Ron Mitchell

Summary AI agents — autonomous, task-focused AI that can read your data, call APIs, and take actions — have moved from labs into real business use in the past year. Companies are using agents to qualify leads, automate complex approval workflows, refresh dashboards, and run recurring reporting. Instead of a person copying and pasting between […]

Quick summary – Big tech and enterprise software vendors are embedding AI agents directly into business apps (think Copilot in Microsoft 365, built-in assistants in CRMs and BI tools). These agents do more than answer questions — they can pull data from systems, generate reports, draft emails and proposals, and trigger automated workflows across apps.

Short summary There’s a fast-growing wave in AI: practical, enterprise-ready AI agents that can run multi-step workflows, talk to company systems, and act semi-autonomously. Instead of one-off chat answers, these agents can qualify leads, create routine reports, open tickets, and trigger follow-up tasks—across CRM, spreadsheets, and BI tools. Why this matters for businesses – Faster

Quick summary AI “agents” — systems that can autonomously perform multi-step tasks (think: read data, call APIs, update systems, and produce a report) — moved this year from proofs-of-concept into real business pilots. Teams are already using them for things like lead triage, invoice reconciliation, routine reporting, and first-line customer responses. Why this matters for

Quick summary Autonomous AI agents — systems that can perform multi-step tasks (like qualify leads, build reports, or coordinate teams) — are no longer just experiments. In 2023–24 the market shifted: platforms and enterprise “copilot” integrations made it easier to embed these agents into everyday workflows. More companies are using agents to automate repetitive work,

Summary AI agents — autonomous systems that combine large language models with tools, memory, and connectors to apps — are moving quickly from experiments into real business use. Over the past year cloud vendors and enterprise software teams have shipped agent frameworks and pre-built connectors that let these agents read your CRM, pull data from

Short summary AI agents — small, focused systems that use large language models plus automation (connectors, APIs, RPA) to perform end-to-end tasks — moved rapidly from labs into real business use in 2023–2024. Companies now use them for things like prospect research, lead qualification, automated reporting, and first-pass customer triage. The result: faster workflows, more

What’s happening – Over the past year vendors and startups have shifted AI agents from experiments to production-ready tools. Modern agents can connect to CRMs, calendars, document stores, and ticketing systems to take actions (book meetings, qualify leads, run reports) — not just answer questions. – Companies are using these agents to automate repetitive sales

Quick summary Major AI platforms and enterprise tools are moving from demos to day-to-day work: “AI agents” — autonomous, task-focused AI that can fetch data, take actions across apps, and generate outputs — are now embedded in productivity suites and stand-alone tools. That shift makes it practical (and affordable) for teams to automate routine work

Big picture summary AI agents — software that can act autonomously on your behalf (for example: read your CRM, draft outreach, schedule follow-ups, and update reports) — are moving from R&D labs into everyday business tools. Over the last year, cloud and AI vendors have released easier ways to build custom agents that safely connect