Ron Mitchell

Short summary 2024 brought a step-change: autonomous AI agents — software that plans, acts, and adapts to complete multi-step tasks — moved from research demos into real enterprise pilots. Platforms and frameworks (think agent builders, vector databases, and retrieval-augmented generation) now let teams automate complex workflows: prospect research, proposal drafting, recurring reporting, and first-line customer […]

Short summary Autonomous AI agents — tools that can act, decide, and run tasks with little human oversight — have moved from demos to real business pilots over the last year. Companies are using them to triage support tickets, qualify leads, generate regular reports, and automate repetitive back‑office work. That shift is making AI less

Summary Autonomous AI agents — software that can plan, act, and interact across apps with little human intervention — moved from labs to real business pilots in 2024 and are accelerating in 2025. Companies are using agents for tasks like prospecting, customer triage, invoice processing, and live reporting. These agents stitch together APIs, CRM data,

Short summary AI agents — autonomous, app-connected assistants that can run tasks, draft messages, and generate live reports — have moved from demos into real business use. Companies are now using them to automate follow-ups, pull together sales and performance reports, and coordinate multi-step workflows across CRM, email, and BI systems. That shift is unlocking

Quick summary Major AI platforms and vendors have been rolling out tools that let businesses build “AI agents” — autonomous apps that can read emails, query databases, run reports, book meetings, and call APIs to complete multi-step tasks. Instead of a person copying and pasting between systems, an agent can act on your behalf across

Quick summary Major cloud vendors and AI startups have moved from showing demos of “autonomous agents” to offering product tools for building them. That means businesses can now create task-specific AI agents that do things like draft sales outreach, assemble monthly reports, qualify leads, or automate multi-step back-office processes — often by connecting to CRMs,

Quick summary There’s been a clear shift in AI: autonomous “agents” — low-code bots that combine LLMs, connectors, and workflows — are moving from prototypes into real business use. Platforms and frameworks now let companies build agents that can read your CRM, pull documents, update records, draft emails, run reports, and even trigger approvals —

Summary AI agents and retrieval-augmented copilots are moving out of labs and into everyday business work. These systems combine large language models with real company data (CRM, spreadsheets, documents) and simple task automation to qualify leads, draft outreach, update records, and generate timely reports — all without a developer on every task. Why this matters

Summary AI agents — software that can plan, act, and use tools (APIs, CRMs, reporting) with little human prompting — are no longer just research demos. Major vendors now offer low-code agent builders and integrations that let teams automate tasks like lead outreach, weekly reporting, ad optimization, and order reconciliation. At the same time, companies

Quick summary Autonomous AI agents — tools that can take multi-step actions across apps, follow-up on leads, and generate reports without constant human prompting — are rapidly moving from experiments into real business workflows. Vendors and startups now offer agents that plug into CRMs, calendars, email, and business intelligence tools to handle tasks like lead