Ron Mitchell

Quick summary AI agents — software that can act autonomously across apps, pull data, and complete multi-step tasks — moved from experiments to practical tools this year. Companies are using them to qualify leads, update CRMs, generate and distribute daily sales reports, and automate repetitive operational workflows. That shift makes AI less a novelty and […]

Quick summary Over the last 18 months the market shifted from “research demos” to practical AI agents that can run workflows, fetch company data, and act on your behalf inside apps. Platforms and frameworks (LLM-based agents, orchestration tools, and secure connectors) now let agents update CRMs, generate recurring reports, triage tickets, and even trigger multi-step

Quick summary AI “agents” — autonomous, goal-driven AI that can read your systems, take actions, and deliver outcomes — have moved from demos to real business pilots. Recent advances in LLMs, connectors to CRMs and data lakes, and safer retrieval techniques mean agents can do things like draft tailored sales outreach, update deals in Salesforce,

Quick summary AI agents — software that can act autonomously to complete tasks, talk to systems, and make decisions — have moved past demos. In the last year we’ve seen vendor toolkits, agent frameworks, and real pilot projects that combine agents with CRM/ERP systems and retrieval-augmented generation (RAG) for smarter reporting. Businesses are testing agents

Short summary AI agents — autonomous, multi-step AI that can use tools (CRMs, calendars, databases, reporting systems) — have moved from lab demos to real business use. Across 2024–2025 more vendors and low-code platforms released agent frameworks that make it practical to run agents in production for sales, customer service, and automated reporting. Businesses are

Short summary AI “agents” — software that can act autonomously across apps, read data, and complete tasks — are no longer just demos. Businesses are using agents to qualify leads, draft and send outreach, update CRMs, generate recurring reports, and even triage customer issues. These agents combine language models, connectors to SaaS tools, and simple

AI agents move into production — what business leaders should do now Summary AI “agents” — autonomous workflows that can read your data, call tools, and complete multi-step tasks — are no longer just research demos. Across industries, companies are building agents to handle sales outreach, compile operational reports, route customer requests, and orchestrate repeatable

Summary AI “agents” — autonomous software that can carry out tasks, follow multi-step workflows, and interact with apps and people — moved from research demos into real business use in 2024. More sales, service, and operations teams are piloting agents to qualify leads, prep sales outreach, run recurring reports, and automate routine approvals. Why this

Short summary Autonomous AI agents — software that can plan, act, and complete tasks with little human direction — moved quickly from research demos to real business pilots in 2024. Companies are now using agents for things like lead qualification, automated meeting follow‑ups, compiling sales and financial reports, and orchestrating multi‑step workflows across apps. Why

Quick summary Autonomous AI agents — software that can use tools, call APIs, and act on goals with minimal human prompting — have moved from labs into real business pilots. Companies are using agents to auto-qualify leads, assemble weekly performance reports, automate order-to-cash steps, and run routine ops checks. That means repetitive work is being