Ron Mitchell

Short summary AI “agents” — autonomous software that plans, acts, and follows up across apps — moved rapidly from demos into practical workplace use over the last few years. Instead of one-off chat answers, these agents can run multi-step workflows: qualify leads in your CRM, build weekly performance reports, triage support tickets, or even handle […]

Short summary A new wave of enterprise-ready AI agents — systems that can carry out multi-step tasks, connect to your data, and act with minimal human input — is moving from labs into real business use. These agents can research prospects, draft outreach, update CRMs, and generate regular performance reports without manual handoffs. That makes

Quick summary Major cloud and AI vendors have moved AI agents — autonomous, multi-step assistants that act on behalf of users — from experiments into enterprise-ready tools. Organizations are already using agents to qualify leads, update CRMs, draft and send follow-ups, and generate recurring sales and performance reports. The results: faster workflows, fewer manual errors,

Story summary AI agents—software that can autonomously carry out tasks by combining reasoning, web access, and your data—are no longer just demos. Over the past year we’ve seen companies put agents into production to run repeatable business workflows: qualify leads, book meetings, generate and deliver routine reports, triage customer requests, and automate follow-ups. Why this

Quick summary In the past year, a clear shift moved generative AI from “helpful demo” to day-to-day work: autonomous AI agents are now being combined with AI-powered reporting and BI systems to automate end-to-end tasks — from lead triage and follow-up to compiling weekly sales and inventory reports. Instead of only giving suggestions, these systems

Short summary AI agents — autonomous, goal-oriented software powered by large language models — are no longer just lab experiments. Over the past year we’ve seen major cloud providers and enterprise software vendors ship “copilot” and agent frameworks that let businesses automate multi-step tasks: researching leads, drafting outreach, triaging support tickets, reconciling invoices, and updating

Summary AI agents — software that can take actions, make decisions, and talk to systems for you — are no longer just prototypes. Over the last 18 months we’ve seen major vendors and startups make agents easier to build and connect to CRMs, ERPs, and reporting tools. That means businesses can automate end-to-end tasks like

Quick summary AI “agents” — autonomous assistants that can fetch data, run tasks, and act on rules — are moving from experiments to real business use. Instead of one-off prompts, companies are wiring agents into CRMs, reporting stacks, and workflow tools so they can monitor leads, generate insights, and trigger actions automatically. Why this matters

Story summary AI agents — software that can perform multi-step tasks on your behalf (think: qualify leads, book demos, update CRM records, draft follow-ups) — have shifted from experiments to practical deployments. Over the past year, more vendors and tools have made it simple to connect autonomous agents to email, calendars, CRMs, and business data.

Quick summary AI agents — autonomous, task-focused AI that can connect to apps, pull data, and take actions — jumped from labs into real-world use in 2023–24. Low-code platforms, better data retrieval (vector databases), and “plug-in” integrations now let businesses run agents for sales outreach, customer follow-up, and automated reporting without months of engineering work.