenting with chatbots to deploying AI agents that run multi-step tasks — things like research, lead qualification, personalized outreach, and automatically updating sales reports. – These agents combine language models, access to internal data (via retrieval-augmented generation or RAG), and automation tools

Quick summary Autonomous AI agents — software that plans, acts, and completes multi-step tasks with minimal human supervision — have jumped from research demos to real business pilots. Companies are using them to triage customer requests, run data extraction and reconciliation, create periodic reports, and trigger downstream automations. The result: faster workflows, fewer manual handoffs,

What happened (short summary) – Over the last year, leading AI platforms pushed easy-to-build “AI agents” and orchestration tools that do multi-step work on their own — from pulling data and drafting emails to updating systems and generating reports. – These agents combine language models, connectors (to CRM, BI, Slack, etc.), and business rules so