AI Post

What’s happening – Autonomous AI agents — software that can take actions, make decisions, and carry out multi-step workflows — are no longer just lab demos. Over the past 18–24 months they’ve been embedded into CRMs, RPA tools, and analytics platforms to handle tasks like lead qualification, follow-up emails, scheduling, and automated reporting. – These […]

Quick summary – In the last year major vendors (Microsoft, OpenAI and others) launched easy ways to build custom AI agents and copilots that connect to your apps and data. – These agents can read CRM records, pull spreadsheets, draft emails, update opportunities, and generate reports — all with natural-language prompts. – The result: faster

Why AI agents are moving into the boardroom — what business leaders need to know Summary of the story – Autonomous “AI agents” — systems that combine large language models with tools, APIs, and workflows to act on behalf of users — have moved from demos and hacker projects into enterprise pilots. – Vendors and

Short summary AI “agents” — autonomous software that can carry out multi-step tasks across apps — are moving from tech demos into real business use. Instead of a human copying data, switching between tools, and sending follow-ups, an AI agent can read your CRM, draft personalized emails, update records, and schedule meetings — all with

Quick summary AI agents — autonomous, task-focused systems that can browse data, run workflows, and take actions on behalf of users — are no longer an experiment. Over the past 18–24 months, vendors and enterprises have moved from PoCs to production deployments: internal agents that qualify leads and book meetings, finance agents that assemble monthly

Summary AI “agents” — autonomous workflows that combine large language models, tool connectors, and your business data — are transitioning from experimental pilots to practical production use. Instead of single-chat assistants, companies are now using agents to run end-to-end tasks: qualify leads, update CRMs, generate weekly reports, triage customer requests, and even coordinate cross-team approvals.

Quick summary AI agents — autonomous workflows powered by large language models that can call tools, read your data, and act without constant human prompts — are moving from research demos to real business use. Frameworks and integrations that let agents connect to CRMs, calendars, databases, and reporting tools have made them practical for tasks

Summary Autonomous AI agents — software that can act, decide, and complete multi-step tasks with little human prompting — have moved beyond flashy demos. Companies are now using agents to draft outreach, triage customer support, update CRMs, and generate automated reports. That shift means AI is no longer just an assistant: it can be an

Quick summary Major vendors and SaaS platforms are adding AI agents — autonomous or semi-autonomous systems that can read data, take actions across apps (CRM, email, calendar), and generate reports. Instead of just answering questions, these agents can qualify leads, draft outreach, update records, and produce recurring performance reports — freeing teams from repetitive work.

What happened (quick summary) – Over the last 18 months we’ve seen a big jump in autonomous AI agents — systems that can use tools, access company data, and complete multi-step tasks without constant human prompting. – These agents combine large language models, retrieval-augmented generation (RAG), and connectors to CRMs, calendars, cloud storage, and APIs