What’s happening Autonomous AI agents — software that can carry out multi-step tasks with little human intervention — are rapidly shifting from lab demos into everyday business use. Advances in language models, agent frameworks, and API integrations mean agents can now handle things like lead qualification, scheduling, data gathering, and routine reporting without constant supervision. […]

Summary AI agents — software that can read, act, and make decisions across apps — are no longer just experiments. In the past year we’ve seen more companies put agents into customer-facing and ops roles: answering customer questions, qualifying leads, updating CRMs, and running routine reports. These agents combine language models, tool integrations (APIs, calendars,

Recent story in brief Over the last year we’ve seen a rapid shift from “chatbots” to practical AI agents — purpose-built, customizable AI assistants that can act on your data, trigger actions, and run multi-step workflows. Vendors like OpenAI and Microsoft made it much easier to build custom agents (think custom GPTs or Copilot Studio),

Quick summary Autonomous AI agents — systems that take multi-step actions (like qualifying leads, updating CRMs, and assembling reports) — have moved from demos into real business tools. Over the last year we’ve seen platforms and vendor bundles that make it easier to connect agents to email, calendars, CRMs and reporting systems. That means companies

Recent news: major AI vendors and enterprise platforms are rolling out purpose-built AI agents that can act inside business systems — scheduling meetings, drafting personalized outreach, pulling data from CRMs and spreadsheets, and producing ready-to-use reports. These agents are more controllable than earlier chatbots: they can follow policies, work with secure connectors, and log actions

A recent wave of product and platform improvements has moved AI agents from experimental demos to practical business tools. Modern agents—built on large language models and connected to company systems—can now fetch CRM data, generate sales outreach, automate routine workflows, and produce near-real-time reports. At the same time, vendors are adding better integrations, monitoring, and

Summary AI “agents” — autonomous workflows that use large language models plus connectors, plugins, or RAG (retrieval-augmented generation) — are no longer just demo-stage toys. Companies are using agents to qualify leads, draft contracts, generate sales reports, and run recurring operational tasks. The result: faster response times, fewer manual handoffs, and cleaner data feeding CRM

What’s happening – A new wave of low-code and no-code AI agent builders from major AI platforms has made it fast and cheap to create task-specific “agents” that act like assistants: they draft emails, pull data, summarize meetings, run reports, and even trigger actions in other systems. – Businesses are moving from experimenting with standalone

Quick summary AI agents — autonomous, connected AI tools that can act on your systems (CRM, ERP, email, reporting dashboards) — are moving from lab experiments into real business use. Companies are using them for things like qualifying leads, generating personalized outreach, triaging invoices, and producing automated weekly reports. The net effect: faster decisions, fewer

Quick summary – Autonomous AI agents are software programs that can carry out multi-step tasks with minimal human direction — for example, researching leads, drafting outreach, updating CRMs, or creating weekly sales reports. – Companies are starting pilots to let agents handle repetitive sales ops and reporting work. The result: faster lead response, fewer manual