Ron Mitchell

Short summary AI agents — software that can act on your behalf to complete multi-step tasks — are moving from labs into everyday business use. Vendors and open-source projects have made it much easier to build agents that combine language models, company data, and workflows. That means you can now automate complex tasks like lead […]

Quick summary AI “agents” — autonomous or semi-autonomous AI assistants that can read systems, take actions, and follow goals — have moved from demos to real business use. Companies are now wiring agents into CRMs, ERPs, help desks and reporting tools to automate tasks like lead qualification, order updates, compliance checks, and routine analytics. Why

Quick summary Major CRM and workplace platforms (Salesforce, Microsoft, HubSpot and others) are embedding AI agents and generative features directly into sales, marketing and service workflows. These agents can draft outreach, qualify leads, update CRMs automatically, and produce natural‑language reports from live data — reducing repetitive work and speeding decisions. Why this matters for your

Summary AI agents — software that can act autonomously across apps, fetch data, and complete tasks — are moving from pilot projects into real business use. These agents combine large language models, retrieval (RAG) from company data, and simple tool integrations (CRMs, email, reporting dashboards). That mix lets them do things like qualify leads, generate

Quick summary AI “agents” — autonomous systems that can use tools, query data, and act on your behalf — have moved from demos into real business use. Over the last 18–24 months vendors and integrators have added enterprise features: secure connectors to CRMs and databases, audit logs, role-based access, and pre-built workflows for sales, support,

Quick summary AI “agents” — software that combines large language models, rules, and automation to complete tasks end-to-end — are no longer just a tech demo. Over the past year we’ve seen companies put agents into real workflows: qualifying leads, scheduling demos, updating CRMs, producing weekly sales and pipeline reports, and automating routine finance and

Big picture summary AI “agents” — software that acts on your behalf by combining language models, tools, and data access — have moved fast from research demos to real business applications. Over the past year vendors and startups have launched agent frameworks and prebuilt solutions for sales, customer support, finance, and reporting. That means more

Quick summary AI agents — software that uses large language models plus tools to carry out multi-step tasks — are catching on in real businesses. Instead of only answering questions, modern agents can pull CRM data, draft emails, update records, run reports, and even start follow-up workflows. That makes them far more useful for sales,

Quick summary AI “agents” — autonomous, multi-step AI helpers that can read systems, fetch data, and complete tasks — are no longer just experiments. In the last year we’ve seen toolkits and integrations mature so these agents can safely connect to CRMs, databases, and reporting systems. That means businesses can automate routine workflows, generate on-demand

Big picture (the story) Over the last year we’ve seen a clear shift: AI agents — sometimes called “copilots” — are moving out of labs and into regular business workflows. Major platforms (Copilot-style tools, Salesforce Einstein GPT, Google’s agent products) now let software act with some autonomy: qualifying leads, drafting proposals, reconciling data, and producing