Ron Mitchell

Quick summary AI agents — autonomous, task-focused AI tools that can read your CRM, draft outreach, and generate reports — have moved from experiments to real business use. More teams are using agents to automate lead qualification, create weekly sales reports, and triage customer requests. The result: faster response times, fewer manual errors, and more […]

Quick summary AI “agents” — autonomous workflows that can read, decide, and act across apps — are no longer just research demos. Companies are using them to run parts of the sales process (lead qualification, outreach sequencing, pipeline updates) and to auto-generate recurring reports and executive summaries. That shift is making business AI practical: faster

Short summary Major AI platforms have made it easy for businesses to build custom AI agents — “copilots” that connect to your CRM, knowledge base, and workflows to act on behalf of teams. Instead of one-size-fits-all chatbots, these agents can research prospects, draft tailored outreach, generate automated reports, and trigger approval or fulfillment steps —

Short summary AI agents — software that can take multi-step actions for you (think: research a lead, draft a tailored outreach email, and book a demo) — have moved from experiments into production across sales, operations, and reporting. Major platforms now provide agent frameworks and easier ways to connect them to company data, so teams

Quick summary – Over the past year, agentic AI — customizable, autonomous assistants that connect to email, calendars, CRMs, and internal data — moved from demos into real business use. – Vendors now offer low-code agent builders and “agent marketplaces,” letting teams create role-based assistants (sales rep, finance analyst, customer success) that can qualify leads,

Short summary AI “agents” — software that can carry out multi-step tasks on its own — are moving from labs into real business use. Big vendors and startups now offer low-code tools to build agents that can, for example, pull data from your CRM, summarize customer interactions, draft outreach, and update records without constant human

Summary – What’s happening: Companies are moving from experiments to real deployments of autonomous AI agents — software that can act across apps (CRM, email, calendar, BI tools) to complete tasks end-to-end. Use cases include automated lead qualification, scheduling, running and annotating sales reports, and triaging support tickets. – Why it matters for business leaders:

Quick summary – Over the past year we’ve seen a clear shift: AI agents — autonomous systems that can act on your behalf (qualify leads, schedule meetings, generate reports, follow up) — are moving out of labs and into real business workflows. – These agents combine large language models, retrieval-augmented workflows, and API integrations so

Quick summary Over the past year, more companies have started using AI agents — purpose-built software that combines language models, business rules, and connectors to other systems — to automate real work. These agents can do things like qualify sales leads, assemble weekly performance reports by pulling CRM and BI data, and execute parts of

Quick summary A new wave of enterprise-grade AI agents — systems that can read your data, act across apps, and complete multi-step tasks — is moving into the mainstream. Vendors and startups are shipping connectors to CRMs, ERPs, and cloud storage; they support retrieval-augmented generation (RAG) for secure access to company data; and they include