Ron Mitchell

Summary Major AI platforms have made it simple for companies to build custom AI agents (sometimes called custom GPTs). These agents can connect to CRMs, help desk systems, databases and reporting tools to do real, practical work: qualify leads, draft outreach, generate weekly sales reports, detect churn risk, and trigger follow-up tasks automatically. Why this […]

Quick summary AI agents—software that can take multi-step actions (think: read your CRM, draft outreach, update records, and schedule follow-ups)—have moved from experiments to real business tools. New no-code platforms, tighter CRM integrations, and better retrieval techniques (so agents can use your company data safely) mean teams can automate parts of sales, support, and operations

The story in one line AI “agents” — autonomous, task-focused AI that can read your data, take actions, and run workflows — have moved from lab demos to practical business use. Over the past year, companies of all sizes are piloting agents to automate outreach, keep CRMs up to date, and generate fast, accurate reports.

Summary Autonomous AI agents — tools that can take actions, not just answer questions — are moving from demos into real business use. Companies are already using agents to triage customer requests, update CRM records, run routine analyses, and create automated reports. That shift is making automation more flexible: instead of one-off scripts, agents can

Big picture: Over the last year the conversation moved from “what if” to “what now.” AI agents — small, goal-focused AI programs that can take actions across apps, pull and synthesize data, and learn from feedback — are moving into real business workflows. Major platforms (enterprise LLMs, orchestration tools, and API integrations) have turned experimental

Quick summary – What’s happening: Over the past year we’ve seen large language models evolve into practical “AI agents” — software that can take multi-step actions (schedule meetings, pull CRM data, draft emails, run reports) instead of only answering prompts. Major model providers and tools now offer agent frameworks and integrations with calendars, CRMs, and

Summary Autonomous AI agents — software that can research, write, act, and report with little human supervision — have moved from experiments into everyday business tools. Today’s agents can qualify leads, draft personalized outreach, schedule meetings, enrich CRM records, and generate campaign or pipeline reports automatically. Improvements in model performance, secure connectors to CRM/email/calendar, and

Quick summary AI “agents” — AI systems that can autonomously perform multi-step tasks across apps (think: run a report, summarize it, and schedule a follow-up) — moved from research demos into real business pilots in 2024. Cloud vendors and startups are shipping tools that let AI act on your data and workflows instead of only

The story in one line AI “agents” — software that can act autonomously across apps (email, CRM, calendars, BI tools) — are moving quickly from lab demos into real business use. Companies are using them to automate repetitive work, generate timely reports, and run sales and operations workflows without constant human direction. Why this matters

AI agents move from demo to day-to-day — what business leaders need to know Summary — the story in plain language Over the past year, “AI agents” and enterprise copilots have stopped being just demos or experiments. Companies are increasingly using lightweight, goal-oriented AI agents to automate routine work: qualifying leads, compiling weekly reports, drafting