Ron Mitchell

Story pick (short): Over the past year we’ve seen a clear shift: AI agents — autonomous, goal-driven AI that can act across apps, pull data, and take multi-step actions — are moving from experimental pilots into real operational use. Major AI platforms now provide agent frameworks and more companies are testing agents for tasks like […]

Why this matters now – Over the past year the biggest shift in business AI has been the move from standalone chatbots to production-ready AI agents — systems that can act on your behalf across apps, pull live data, and complete multi-step tasks. – These agents are no longer just demos. Vendors and open-source projects

Quick summary AI agents and embedded copilots are moving from novelty to everyday tools. Modern tools can read dashboards, write plain‑English summaries, and—crucially—trigger workflows (alerts, approvals, CRM updates, purchase orders) when KPIs cross thresholds. That shifts reporting from “look what happened” to “here’s what to do next.” Why this matters for business – Faster decisions:

Quick story AI agents — software that can act across apps, follow multi-step instructions, and learn from outcomes — jumped from demos into real business use in 2024–25. Big vendors rolled out “custom agents” in productivity suites and startups built specialist agents for sales outreach, customer support, and automated reporting. Companies are already using agents

Summary AI agents — autonomous software that can research, take actions, and report results — have moved from labs into real business use. Teams are using agents to find and qualify leads, draft personalized outreach, update CRMs, and generate sales and performance reports automatically. The result: faster workflows, fewer manual tasks, and clearer, near-real-time visibility

Hook: Autonomous AI agents — small software workers that can plan, act, and follow up across apps — are finally moving from experiments to real business pilots. That shift matters for leaders who want faster sales cycles, cleaner reporting, and lower operating costs. Summary of the story – What’s happening: Advances in large language models,

Quick summary Autonomous AI agents — models that can use tools, call APIs, and complete multi-step tasks with minimal human prompts — have moved beyond proofs-of-concept into real business use. Companies are using them to qualify leads, populate CRMs, generate personalized outreach, automate routine reporting, and trigger downstream workflows. The result: faster response times, more

Summary AI agents — autonomous, task-focused AI that can read your systems, take actions, and report results — are no longer just a research topic. Companies are deploying agents to qualify leads, book meetings, update CRM records, and auto-generate sales and performance reports. The result: faster response times, fewer manual steps, cleaner data, and more

Summary A growing wave of AI agents—software assistants that can read emails, access CRMs, create documents, and take actions—has moved from research demos into real business use. These agents can draft outreach, update records, summarize meetings, and generate reports automatically by pulling from internal data and public sources. Many companies are already running pilot projects

Quick summary AI agents—customized, semi-autonomous models that can read your data, act inside apps, and carry out multi-step tasks—are being adopted beyond labs and dev teams. With easier low-code builders, retrieval-augmented generation (RAG) for secure access to company data, and integrations into CRMs and workflow tools, companies are using agents for things like prospect outreach,