Summary A new wave of “AI agents” — autonomous, task-focused AI assistants that can use tools (CRMs, email, reporting systems) and make multi-step decisions — is moving from tech demos into real business use. Instead of a person prompting an AI each time, these agents can run recurring workflows: qualify leads, assemble weekly sales reports, […]

Big story in brief In 2024, AI moved from demos to practical workplace tools. One turning point was OpenAI’s rollout of Custom GPTs and the GPT Store — simple, low-code ways to build domain-specific AI agents that can answer questions, run routines, and connect to company data. At the same time, enterprises started pairing these

AI agents are automating cross‑app workflows — what business leaders need to know Story summary Over the last year we’ve moved from demos and prototypes to real, usable AI agents that can connect to apps, run multi‑step workflows, and act with some autonomy. Vendors and open‑source projects (think Copilot‑style assistants, LangChain/AutoGPT patterns, and multimodal models)

The story — quick summary AI agents are moving out of labs and into everyday business workflows. These are software “assistants” that can read your CRM, draft personalized outreach, generate weekly reports, or triage customer requests — then take action across apps. New platforms and toolkits make it easier for non‑technical teams to assemble agents

Quick summary AI agents—autonomous, goal-oriented systems that can read, act, and coordinate across apps—are moving from research demos into real business use. Instead of a single chatbot that answers questions, these agents can: – pull customer data from your CRM, – draft and send personalized outreach, – create and distribute weekly sales reports, – or

Short summary AI “agents” — autonomous systems that can read, act, and follow multi-step instructions across apps — have moved beyond proof-of-concept. Major AI platforms now give businesses the tools to build task-specific agents: think automated lead outreach, real-time sales reporting, or an assistant that updates CRM records and schedules meetings. The result: faster workflows,

Story summary Autonomous AI agents — software that can carry out tasks, consult your data, and take next steps without constant human prompts — are moving from lab experiments into real business use. Vendors and enterprises are now shipping agent platforms that connect to CRMs, internal docs, databases and reporting systems so agents can qualify

Quick summary AI agents — autonomous software that can follow instructions, use tools, and act across systems — are no longer just demos. Over the past year we’ve seen more companies deploy agents in real workflows: qualifying leads, scheduling demos, updating CRMs, handling routine customer questions, and generating recurring reports. These agents combine large language

Quick summary AI “agents” — autonomous, multi-step assistants that can read your systems, take actions, and follow up — have moved from experiments to enterprise-ready tools. Major cloud vendors now offer low-code agent builders, and companies are using agents for lead qualification, order routing, customer support triage, and automated reporting. The result: faster responses, fewer

Short summary AI agents — autonomous software that can read, decide, act, and learn — are moving from experiments into everyday business use. Companies are combining these agents with retrieval-augmented generation (RAG) and connected data (CRMs, ERP, knowledge bases) to automate tasks like lead triage, proposal drafting, routine reporting, and exception handling. That means less