Ron Mitchell

Quick summary Leading AI platforms are no longer just about chatbots or single-query answers. Over the past year, vendors have shipped agent toolkits, integrations, and APIs that let software act autonomously across systems — scheduling meetings, qualifying leads, generating and emailing sales reports, or triggering follow-ups. In plain terms: AI can now execute multi-step business […]

What’s happening – Over the past year we’ve seen a big shift: AI agents — small, goal-focused systems that can access tools, talk to apps, and act on behalf of users — are moving out of experiments and into real business work. – Companies are using agents to automate sales outreach, run routine reporting, enrich

AI agents move from experiment to enterprise — what business leaders need to know Summary (quick read) AI “agents” — autonomous software that can plan, act, and use tools like calendars, CRMs, and reporting systems — have moved beyond lab demos and are becoming practical business tools. Over the past year we’ve seen platforms add

AI agents are moving from experiments to everyday business tools — here’s what that means for you Summary of the story AI “agents” — autonomous, task-focused systems that use large language models plus tools (calendars, CRMs, databases, APIs) — are no longer just lab experiments. Over the last year many vendors and enterprises have moved

Quick summary AI agents — autonomous, task-focused AI that can use tools, access data, and act on your behalf — are moving from demos into real business use. Companies are now using agents to run sales outreach, enrich CRM records, generate recurring reports, and handle routine approvals. Advances in long-context models, tool integration, and secure

Quick summary AI “agents” — autonomous assistants that can research accounts, draft and send outreach, update CRMs, and summarize meetings — have moved from demos into real pilot programs at many companies. Instead of asking a human to perform each step, businesses now give agents a goal (eg, qualify 50 leads) and let the agent

The story (short summary) AI “agents” — autonomous software that can carry out multi-step business tasks with little human direction — moved from research demos into real business pilots over the last 12–18 months. Tools and frameworks such as Auto-GPT-style agents, LangChain workflows, and vendor-built agents inside CRMs and productivity suites are letting companies automate

Quick summary AI “agents” — software that can act on your behalf by reading data, calling tools, and executing tasks — have moved beyond demos. Over the last 12–18 months we’ve seen vendors and platforms ship low-code agent builders, secure connectors to CRMs and ERPs, and better guardrails for data access. That combination makes it

Quick summary AI “agents” — autonomous workflows built on large language models that can read your data, take actions, and talk to other apps — have moved from demos into real, everyday business use. New open-source models, cheaper compute, and tools like vector databases and agent-orchestration libraries have made it practical for sales, operations, and

Quick summary AI “agents” — small, task-focused AI programs that read data, take actions, and talk to systems — are moving out of R&D into everyday business use. Companies are using agents to qualify leads, draft personalized outreach, auto-generate sales reports, and trigger follow-up workflows in CRMs. The result: faster decisions, fewer routine tasks, and