Ron Mitchell

Short summary Big cloud and AI vendors are pushing programmable AI agents — autonomous assistants that can access your data, run workflows, and act on behalf of users (for example: summarize CRM pipelines, create weekly sales outreach lists, trigger invoices, or update dashboards). These agents combine large language models, data connectors, and automation tools so […]

Quick summary AI “agents” — goal-oriented, multi-step AI assistants built with low-code tools and automation platforms — are moving out of labs and into real business workflows. Companies are using them to qualify leads, draft personalized outreach, handle first-line customer support, and generate routine reports. At the same time, AI-powered reporting tools let non-technical teams

Quick summary AI agents — autonomous, task-focused AI assistants that can read systems, take actions, and learn from feedback — are no longer just experiments. Over the last year we’ve seen major vendors and enterprises shift from pilots to production deployments: sales copilots that draft personalized outreach, virtual reps that qualify leads, and background agents

Short summary AI agents — autonomous software that can read your systems, take actions, and follow multi-step instructions — are no longer an experiment. Over the last 18–24 months we’ve seen large vendors and specialist startups build agents that connect to calendars, CRMs, support desks, and reporting tools. That means the technology can now qualify

Quick summary AI agents — the “copilot” tools that can read your CRM, email, calendar, and dashboards, then act or recommend next steps — have moved beyond experiments. Companies now use them to qualify leads, auto-generate customer follow-ups, and produce timely reports that used to take hours. That shift is making AI a practical tool

Short summary AI “agents” — software that can carry out multi-step tasks by connecting to apps, data, and APIs — are moving from labs into real business workflows. Over the last year we’ve seen toolchains, connectors, and orchestration platforms that make building and governing these agents faster and more reliable. That means companies can automate

Quick summary AI “agents” — software that carries out tasks autonomously by using your systems, data, and business rules — are no longer hype. Major vendors and startups are embedding agent-style features into CRMs, ERPs, and analytics tools so the software can do things like draft personalized outreach, reconcile data across systems, and generate up-to-date

Quick summary Autonomous AI agents — AI that can act across apps, make decisions, and run multi-step workflows — moved from demos to real business pilots over the last two years. Instead of only answering questions, these agents can qualify leads, update CRMs, generate deliverables, and produce recurring reports by calling tools and services on

Quick story Across 2023–2024 we saw a clear shift: large AI platforms and enterprise tools began offering ready-made “AI agents” — virtual assistants that can act, not just answer. These agents can read from your systems (CRM, calendars, email), run multi-step workflows, and trigger actions (create tasks, send emails, generate reports). That change moved AI

Big picture Autonomous AI agents — software that can perform multi-step tasks across apps (research leads, send outreach, update CRMs, schedule meetings, and create reports) — are no longer just demos. Companies are piloting agents inside sales, support, and operations to automate routine work and generate real business outcomes like faster response times, higher lead