Ron Mitchell

Quick summary Enterprise “AI agents” — task-focused AI assistants that act across apps and data — moved from demos into real business pilots in 2024. Low-code agent builders, better connectors to CRMs and warehouses, and cheaper large language models have made it practical for sales, ops, and finance teams to automate routine work, produce faster […]

Short summary Autonomous AI agents — systems that can carry out multi-step tasks on their own using LLMs, data retrieval, and integrations — are no longer just research demos. In the past year we’ve seen agent frameworks and orchestration tools mature, plus more plug-and-play integrations with CRMs, reporting tools, and RPA. That makes it realistic

Quick story – Over the past 12–18 months we’ve seen a big shift: companies are moving from experimenting with chatbots and models to deploying autonomous AI agents and low‑code agent builders that connect directly to CRMs, ERPs, knowledge bases, and reporting systems. – These agents don’t just answer questions — they can run outreach sequences,

Quick summary AI “agents” — autonomous tools built on large language models that can read your data, take actions, and learn from outcomes — went from experiment to enterprise staple in 2024. Low-code agent builders and tighter integrations with CRMs, calendars, and data warehouses mean non‑technical teams can deploy agents for tasks like lead qualification,

Quick summary AI “agents” — autonomous AI assistants that can access tools, databases, and apps to complete tasks — are no longer just demos. With improved models, tool integrations, and retrieval systems, companies are automating end-to-end work like lead qualification, quote generation, and automated reporting. The result: faster decisions, fewer manual updates, and clearer, faster

Short summary AI “agents” — autonomous programs that watch data, make decisions, and act (like drafting messages, scheduling, or updating systems) — are no longer just experiments. Over the last year we’ve seen toolkits, integrations, and SaaS platforms make agents reliable enough for everyday business tasks: sales outreach, customer support triage, meeting follow-ups, and automated

Why this matters right now AI “agents” — autonomous assistants that can read your systems, run tasks, and take next steps on their own — moved from labs into real business pilots in 2024 and are accelerating across sales, operations, and reporting. These agents can: – Monitor dashboards and trigger updates or alerts – Draft

Quick story summary Major AI platforms pushed easy-to-build, enterprise-ready AI agents in 2024. Vendors from OpenAI to Microsoft and several startups shipped tools that let teams create purpose-built assistants (sales assistants, finance bots, HR helpers) and connect them to internal systems. That shift makes it practical — and affordable — to automate routine work, generate

Short summary AI “agents” — autonomous or semi-autonomous software that can run tasks, pull data, and interact with tools — are moving out of demos and into real business use. Teams are using agents to automate repetitive work (like lead qualification, meeting prep, and recurring reports), stitch together data from multiple systems, and surface action-ready

Short summary AI “agents” — autonomous, multi-step AI workflows that can read data, take actions, and talk to systems (CRM, email, dashboards) — have shifted from lab demos to real business pilots. Over the past year organizations have started using agents to qualify leads, auto-update CRMs, generate executive reports, and flag anomalies in performance data.