Ron Mitchell

Quick summary AI “agents” are the next wave of business AI: lightweight, autonomous workflows built on large language models that can read data, act across apps, and complete multi-step tasks without human micromanagement. Think of them as digital assistants that can qualify leads, generate weekly reports, triage support tickets, or update CRM records — then […]

Quick summary AI “agents” — software that can act autonomously to complete tasks (research leads, schedule meetings, generate reports, route tickets) — moved from labs into real business pilots in 2024. Large vendors and open-source frameworks made it easier to build multi-step agents that connect to CRMs, calendars, and data stores, so companies can automate

Short summary AI “agents” — autonomous systems built on large language models that can access tools, databases, and apps — moved from experiments into mainstream business use in 2024. Vendors and startups added agent features to CRMs, help desks, and analytics platforms so agents can perform multi-step tasks: enrich leads, triage tickets, pull data, generate

Quick summary AI “agents” — autonomous assistants that can read your systems, draft emails, run analysis, and take actions — have moved from proof-of-concept experiments into real business use. Over the past year we’ve seen more tools and integrations that let these agents connect to CRMs, databases, and reporting stacks safely and at scale. That

Quick take Autonomous AI agents — systems that complete multi-step tasks across apps (CRM, email, calendar, ERP) — have moved from lab experiments to real business deployments. Companies are using them to qualify leads, update pipelines, generate reports, reconcile invoices, and even draft and send personalized outreach. The result: faster work, fewer errors, and more

Story pick (quick context) Autonomous AI agents — AI tools that can act across apps, pull data, write messages, update systems, and trigger automations — are moving beyond labs and single-team pilots into real business workflows. Companies are using them to draft outreach, enrich CRM records, generate and distribute reports, and even complete routine operational

Summary AI agents — autonomous software that can act on your behalf, pull data, and complete tasks — are moving fast from lab demos into real business work. Sales teams are using agents to draft and personalize outreach, operations teams are automating recurring reports and approvals, and service teams are triaging customer issues before a

Quick summary AI “agents” — software that can take multi-step actions on its own — have moved from labs into real business tools. Over the past year vendor platforms and startups have pushed agent frameworks that can book meetings, qualify leads, fetch and summarize data, and run routine processes without constant human prompting. Why this

AI story (short): AI agents — autonomous workflows powered by large language models that can call APIs, use tools, and take multi-step actions — have moved from experiments into practical business use. Companies are using agents to automate lead qualification, generate regular sales and operational reports, run data-cleaning tasks, and handle first-line customer support. The

Big story in a sentence Autonomous AI agents — small, goal-directed AI programs that can run tasks, pull data, and act across apps — are moving from demos into real business use. Major cloud vendors and startups are embedding agent features into CRMs, scheduling tools, and reporting stacks, and companies are starting pilots to shave