Ron Mitchell

Story summary Over the past 12–18 months we’ve moved past the proof-of-concept phase for autonomous AI agents. Big vendors and a growing open-source ecosystem have made it easier to create agents that can read your data, act across apps (CRMs, calendars, ERPs), and execute multi-step tasks with minimal human supervision. Tools for agent orchestration, retrieval-augmented […]

Quick summary AI “agents” — autonomous AI tools that can read your data, draft messages, take actions in apps, and generate reports — are moving from experiments to everyday tools for sales and operations. Big vendors (Salesforce, Microsoft, HubSpot and others) have embedded agent-like features into CRMs and productivity suites, and specialist startups are building

Quick summary AI agents — autonomous, task-focused systems that can read, act, and interact across apps — have moved from lab demos to real business deployments. Over the last 12–18 months vendors and integrators have focused on safer orchestration, CRM and calendar integrations, and reliable data retrieval. That means companies are no longer experimenting for

The story (short) AI agents—LLM-powered systems that can act autonomously across apps and data—moved from demos to real business pilots in 2024. Big vendors and startups shipped agent frameworks and connectors for CRMs, calendars, email, and BI tools. That means AI can now qualify leads, generate follow-up emails, update records, and even produce routine reports

AI story (short summary) AI “agents” — autonomous, task-focused AI that can research, act across apps, and carry out multi-step workflows — have gone from proof-of-concept to real deployments across industries. Major vendors and startups are embedding agent capabilities into productivity and CRM tools, and companies are using them for things like personalized outreach, automated

Summary There’s been a clear surge in practical, enterprise-ready “AI agents” — autonomous or semi-autonomous systems that can act across tools (CRM, email, ERPs, BI) to complete end-to-end tasks. Platform features from major providers and an ecosystem of orchestration tools now let businesses automate complex workflows: qualify leads, update records, generate and distribute reports, and

Why AI agents are the next business productivity frontier Summary — what’s happening AI “agents” — autonomous, task-focused AI that can read data, call APIs, and take actions across apps — are moving from demos into real business use. Organizations are using agents to research leads, draft and send personalized outreach, update CRMs, and assemble

Quick summary In recent months we’ve seen a big push to put AI agents and enterprise copilots into real work — not just experiments. Tools that combine large language models, retrieval-augmented generation (RAG), and workflow automation let businesses automate repetitive tasks, generate faster reports, and support sales and customer service with conversational assistants. Why this

Story summary AI agents — autonomous, multi-step AI assistants that can read data, take actions, and coordinate tools — moved from proof-of-concept to production in 2024–2025. Platforms and “agent orchestration” tools (think low-code builders for multi-step AI workflows) are making it easy for non-engineers to create agents that do things like qualify leads, generate and

Summary AI “agents” — autonomous or semi-autonomous systems that can carry out multi-step tasks (think: qualify leads, pull and summarize reports, or update CRM records without a human clicking every step) — are moving from demos into real business use. Major platforms and vendors are embedding agent capabilities into CRM, productivity suites, and reporting tools,