Ron Mitchell

Quick summary At Microsoft Build 2024, Microsoft pushed further into enterprise AI with Copilot Studio — a toolset for building custom AI agents (copilots) that connect to an organization’s apps and data. Rather than one-size-fits-all chatbots, these agents can be tailored to handle specific tasks: summarize CRM activity, draft sales outreach, automate reporting, or coordinate […]

Quick summary AI “agents” — autonomous, task-focused AI that can read your systems, take actions, and follow up — are moving from labs into real business use. Big vendors (think Copilot-style features) and a wave of startups now offer agent platforms that connect to CRMs, data warehouses, email, calendars, and BI tools. That makes it

The story in one line AI “agents” — AI models that can call tools, fetch data, and complete multi-step tasks — are no longer experiments. Companies are increasingly wiring these agents into CRMs, calendars, reporting tools, and automation platforms to handle prospecting, meeting scheduling, follow-ups, and operational reporting. Why this matters for business leaders –

Quick summary In the last 12–18 months, major AI platforms and toolkits have made it much easier to build “autonomous AI agents” — software that can plan and complete multi-step business tasks by connecting to calendars, CRMs, email, databases and APIs. Vendors now offer built-in connectors, developer toolkits, and safer execution environments that let these

Quick summary Over the last year the conversation shifted from “what LLMs can write” to “what AI agents can do.” Modern models and tool frameworks now let AI act—query your databases, run reports, update CRMs, book meetings, and hand off to humans when needed. That makes AI agents more than a novelty: they’re practical automation

Quick summary AI agents — software that can act autonomously across apps, gather data, and complete tasks — are moving from lab demos into everyday business use. Companies are using them to qualify leads, draft proposals, automate reporting, and coordinate multi-step processes that used to need multiple people. The result: faster decisions, fewer manual handoffs,

Quick summary AI agents — autonomous, task-focused AI tools that can read your systems, take actions, and follow up — are moving fast from lab demos into real business use. Vendors and startups are now offering “agent builders” and pre-built connectors for CRMs, calendars, email, and data warehouses. Behind the scenes they use retrieval-augmented generation

Summary AI agents — small, task-focused systems that combine large language models with real-time data, tool access, and automation — moved quickly in 2024 from proof-of-concept demos to practical deployments. Businesses are now using them to draft outreach, enrich CRM records, run routine reporting, and trigger workflows that used to take hours of manual work.

Summary AI “agents” — autonomous assistants that can read your CRM, schedule meetings, pull data, and take multi-step actions — are no longer just demos. Over the last year vendors and open-source projects have made it easier to build agents that connect to email, calendars, CRM systems, and data stores. They combine retrieval-augmented generation (RAG),

Summary AI agents—autonomous, task-focused systems that can read your data, run analyses, draft communications, and take actions—are no longer just a developer playground. Over the past year we’ve seen more companies put AI agents into production for sales outreach, customer service triage, and automated reporting. These agents combine large language models with connectors to CRMs,