Ron Mitchell

Big picture This year we’ve moved past the “wow” phase of generative AI. Instead of isolated demos, more companies are putting AI agents into real sales, operations, and reporting workflows. These are not just chatbots — they’re task-oriented agents that can qualify leads, update CRMs, generate client-ready reports, and trigger downstream automation. Why this matters […]

Summary AI agents — autonomous, task-focused AI that can read your systems, take actions, and follow up — are no longer just lab experiments. Advances in large language models, cheaper compute, better connectors to CRMs and databases, and ready-made agent frameworks mean companies can now deploy AI agents that handle real work: qualifying leads, drafting

Story summary AI agents — autonomous, task-focused AI that can access tools, databases, and workflows — have moved from demos and lab experiments to real business pilots. Advances in retrieval-augmented generation (RAG), tool integration, and multi-step orchestration mean these agents can now fetch internal data, run queries, generate reports, and trigger actions across apps with

Quick summary AI “agents” — autonomous workflows powered by large language models — are moving from demos to real work. Companies are increasingly connecting agents to CRMs, data warehouses, scheduling tools, and BI systems so the agents can fetch data, draft outreach, auto-generate reports, and even complete routine approvals. The result: less time on admin,

Quick summary – What’s happening: Over the past year businesses have moved past one-off AI pilots and are rolling out AI agents and copilots that do real work — from drafting personalized outreach to generating operational reports and automating routine approvals. – Why it matters for business leaders: These agents shorten cycles, reduce repetitive work,

The story (short) Across 2023–24 we saw a clear shift: AI moved from chat-only assistants to autonomous, connected agents that can act across apps — think a virtual assistant that reads your CRM, pulls numbers from your ERP, and drafts a monthly sales report without back-and-forth. Major platform moves (custom GPTs, copilot-style connectors, and AI-powered

Quick update: custom AI agents just crossed a usability threshold. Platforms from major AI providers and open frameworks now make it easy to build lightweight agents that connect to your CRM, spreadsheets, reporting tools, and calendar — and act autonomously on routine business work (drafting outreach, pulling monthly reports, triaging tickets, scheduling follow-ups). Why this

Quick summary AI agents — software that can act autonomously across apps (think: read emails, update CRM records, generate reports, and schedule follow-ups) — are moving from experiments into real business use. Companies are using agents to automate repetitive sales tasks, keep reporting current, and act as “always-on” assistants that help teams move faster. Why

Quick summary Over the last year we’ve moved past “wow” demos: AI agents — autonomous systems that combine LLMs, tool use, and data access — are being put into real business workflows. Companies are using agents to triage customer issues, auto-generate and distribute sales reports, run outreach sequences, and coordinate cross-team tasks. The result: faster

Quick story: Autonomous AI agents — not just chatbots — are moving into the mainstream. Advances in large models, memory, tool/plugin integrations, and low-code agent frameworks mean businesses can now build AI “agents” that act on behalf of teams: research leads, qualify prospects, update CRMs, run performance reports, and even coordinate calendar scheduling. Early adopters