Ron Mitchell

Quick summary AI “agents” — software that can carry out multi-step tasks on its own — moved from experiments into real business pilots in 2023–24. These agents combine large language models with company data, workflows, and APIs to do things like prospect for leads, generate weekly sales reports, or triage customer requests without constant human […]

Summary AI agents — software that autonomously completes tasks by combining language models, data access, and action tools — have moved from lab demos to real business pilots. Companies are already using agents to qualify leads, summarize customer threads, update CRM records, generate weekly reports, and route exceptions to humans. The result: faster work, fewer

Quick summary Autonomous AI agents — not just one-off chatbots — are moving from labs into real business use. Major platforms and a wave of new tools now let companies deploy agents that act on behalf of teams: they gather data, trigger workflows, draft emails, reconcile transactions, and generate reports automatically. That shift makes AI

Quick story In the past year we’ve seen a fast shift: “AI agents” — like custom conversational bots and task-runner agents — moved from demos into real business tools. Major platforms now let companies build, publish, and connect agents to internal systems (CRMs, databases, calendars). That means an agent can do multistep work: qualify leads,

What’s happening – AI “agents” — software that combines large language models with tools, connectors, and decision logic — are moving from research demos into real business use. – Low-code agent builders and orchestration frameworks (think LangChain-style patterns and vendor toolkits) make it possible to connect models to your CRM, spreadsheets, BI tools, and ticketing

Quick summary AI agents — autonomous, task-focused assistants that can read your systems, take actions, and talk to people — are no longer just experiments. Over the past year we’ve seen major vendors and startups push agents into real business apps: they can draft outreach, pull live sales metrics, open tickets, and summarize meetings automatically.

Hook: Autonomous AI agents — not just chatbots — are now being used in real business workflows: prospecting, quoting, reporting, and routine approvals. That shift changes how work gets done. What’s happening – Over the last 12–18 months we’ve seen AI agents evolve from research demos into enterprise-ready tools. These agents combine large language models

AI agents — autonomous AI that can take actions, access apps, and run workflows — have stopped being just experiments. Over the last year, major platforms and cloud vendors have made agent builders and integrations easier to use. That means businesses can now deploy agents to qualify leads, triage customer requests, and generate regular reports

Hook If you’ve seen more references to “agents” and “Copilot” in vendor roadmaps, you’re not imagining it. Over the past year the AI market shifted from single‑query models to agent-style assistants that can act, chain steps, call tools, and run business processes. That change matters for every leader who cares about efficiency, sales growth, and

The story (short) AI agents — autonomous or semi-autonomous AI assistants that can carry out sequences of tasks — have stopped being just a tech curiosity. Across industries they’re being used to automate sales outreach, generate recurring business reports, qualify leads, and run routine back‑office workflows. Companies are combining agent frameworks with retrieval-augmented generation (RAG)