Ron Mitchell

Big story in one line Autonomous AI agents — think LLM-based bots that can read your CRM, run reports, send outreach, and close routine tasks without constant human prompting — have moved from prototypes to practical business tools thanks to better models, connectors, and retrieval tooling. Why this matters for leaders – Faster decisions: Agents […]

Quick summary – What’s happening: Over the last year, a wave of product launches and enterprise pilots put AI agents — autonomous, task-focused AI that can act across apps and data — into real business workflows. Vendors and in-house teams are using agents for sales outreach, CRM updates, automated reporting, and operational tasks that used

Big picture No-code and low-code “AI agent” builders (tools that let non‑engineers create autonomous, multi‑step AI assistants) have moved from novelty to practical business tools. These platforms connect LLMs to your CRM, calendars, and reporting systems so an agent can qualify leads, draft proposals, update records, and generate weekly sales summaries — without a full

Quick summary AI agents — autonomous, task-focused AI assistants that can read data, run workflows, and act on systems — moved from experiments to real business use in 2024. Firms are wiring agents into CRMs, BI tools, and automation platforms so the agent can generate sales reports, update records, run follow-ups, and trigger operational tasks

Quick summary There’s a clear surge in interest and tooling for autonomous AI agents — systems that can carry out multi-step tasks (think: read a CRM entry, draft outreach, schedule a meeting, and update records) with minimal human prompting. Major platforms and startups have been building agent frameworks and “agent marketplaces,” making it easier for

Quick summary AI “agents” — autonomous assistants built from large language models plus connectors and business data — moved this year from lab demos into real workflows. Instead of just answering questions, these agents can take actions: pull data from your CRM, draft and send follow-ups, run and summarize reports, and trigger routine processes. That

Summary Over the past year, “autonomous” AI agents — systems that can take multi-step actions with limited human direction — have moved out of demos and into real business pilots. Companies are using agents to run routine sales outreach, generate and validate reports, automate order processing, and triage customer issues. Vendors are packaging agent frameworks

Quick summary Big tech and startups are rolling out “AI agents” — software that can read your data, act across apps, and carry out multi-step tasks with little human prompt. These agents can, for example, qualify leads, draft and send follow-ups, update CRMs, and generate recurring sales reports automatically. Why this matters for business –

Story summary Custom AI agents — think company-specific “GPTs” and low-code agent builders — have moved from proof-of-concept to practical tools for business teams. Over the last year these agents (built with retrieval-augmented generation, connector libraries, and simple orchestration layers) started showing up inside CRMs, BI tools, and workflow platforms. That means businesses can now

Short summary In the past year major cloud providers and startups have pushed AI agents from labs into real business workflows. These are not just chatbots — AI agents can read your internal data, execute tasks across apps (CRM, ERP, email), and generate reports or follow up with customers automatically. Companies are piloting agents for