Ron Mitchell

Quick summary AI agents — autonomous or semi-autonomous software that can carry out multi-step tasks (think: analyze data, write reports, follow up on leads) — are moving fast from research demos into everyday business workflows. Over the last year, major cloud vendors and enterprise software providers have focused on agent-builder tools and “copilot” experiences that […]

There’s been a clear shift: AI agents — autonomous systems that can read, act, and follow up across apps — are moving from demos into real business work. Vendors and open-source tools now let these agents handle tasks like lead outreach, triaging support tickets, compiling weekly reports, and automating approvals. Why this matters for businesses

Summary AI “agents” — software that can act autonomously on your behalf — plus AI-powered reporting are moving fast from prototypes into real business use. Companies are using agents to handle repetitive workflows (scheduling, lead follow-up, data extraction) and using automated reporting tools to turn raw numbers into clear narratives and action items. The result:

Short summary AI agents — autonomous assistants that carry out multi-step tasks across apps — have moved from experiments to production-ready tools. In the last year we’ve seen major platforms and low-code vendors focus on agent orchestration, connectors to enterprise systems, and safer guardrails. That means these agents can do things like qualify sales leads,

Quick story summary AI agents — autonomous programs that use large language models plus connectors to act across apps — have moved beyond research demos. Big vendors (think Copilot-style assistants), open-source agent frameworks, and specialist startups are packaging agents that can run sales outreach, qualify leads, pull and summarize CRM data, and produce recurring reports

Quick summary AI agents — autonomous software that can read data, take actions, and carry conversations — are moving from lab experiments into real business use. More companies are using agents to qualify leads, run outreach sequences, update CRMs, and generate near-real-time sales and performance reports. That means automation that not only speeds up tasks

Quick summary AI agents — autonomous software that can read, reason, and act across apps — are no longer just a demo. More companies are putting agents into real workflows to automate outreach, qualify leads, update CRMs, and generate reports. The result: faster responses, cleaner data, and more consistent follow-up without adding headcount. Why this

Quick summary – Over the last year we’ve seen a big shift: AI agents (autonomous or semi-autonomous software that can read your data, take actions, and carry conversations) are leaving lab pilots and being embedded into real business workflows. – These agents are showing up in sales, customer service, and operations — scheduling follow-ups, drafting

Big picture: Over the last year, AI “agents” — models that can plan, act, and use tools on their own — have moved out of research demos and into real business workflows. Low-code agent builders, integrations with CRMs and cloud platforms, and better connectors for data and reporting mean companies can now deploy agent-based automation

Quick summary AI “agents” — autonomous workflows that combine large language models with data connectors and action tools — have gone from R&D demos to real business pilots. Tools and frameworks such as Auto-GPT, LangChain-style agents, and vendor copilots have made it easier to chain tasks like data lookup, document generation, email follow-up, and CRM