Ron Mitchell

Summary – What’s new: AI agents — autonomous, multi-step tools powered by large language models — are moving from experiments into real business workflows. Teams are using them for lead research, personalized outreach, meeting scheduling, routine customer replies, and automated reporting. – Why it’s catching on: agents can do repetitive, time-consuming tasks at scale while […]

Quick summary AI “agents” — autonomous assistants that can read your systems, take actions, and generate reports — have shifted from demos to real business use. Low-code platforms, better retrieval-augmented generation (RAG), and built-in CRM/BI integrations mean companies are now deploying agents to handle tasks like lead qualification, customer support triage, scheduling, and real-time pipeline

AI agents are moving into the boardroom — what business leaders should do next Summary of the story Over the last year we’ve moved past AI as a novelty and into AI agents that actually run tasks across apps: pulling data from CRMs, generating status reports, routing leads, and even executing basic workflows. Major platforms

Quick story summary Companies are moving past one-off generative AI experiments and deploying autonomous AI agents that connect to core systems (CRM, calendar, BI, support ticketing). These agents can qualify leads, draft personalized outreach, assemble weekly sales reports from multiple data sources, and triage customer requests — often with little human intervention. Marketplaces and pre-built

The story in brief – Autonomous AI agents — tools that can carry out multi-step tasks, talk to your systems, and act with minimal human direction — moved from labs into real business pilots across sales, finance, and operations. – Companies use agents to draft outreach, run reconciliations, build weekly dashboards, and follow up on

Summary AI agents — autonomous software that uses large language models to read, decide, and act across systems — are no longer just lab experiments. Companies are using them to draft personalized sales outreach, automate parts of customer service, and generate regular business reports that once took analysts hours. These agents can connect to CRMs,

Why AI agents are the next big win for business automation Summary AI “agents” — autonomous, goal-driven AI programs that can act across apps and data — are moving from research demos into real business use. Frameworks like LangChain and consumer projects such as Auto-GPT showed what’s possible, and now major cloud and SaaS vendors

Summary AI agents — autonomous, task-oriented AI that can read data, take actions, and talk to other systems — moved from hype to real deployments this year. Major cloud providers and a wave of startups released enterprise-grade agent platforms and secure connectors, making it easier to let AI handle repeatable work: qualify leads, run daily

Recent story (short): Over the past year major cloud and software vendors have shifted from offering standalone AI models to providing enterprise-ready AI agents and orchestration tools. These agents—autonomous or semi-autonomous software that can research, draft outreach, schedule meetings, update CRMs, and generate reports—are being packaged for business use with stronger security controls and audit

Quick summary AI agents — autonomous, task-focused AI that can act across apps, fetch data, and make decisions — have shifted from experimental demos to real enterprise deployments. Instead of just generating text, today’s agents can qualify leads, update CRMs, run recurring reports, and trigger workflows across systems. That means faster sales cycles, cleaner reporting,