Ron Mitchell

Quick summary AI agents — customizable, semi‑autonomous assistants that can follow multi‑step workflows — are suddenly practical for everyday business work. Major vendors now make it much easier to build tailored agents that connect to CRMs, BI tools, calendars and internal docs. That means companies can automate follow-up, generate timely reports, and take routine decisions […]

The story (quick summary) Businesses are accelerating use of AI agents — not just chatbots, but intelligent assistants that connect to internal systems, automate processes, and generate business reports. Companies are pairing these agents with retrieval-augmented generation (RAG) and vector databases so the agents can answer specific, up-to-date questions from your own data (CRM, contracts,

Short summary AI “agents” — autonomous, workflow-driven AI that can read systems, take actions, and follow goals — are rapidly being embedded into CRM and sales tools. Major vendors and startups are adding agent features that can qualify leads, draft personalized outreach, update records, run follow-up tasks, and generate real-time reports without constant human prompts.

Summary AI agents — autonomous, task-focused systems that can read, act, and report — are moving from tech demos into real-world business use. Companies are now wiring agents into CRMs, help desks, and BI tools to automate repetitive work: qualifying leads, updating records, generating sales reports, and routing customer issues. The shift isn’t about replacing

Quick summary AI “agents” — autonomous, goal-driven AI tools that can read, act, and loop on tasks — have moved from research demos to real business pilots. Major platforms and startups now offer agent frameworks that connect to CRMs, calendars, email, and reporting systems. That means businesses can automate not just single tasks, but whole

Quick summary AI “agents” — autonomous, multi-step AI tools that can read, decide, and act across apps — moved from research demos to real business pilots in 2023–24. Companies now use agents for tasks like prospecting, scheduling, triaging support tickets, and generating recurring reports. The shift isn’t just about smarter chatbots; it’s about AI taking

Summary AI “agents” — autonomous or semi-autonomous AI programs that can take actions across apps — are rapidly moving out of labs and into real business workflows. Today you can train an agent to draft outreach, enrich CRM records, build a weekly sales report, or automate a parts-order workflow without hand-coding every step. Startups and

Quick summary AI “agents” — small, goal-oriented systems that combine large language models with data tools and APIs — are moving from experiments into day‑to‑day business use. Instead of a person running searches, copying data, and making decisions step by step, an agent can autonomously gather information, update your CRM, draft an email, or generate

Big picture Over the last year vendors have moved AI agents from demos into tools businesses can actually use. Low‑code builder platforms and “custom agent” features from major providers make it faster to create agents that handle sales outreach, customer support triage, routine reporting, and process automation — without rewriting your core systems. Why this

Quick summary There’s a clear shift right now: AI agents — models that can act autonomously across apps, pull data, and complete multi-step tasks — are moving from labs into day-to-day business use. Vendors and startups have released more robust agent toolkits and integrations, and companies are starting to deploy them for lead qualification, CRM