Ron Mitchell

Quick summary Recent months have shown a clear shift: AI agents — autonomous, task-focused AI that can read systems, take actions, and report results — are moving out of research labs and into real business workflows. Vendors and platforms now make it easier to connect agents to CRMs, ticketing systems, and BI tools so these […]

Quick summary In 2024 we saw a big shift: platforms like OpenAI’s custom “GPTs,” Microsoft’s Copilot Studio, and other agent builders made it easy for non‑developers to create task‑focused AI agents. These agents can connect to calendars, CRMs, spreadsheets, and internal knowledge to automate routine work — from drafting outreach, to generating weekly sales reports,

Short summary AI “agents” — autonomous workflows powered by large language models plus connectors to your apps — are moving from demos into real business use. Instead of a human copying data between systems or writing routine emails, an agent can read your CRM, pull product and pricing rules, send personalized outreach, update records, and

Summary AI “agents” — models that can run multistep workflows, connect to your systems, and act with limited human supervision — have moved from demos into real business pilots. Improved model capabilities, orchestration frameworks, and easy connectors to CRMs and data warehouses mean agents can now do things like draft personalized outreach, update opportunity records,

Quick summary AI agents — autonomous, task-focused systems built on large language models — are moving from R&D demos into everyday business tools. Companies are using them to run follow-up outreach, assemble and clean sales data, generate automated reports, and trigger cross-system workflows without constant human supervision. The result: faster decisions, fewer manual steps, and

Short summary In the past year we’ve seen AI agents — autonomous software that can follow multi-step instructions, talk to apps, and make decisions — move out of labs and into real business workflows. Instead of just generating text, today’s agents can pull data from your CRM, run a numbers check, create a customer summary,

A growing wave of companies are moving beyond pilots and putting AI agents into everyday workflows — handling tasks like customer triage, sales outreach, invoice processing, and automated reporting. These “agents” combine large language models with connectors to your data and tools, so they can act (not just advise): pull a CRM record, draft an

Quick summary AI “agents” — autonomous, multi-step AI workflows that can fetch data, interact with systems, and complete tasks — moved from experiments to real-world tools in 2024. Companies are using agents for things like personalized sales outreach, automated invoice processing, smart reporting, and follow-up workflows that used to require several people. Why this matters

Quick summary Businesses are increasingly using autonomous AI agents — LLM-powered “bots” that can plan, act, and iterate on tasks — not just for chat but for real workflows: personalized sales outreach, end-to-end customer triage, automated reporting, and back-office process automation. Early deployments show meaningful wins: faster reports, fewer manual handoffs, and higher sales response

Story summary AI agents — autonomous assistants built on large language models plus tools and data — have moved beyond lab demos into real business use. Instead of one-off chatbots, companies are now deploying agents that can act across systems: triaging support tickets, drafting and sending personalized sales outreach, reconciling invoices, and assembling recurring business