Ron Mitchell

Quick summary AI “agents” — autonomous, tool-using AI that can run tasks end-to-end — have moved from research demos into real business pilots. Using agents, companies are automating lead outreach, qualifying prospects, updating CRMs, and generating real-time sales reporting without handoffs between tools. Why it matters for business – Faster response times: agents can contact […]

Quick summary AI agents — systems that combine large language models with real-time data access, tool use, and task orchestration — are no longer just demos. Over the last 18 months major AI platforms and enterprise tools have added agent-like capabilities (think automated workflows that can read your calendar, query your CRM, pull BI data,

Quick summary – AI agents are autonomous software that combine large language models with tools (CRMs, databases, email, RPA) to complete end-to-end tasks — for example, qualify leads, generate weekly sales reports, or run invoice reconciliations. – Over the last year we’ve seen these agents move out of proof-of-concept demos into real workflows because of

Quick summary Over the past year AI “agents” — software that can act autonomously across apps and data — have moved from proofs-of-concept into practical business tools. Vendors and open-source toolkits now let companies chain models to do real workflows: find leads, enrich CRM records, run cross-system checks, and generate updated sales reports without constant

Quick summary AI agents — systems that can perform multi-step tasks, talk to your apps, and make decisions — have moved from demos into real business use. Major AI and cloud vendors now offer platforms for building “copilots” or autonomous agents that can run workflows end‑to‑end: pull CRM data, qualify leads, update records, generate reports,

Summary Big AI models and agent frameworks have moved from experiments to practical tools. In 2024 we saw major model releases and platform updates (custom GPTs, multimodal models, and agent/plugin ecosystems) that make it easier to build AI agents that can use your apps, fetch data, run workflows, and generate reports — not just answer

Quick summary There’s been a clear shift: autonomous AI agents — systems that can carry out multi-step tasks, call APIs, and orchestrate tools — are moving from experiments into everyday business use. Companies are using these agents to qualify leads, automate outreach, generate sales reports, and run routine back-office workflows without constant human hand-holding. Why

AI agents automating sales and reporting — what leaders need to plan for Why this story matters now AI agents — autonomous, task-focused systems that combine language models, connectors, and automation — have moved beyond lab experiments. Companies are piloting agents to qualify leads, update CRM records, generate weekly sales reports, and trigger follow-up workflows

Short summary AI “agents” — autonomous software that can carry out multi-step tasks (think: find leads, craft outreach, book meetings, and update CRM) — are moving from labs into real business use. Teams are combining large language models, automation tools, and internal data to create agents that do real work without needing a human at

What’s happening AI “agents” — small, autonomous software assistants that can run multi-step tasks, talk to apps and generate reports — are moving from labs into real business workflows. Low-code agent builders and enterprise-ready connectors now let companies create agents that do things like run outreach campaigns, reconcile leads with CRM records, and generate weekly