AI Post

A quick update (and why it matters for your business) In the last year we’ve seen a surge in practical, enterprise-ready AI agents — task-focused systems that can read your CRM, pull data from reporting systems, draft outreach, and even take multi-step actions with secure connectors. These aren’t just research demos anymore. Businesses are using […]

Quick summary AI “agents” — autonomous, connected AI that can read your systems, take actions, and interact with people — are no longer experiments. Low-code agent builders and pre-built connectors to CRMs, calendars, and data warehouses are letting teams automate tasks like lead follow-up, meeting summaries, and real-time sales reporting without months of engineering work.

Quick summary AI “agents” — autonomous systems that combine large language models with tools, data access, and workflows — have moved from experiments to practical pilots across sales, operations, and finance. Instead of a person prompting an AI every time, agents can monitor systems, gather data, take multi-step actions (send an email, update CRM, generate

Short summary AI agents — software that can take actions, run workflows, and learn from results — are finally maturing for real-world business use. Over the last 18–24 months we’ve moved past proof-of-concept demos toward stable, secure tools that integrate with CRMs, calendars, and reporting systems. That matters because these agents can automate routine sales

Quick summary AI “agents” — autonomous, multi-step workflows built on large language models — jumped from demos into practical use in 2023–2024. Tooling and integrations (open-source frameworks and commercial copilots) now let businesses connect LLMs to CRMs, databases, BI systems, and APIs so agents can do things like prepare reports, triage leads, update pipelines, and

Quick summary Over the past year we’ve seen a clear shift: software vendors and startups are moving from “smart assistants” to true AI agents — autonomous workflows that can fetch data, run analyses, update systems, and alert people when action is needed. Think an agent that pulls CRM data, generates a weekly sales forecast, creates

Quick story AI agents — autonomous software that can read your systems, take actions, and generate human-ready outputs — have moved from labs into real company workflows. Over the last year we’ve seen many vendors and startups ship agent orchestration tools and pre-built connectors for CRMs, ERPs, and data warehouses. The result: teams can now

Short summary AI vendors and cloud giants have made it easy for companies to create their own AI agents — see examples like OpenAI’s Custom GPTs and similar offerings from Microsoft and others. These are not generic chatbots: they can be connected to your CRMs, analytics, document stores and internal tools so the agent acts

Quick take AI agents — low-code, customizable bots that can read data, act on systems, and follow rules — are moving from experiments into real business value. Tools like GPTs, Microsoft Copilot Studio and enterprise AI builders have made it fast to create agents that qualify leads, update CRMs, auto-generate reports, and run routine workflows.

Short summary Autonomous AI agents — software that can act on your behalf, make decisions, and interact with apps and data — are no longer a niche research topic. Over the past year we’ve seen pilots and early production use across sales, customer service, finance, and operations. These agents can triage leads, draft outreach, run