Ron Mitchell

Summary AI agents — autonomous, task-focused systems that can plan, act, and follow up — have moved well beyond demos. Organizations are using agents to qualify leads, draft and send follow-up emails, automate parts of customer service, and compile weekly performance reports. These tools combine large language models, connectors to your apps (CRM, calendar, ERP), […]

Quick story Autonomous AI agents — programs that can carry out multi-step tasks on their own — moved quickly from demos into real business pilots. Tools inspired by Auto-GPT and agent-capable platforms (think plugins, API-based assistants and task orchestration layers) are now being used to research leads, extract and clean data, draft outreach, and assemble

What happened A new wave of autonomous AI agents — tools that can research leads, draft outreach, schedule meetings, and update CRMs with little human direction — has moved from lab experiments into real business tools. Vendors and open-source frameworks (think agent platforms built on modern LLMs and app connectors) are making it easy to

The story Over the past 12–18 months we’ve seen AI agents — software that acts on your behalf, connects to internal systems, and completes multi-step tasks — move out of labs and into mainstream business tools. Major vendors have embedded agent features into CRMs, collaboration platforms, and reporting tools, and a growing number of companies

Summary AI agents — autonomous, task-focused AI that can research, take actions, and connect to systems — have moved from experiments into real business use. Over the last 18–24 months vendors and platform providers have made it easier to build agents that plug into CRMs, calendars, and reporting systems. That means businesses can delegate routine

Quick summary AI agents — autonomous, task-focused AI that can act across apps — are no longer just experiments. Companies are moving pilots into production to automate repetitive work: qualifying leads, updating CRMs, generating weekly sales reports, scheduling follow-ups, and routing exceptions to humans. The result is faster decision-making, cleaner pipeline data, and more time

The story (short) AI “agents” — software that can act autonomously across apps, pull data, and complete multi-step workflows — moved from research labs into mainstream business tools in 2023–24. Major cloud and AI vendors released agent frameworks and no-code builders that let companies create assistants that schedule meetings, enrich CRM records, generate reports, and

Why this story matters now – Over the last 18–24 months, so-called AI agents — purpose-built, persistent AI assistants that can connect to systems, run tasks, and make decisions — have moved from research demos into real business pilots. – Companies are using agents to automate repetitive work (sales outreach, lead qualification), speed reporting (automated

Quick summary Autonomous AI agents — small systems that can take multi-step actions (like reading CRM data, drafting follow-ups, and updating records) — moved from research demos into practical tools in 2024. Major AI platforms made agent tooling easier to build and integrate, and businesses are now trialing agents to automate routine processes, generate on-demand

Summary AI “agents” — software that can read, decide, and act across apps and data — have moved from lab demos to real business tools. Today’s agents combine faster models, multimodal inputs (text, docs, images), and easy connectors to CRMs, ERPs, and cloud storage. That means they can do end-to-end work: draft sales outreach, update