Ron Mitchell

Short summary Big tech and enterprise software vendors are embedding AI agents and copilots directly into business apps. You’re likely seeing “agent” features in CRMs, help desks, and analytics tools that can draft emails, qualify leads, pull numbers, and even execute routine tasks across systems. Why this matters for business – Faster decisions: Agents can […]

Short summary AI agents — software that can autonomously perform tasks, follow up on conversations, and connect to your systems — are no longer just demos. Over the past year companies have moved from experiments to production: agents are handling routine customer replies, generating weekly sales reports, scheduling follow-ups, and automating parts of the order-to-cash

Quick summary AI agents — software that can act on your behalf, run workflows, and pull together data from multiple systems — have moved from lab demos to practical tools inside CRMs, reporting stacks, and automation platforms. Instead of just answering questions, modern agents can draft outreach, update records, generate executive reports, and trigger follow-up

Story summary Autonomous AI agents — small systems that use large language models to plan, act, and connect to your tools — have moved quickly from demos into real business pilots. Companies are using agents to draft and route sales outreach, automate routine financial reporting, refresh dashboards, and trigger follow-up tasks in CRMs and ERPs.

Quick summary AI “agents” — autonomous assistants that can read your CRM, pull data from spreadsheets, send emails, and create reports — moved from proofs-of-concept into real business use in 2024. Improvements in large language models plus easier integration tools mean businesses can now run agents that coordinate across multiple apps, surface insights, and take

Why this matters now AI agents — autonomous, task-focused AI tools that can read your systems, take actions, and follow rules — have moved from demos into real business pilots. Vendors have added agent features to popular AI platforms, and teams are starting to use them for things like lead triage, CRM updates, repeatable outreach,

Short summary AI agents—small, goal-driven applications that combine large language models with tools like calendars, CRMs, and dashboards—are moving from prototypes into real business work. Companies are using them to qualify leads, update CRM records automatically, generate weekly sales reports, and trigger follow-ups without a person touching every step. Why this matters for business –

Short summary AI agents — software that can act across apps, pull data, and complete tasks with little human instruction — have moved from demos into real business projects. Companies are now using agents to find qualified leads, enrich CRM records, draft personalized outreach, and generate sales and performance reports automatically. This shift isn’t just

Quick summary AI “agents” — autonomous, multi-step software that can plan, act, and follow up — have moved from experiments into everyday business use. No-code agent builders, better connectors to CRMs and data warehouses, and cheaper private LLM options mean teams can now deploy agents to do things like qualify leads, generate weekly dashboards, or

Quick summary AI agents — autonomous, task-focused AI that can read, act, and coordinate across systems — have moved from demos into real business use. Low-code agent builders and integrations (think custom GPTs, Copilot-style assistants, and agent frameworks) let teams automate sales outreach, compile weekly performance reports, and run approval workflows without constant manual oversight.