Ron Mitchell

Big idea — what’s happening now AI “agents” — models that can take multi-step actions, call tools, and follow instructions without constant human prompts — have moved from demos into real business workflows. Vendors and open-source frameworks (think agent runtimes, retrieval-augmented generation, and tool integrations) now let these agents connect to CRMs, calendar systems, reporting […]

Quick story Over the last year the biggest change in business AI hasn’t been a new language model — it’s been the rise of autonomous AI agents. Tools and frameworks (from open-source stacks to vendor “Copilot” agents) now let AI perform multi-step work across apps: reading your CRM, drafting outreach, scheduling meetings, generating recurring reports,

Summary AI agents — autonomous, workflow-focused assistants that can use tools, access data stores, and act on your behalf — are no longer just experiments. Businesses are starting to deploy them for real tasks: automating routine customer replies, running sales reporting, extracting insights from large document sets, and orchestrating multi-step processes across apps. Why this

Short summary AI “agents” — autonomous AI tools that act on your behalf (triage leads, update CRM records, schedule demos, generate reports) — are moving from experiments into everyday business use. Major platforms and startups have released agent-building frameworks and plug-ins that make it easier to connect AI to your CRM, calendar, and reporting systems.

Summary Major enterprise software vendors are baking AI agents into everyday tools. Examples include Microsoft’s Copilot in Microsoft 365 and Dynamics, and Salesforce’s Einstein GPT and agent features. These agents can draft personalized outreach, update records in your CRM, triage customer requests, and produce natural‑language, AI‑powered reports from your data. Why this matters for business

Quick summary Major CRM and sales-platform vendors are embedding AI agents into everyday workflows — think Copilot-like assistants that draft outreach, summarize meetings, update records, and generate pipeline reports automatically. These agents combine large language models with connectors to your CRM, calendar, email, and knowledge base so they can act (not just advise). Why this

Short summary AI “agents” — autonomous software that can read, act, and coordinate across tools — moved from labs into real business use in 2024–25. Big cloud and AI vendors shipped agent frameworks and connectors to CRMs, email, calendars, and internal databases. That means an AI can now qualify leads, assemble a sales brief, update

Quick summary AI agents — autonomous workflows built on large language models — have moved from labs into real business use. Cloud vendors and toolmakers now offer agent frameworks that connect LLMs to your apps, data, and calendars so the AI can run multi-step tasks without constant human direction. Companies are already using agents to

Short summary Autonomous AI agents — software that can act, decide, and complete multi-step tasks with little human input — have moved from demos into practical use. In the last year, platform providers and toolmakers have focused on agent frameworks that connect language models to real systems (CRMs, ERPs, BI tools, RPA). That makes it

Summary — what’s happening now AI agents — software that can reason, act on information, and run tasks end-to-end — have moved out of labs and into real business workflows. Instead of just answering questions, modern agents can pull data from your CRM, generate outreach messages, run analyses, update systems, and escalate exceptions to people.