Ron Mitchell

Quick summary AI agents — autonomous software that can read, act, and integrate across apps — are moving from experiments to everyday business tools. Major cloud and AI vendors have made it easy to connect agents to CRMs, email, ticketing systems, and data warehouses. That means you can now create automated workers that do things […]

Summary AI agents — autonomous, task-focused AI that can read documents, run workflows, and talk to systems — are no longer just experiments. Over the last 12–18 months, businesses have moved from proofs-of-concept to running agents in everyday sales, support, and operations tasks. That shift is driven by better models, easier integrations (APIs and connectors),

Quick summary In the past year we’ve seen a surge in tools that let AI act like a digital assistant — not just answer a question, but complete multi-step tasks. Platforms and frameworks (think agent frameworks, Copilot/assistant builders, and open-source agent projects) make it easier to connect LLMs to your CRM, calendar, databases, and reporting

Summary AI agents are software assistants that can act on your behalf: reading data, running workflows, sending emails, updating CRM records, and creating reports — often by chaining tools and APIs. Over the last year vendors and startups have moved beyond chat-only models and shipped agent features that connect directly to enterprise apps, making automation

Short summary AI agents — autonomous workflows driven by large language models — are moving out of research labs and into real business operations. Organizations are now using agents to qualify leads, run follow-ups, generate routine reports, automate billing and procurement tasks, and triage customer requests. Improvements in model accuracy, retrieval-augmented generation (RAG), connectors to

Big picture (the story) – Over the last 12–18 months, “AI agents” — LLM-powered assistants that can read your systems, take multi-step actions, and follow up autonomously — have moved from demos into production pilots across sales, customer service, and finance. – You’re seeing this in two places: major cloud platforms and a new wave

The story in one line AI “agents” — autonomous AI systems that can read your data, run tasks across apps, and carry out multi-step workflows — are moving from experiments into real business use. Better tooling (model APIs, agent frameworks, and vector databases), plus vendor copilots and enterprise integrations, means companies can now deploy practical

AI agents are moving from demos to day-to-day work. Over the last year, major AI platforms and vendors have shipped agent toolkits and orchestration tools that let businesses automate multi-step tasks—think lead qualification, meeting follow-ups, or creating weekly sales reports—without a developer standing over every workflow. Why this matters for businesses – Faster outcomes: Agents

Quick summary AI “agents” — autonomous workflows that connect a language model to your apps (CRM, email, calendar, BI) — have moved beyond demos into real business use. Companies are using agents to qualify leads, draft personalized outreach, prepare meeting briefs, and automate routine reporting. The result: faster sales cycles, fewer manual errors, and clearer,

The story in one line Autonomous AI agents — software that can plan, act, and follow up with little human hand-holding — are moving from demo projects into real business use. Teams are using agents to research leads, draft and send personalized outreach, update CRMs, and generate real-time reports that drive faster decisions. Why this