Ron Mitchell

Quick story AI “agents” — autonomous AI assistants that can access tools, fetch company data, and take multi-step actions — have shifted from research demos to real business pilots. Improvements in large language models, tool orchestration frameworks, and cheaper compute mean companies can now build agents that qualify leads, update CRMs, generate reports, and automate […]

Quick summary AI agents — software that can act on your behalf across apps, follow multi-step instructions, and learn from results — are moving from labs into everyday business use. Companies are using agents to run outreach sequences, assemble cross-system reports, triage customer issues, and automate repetitive workflows. That means faster decisions, fewer manual steps,

What’s new AI agents — autonomous, task-focused AI that can take multi-step actions (schedule, qualify leads, generate reports, escalate issues) — are no longer just R&D demos. Big vendors and startups have packaged agent frameworks and connectors that let companies plug them into CRM, email, chat, and BI systems with stronger security and audit trails.

Quick story AI agents — software that can autonomously perform tasks, follow multi-step processes, and interact with systems and people — are finally crossing the gap from experiment to everyday business use. Sales teams are already using agents to draft outreach and manage follow-ups. Finance teams are automating routine reporting and reconciliations. Operations teams are

Quick summary AI agents — autonomous, task-focused AI that can research leads, update CRMs, draft outreach, and generate reports — are moving from experiments into real business use. Vendors and startups have wrapped agent frameworks into tooling that connects to calendars, CRMs, document stores, and reporting systems. The result: teams can cut admin work, speed

Quick story summary Autonomous AI “agents” — tools that can act on behalf of users to complete multi-step tasks — moved from research demos into real business pilots over the past year. Companies are using agents to qualify leads, automate scheduling, pull together weekly reports, and triage customer messages. Rather than a single chat reply,

How AI agents are starting to change sales, reporting, and business automation — and what to do next Summary (what happened) Over the last year major AI platforms have made “AI agents” — autonomous or semi-autonomous AI workflows that can act, fetch tools, and follow multi-step tasks — easy to deploy. These agents can connect

Quick summary – What’s happening: Over the past year major AI platforms and startups have pushed autonomous, multi-step “AI agents” — systems that can plan, execute, and follow up on tasks across apps without constant human prompting. – Why it matters for business: These agents can automate complex workflows (lead qualification, follow-up outreach, weekly reporting,

Short summary AI “agents” — autonomous, task-focused AI that can read your systems, take actions, and return results — are no longer just lab experiments. Over the past year major vendors and SaaS products have embedded agent-style features into CRMs, collaboration tools, and analytics platforms, letting AI do things like qualify leads, run recurring reports,

Quick summary — the story in plain terms – Autonomous AI agents — software that can act on your behalf across apps, run multi-step workflows, and make decisions with minimal human input — have moved from lab demos into real-world business pilots and early production. – Big productivity platforms (think Microsoft Copilot, Google and Salesforce