Ron Mitchell

The story in one line AI “agents” — autonomous AI tools that can fetch data, take multi-step actions, and talk back to users — moved from demos to real business work in 2024. Major vendors and developer frameworks released enterprise-ready features (model access, integrations, orchestration and governance), and companies are starting to deploy agents for […]

Quick summary AI “agents” — software that can act on instructions, connect to systems, and carry out multi-step tasks — are moving from experiments into real business use. Instead of just suggesting answers, modern agents can pull CRM data, generate reports, update records, and follow up with customers automatically. That shift is making automation more

Short summary AI “agents” — autonomous, task-oriented AI systems that can research, draft, execute workflows and talk to other software — are moving from developer experiments into everyday business use. Sales and operations teams are using agents for prospect research, meeting prep, automated outreach drafts, and AI-powered reporting that pulls data from CRMs, finance systems,

Quick summary AI “agents” — autonomous or semi-autonomous AI programs that act on your behalf across apps — moved from proof-of-concept demos into real, money-saving business tools in the last 12–18 months. Companies are already using agents to qualify leads, summarize customer interactions, update CRMs, and generate recurring management reports with less human time involved.

Quick take AI “agents” — models that can act autonomously across apps, trigger workflows, and learn from feedback — are moving fast from experiments to real work. Instead of only answering questions, modern agents can schedule meetings, update CRMs, run sales outreach sequences, and generate recurring performance reports. For business leaders, that means faster operations,

Quick summary AI agents — autonomous, multi-step AI assistants that can act on your systems, fetch and summarize data, and execute workflows — are moving from demos into real business use. Over the last year, major cloud vendors and startups have released toolkits and platforms that make it easier for non‑developers to build and deploy

Quick summary Major cloud vendors and AI startups have pushed AI “agents” — goal-driven bots that connect to data, apps, and APIs — from labs into real business use. These agents can read your CRM, pull sales reports, qualify leads, summarize meetings, and trigger follow-up actions without a developer for every change. Improvements in retrieval-augmented

Short summary AI agents — autonomous workflows powered by large language models and tool access — are moving out of labs and into everyday business systems. Instead of a human doing each step, an agent can read your CRM, draft outreach, schedule calls, update records, and generate a weekly pipeline report — all with less

Short summary AI agent builders and “custom GPTs” have made it much faster and cheaper for businesses to create purpose-built assistants that read your documents, pull CRM data, and trigger workflows — often without a full engineering project. Instead of one-size-fits-all chatbots, companies can now spin up agents that handle sales outreach, generate weekly reports,

AI story (short summary) AI agents — software that can take multi-step actions (reach out to leads, update your CRM, run reports, escalate issues) — have moved from lab experiments into real business use. Major vendors and open frameworks now offer no-code and low-code agent builders, plus connector libraries for CRMs, calendars, and reporting tools.