Ron Mitchell

Quick summary A new wave of AI agents — LLM-powered assistants that can connect to apps, run workflows, and generate outputs without constant human prompting — is making it easier for companies to automate end-to-end tasks and produce smarter, faster reports. These agents can read calendar events, pull CRM data, run queries, update systems, and […]

Summary AI agents — autonomous, task-focused systems that can read your CRM, pull data, and take actions — are moving fast from experiments to real business use. Instead of only answering questions, these agents can qualify leads, update pipelines, build monthly reports, and even trigger follow-ups or orders. The result: faster decisions, fewer manual errors,

Summary AI agents — autonomous systems that combine language models, tool access, and data connectors — are moving from demos into everyday business use. Advances in retrieval-augmented generation (RAG), secure connectors to CRMs and databases, and lightweight orchestration mean agents can now perform end-to-end tasks like prospect qualification, routine reporting, and order follow-up with lower

Summary AI agents — autonomous, task-focused software that can act across apps and systems — are no longer just research demos. Over the past year businesses have accelerated pilots that let agents do things like qualify leads, assemble sales briefs, generate customer responses, and run recurring reports. At the same time, BI tools and data

Story pick AI agents — autonomous software that reads, decides, and acts across apps (email, CRM, calendars, knowledge bases) — are no longer just demos. Over the last 18–24 months they’ve matured from one-off pilots into practical tools that businesses use to automate workflows, qualify leads, and power real‑time sales coaching. Why this matters for

Short summary In the last 12–18 months companies of all sizes have started using AI agents — small, goal-oriented software that can read your data, run tasks, and take follow-up actions — to automate routine work. Instead of a human pulling weekly sales reports, prepping account summaries, or sending personalized follow-ups, an AI agent can

Quick summary A wave of AI agents — smart, task-focused AI that can read your systems, take actions, and learn from results — is moving out of labs and into real businesses. These agents connect to CRMs, ERPs, email, calendars, and BI tools to do things like qualify leads, draft personalized outreach, update records, and

Summary AI agents — goal-directed AI that can read your documents, query systems, and take multi-step actions — have moved from demos into real business use. Major platforms now provide “agent builders” and easy connectors for CRM, cloud storage, and databases. That makes it faster for teams to automate sales outreach, generate timely reports, and

Summary AI agents — software that can act autonomously on your data, tools, and workflows — have moved from lab experiments into real business projects over the last year. Companies are using agents to run sales outreach, generate and update reports, triage customer issues, and automate routine back-office tasks. The result: faster cycle times, fewer

Summary A new wave of AI agents — autonomous, task-focused AI that can research, draft, and act inside apps — is shifting from lab experiments to real commercial tools. These agents can triage support tickets, assemble sales outreach lists, populate reports, and trigger follow-up actions inside CRMs and ERPs. The result: faster execution, fewer manual