Ron Mitchell

Quick summary AI agents — small, autonomous software assistants that can read, write, and act across apps — have moved from labs into real business use. Instead of a person manually pulling dashboards, sending follow-ups, and chasing approvals, an AI agent can gather data from your CRM, summarize customer health, draft an outreach sequence, and […]

AI story summary AI agents — autonomous, multi-step AI that can research, act, and follow up without constant human prompts — have moved from demos into real business use. Over the last year, platforms and frameworks (agent toolkits, integrations with RPA and CRMs, and safer retrieval methods) have made it practical to run these agents

Story (quick summary) AI agents — autonomous, task-focused AI that can act across apps, pull data, and complete workflows — have moved from lab demos into real business use. Over the past year, teams in sales, customer service, and finance began deploying agents to run end-to-end tasks: qualify leads, draft and send follow-ups, reconcile invoices,

Quick summary – The big shift: AI is no longer just chatbots or single-step helpers. New “AI agents” can run multi-step workflows, access your systems, and take actions — from qualifying leads to generating monthly reports. – Why it’s trending: toolkits and orchestration platforms (think agent frameworks and enterprise copilot builders) are making it practical

Quick summary AI agents — autonomous, task-focused AI that can act across apps — are moving from labs into everyday business use. Over the past year we’ve seen platforms and SaaS vendors add agent features that can do things like qualify leads, run outreach sequences, gather data from systems, and produce routine reports without constant

Summary AI “agents” — autonomous or semi‑autonomous AI tools that complete tasks end‑to‑end (think: draft outreach, summarize meetings, update reports, or run follow‑ups) — moved from labs into real business use in 2024–25. Improvements in large language models, easier APIs, and low‑code agent frameworks let companies embed these agents into sales, operations, and reporting workflows

Short summary AI agents — autonomous, task-focused AI tools that can plan, act, and integrate with your systems — are no longer just a developer curiosity. Over the past year, businesses have started using agent frameworks and plug‑and‑play “GPTs” to automate sales outreach, generate recurring reports, and run routine operational checks. Those agents combine generative

Over the past year major platforms and vendors have moved AI agents from experiments into production-ready features. What used to be “prove it” projects (scripts that call a model and stop) are now full workflows: agents that fetch data, run analytics, generate reports, and trigger downstream systems — often inside familiar tools like CRMs, BI

Short summary AI agents — autonomous software that can read, reason, and act on your behalf — are no longer just experiments. Companies are using them to follow up on leads, automate routine operations, generate sales reports, and triage customer requests. Instead of a person copying and pasting between systems, an agent can pull CRM

Story summary Major CRM and business-software vendors are embedding AI agents — not just chatbots, but proactive assistants that can draft outreach, update records, run forecasts, and generate executive reports automatically. Companies from large enterprises to mid-market teams are piloting these agents to reduce administrative work, speed response times, and personalize customer interactions at scale.