Ron Mitchell

Short summary Autonomous AI agents — software that can act, decide, and follow-up on tasks without constant human prompts — are moving from labs into everyday business tools. Recent product releases and pilot programs show agents handling outreach, qualifying leads, scheduling meetings, and even assembling sales proposals. That’s a shift from “AI that suggests” to […]

Quick summary AI “agents” — small, task-focused AI programs that can read your systems, take actions, and coordinate work — are moving from demos into real business use. Companies are using custom agents to qualify leads, automate order processing, generate recurring reports, and run follow-up sequences. The result: faster workflows, fewer manual mistakes, and more

Quick story Autonomous AI agents — software that can plan, act, and learn across tools without constant human direction — moved from research demos into practical business use in the last year. Advances in large models, retrieval-augmented generation (RAG), vector search, and agent frameworks now let companies deploy agents that do tasks like lead research,

Short summary AI agents — autonomous software that can read data, take actions across apps, and carry out multi-step workflows — are no longer just lab projects. Over the last year we’ve seen more enterprise-ready agent platforms and tighter integrations with CRM, calendar, email, and BI systems. That means businesses can automate whole pieces of

Quick summary – Over the last year, autonomous AI agents have gone from labs into live business workflows. These are AI-powered assistants that can take multi-step actions — e.g., read a CRM record, draft a proposal, book a meeting, and update sales reporting — without a human doing every step. – Companies piloting these agents

Quick summary AI agents — autonomous systems that combine language models, tools, and company data to complete end-to-end tasks — are moving out of demos and into production. Across sales, customer service, finance and operations, companies are deploying agents to qualify leads, generate and deliver regular reports, triage support tickets, and automate repetitive workflows. The

Quick summary AI “agents” — autonomous assistants that can run tasks, talk to systems, and take actions — have moved from demos into real business use. Major cloud and AI providers and a wave of low‑code platforms now let companies build agents for things like lead triage, customer follow-ups, meeting scheduling, invoice checks, and automated

Quick summary – Autonomous AI agents and “copilot” features are being embedded directly into CRMs, outreach tools, and analytics dashboards. Instead of just generating text, these agents now take end-to-end actions: draft and send follow-ups, update pipeline stages, build weekly reports, and surface next-best steps. – This shift isn’t just about flash demos. Businesses are

Quick summary AI agents — autonomous, task-focused AI that can act across apps and systems — moved from research demos to real business pilots in the past 18 months. Vendors are baking agent capabilities into “copilot” products and specialist startups are building agents for things like lead qualification, customer follow-up, and automated reporting. Why this

Story summary AI agents — autonomous or semi-autonomous AI assistants that can carry out sequences of tasks, talk to apps, and make decisions — have moved from demos into real business use. Over the last year we’ve seen better integrations with CRMs, low-code platforms that speed deployment, and enterprise-grade models that keep data inside corporate