Ron Mitchell

Quick summary AI agents — software that can act autonomously across systems (think: find leads, draft emails, update CRM, or generate monthly KPIs) — are no longer just experiments. Companies across industries are putting these agents into production to handle repetitive sales tasks, produce narrative business reporting, and automate cross-system workflows. The result: faster cycle […]

Summary – What’s happening: More companies are deploying AI agents — autonomous or semi-autonomous software that connects large language models to your tools (CRM, ERP, calendar, BI). These agents can draft personalized outreach, update records, summarize meetings, and generate on-demand reports without a human doing every step. – Why it matters for business leaders: These

Quick summary AI agents — software that uses large language models to read, act on data, and call tools — have moved beyond demos. Over the past year many companies have started building agent-driven workflows that do tasks like assembling sales-ready briefs, auto-generating reports, chasing up data, and orchestrating multi-step processes across apps. Why this

Quick summary There’s a clear shift right now: AI agents — autonomous, task-focused AI that can act across apps and systems — are moving from experiments into real business use. Teams are using agents to draft outreach, update CRMs, generate live sales reports, and trigger routine workflows without constant human intervention. This reduces manual work,

Quick summary AI “agents” — autonomous, task-focused AI that can read data, run tools, and take actions — have moved fast from research demos into real business products. Over the past year many vendors and startups have added agent features, plus no-code platforms and connectors that let non‑technical teams link agents to CRMs, email, and

Quick summary AI agents — software that can carry out multi-step tasks and talk to your systems — have moved from demos into real-world use. Companies are now wiring agents to CRM, email, spreadsheets, and BI tools so a single agent can research a lead, draft outreach, log activity, and update dashboards automatically. That means

Short summary AI “agents” — small, goal-oriented AI programs that can act on your behalf (read data, send emails, update systems, book meetings) — are moving from labs into real business workflows. Enterprises and startups are embedding these agents into CRMs, help desks, and reporting pipelines so the software can complete multi-step tasks with little

Quick summary Across industries we’re seeing a surge in AI agents — software that autonomously performs tasks by connecting to your apps, data, and workflows. These agents can draft outreach, update CRMs, run customer research, generate weekly performance reports, and even trigger approvals and follow-ups without waiting for a human to start the process. Why

Quick summary AI agents — autonomous or semi-autonomous software that can complete multi-step tasks (think: research a lead, draft outreach, schedule a meeting, and update your CRM) — are no longer just demos. In 2024–25 we’ve seen major platform vendors and startups add agent frameworks and “Copilot”-style features that let businesses automate complex workflows end-to-end.

Short summary AI “agents” — small, goal-oriented AI programs that can connect to apps, run multi-step workflows, and generate reports — are no longer just a lab novelty. Businesses are deploying agents inside CRMs, analytics tools, and internal chat systems to automate routine sales tasks, generate up-to-date reports, and surface insights that previously required hours