AI Post

A quick story Over the last year we’ve seen a clear shift: autonomous AI agents — systems that combine language models, data access, and task automation — are moving from experiments into real business use. Teams are using agents to research leads, draft personalized outreach, pull together weekly sales reports from multiple systems, and even […]

The story in one line Over the past year businesses have moved AI agents — “copilots” embedded in CRMs, reporting tools, and workflow apps — from pilots into everyday operations. These agents can draft outreach, generate automated reports, triage tickets, and run routine processes without constant human supervision. Why this matters for business – Faster

Short summary AI agents — autonomous, task-focused systems that combine large language models with triggers, memory, and API connections — have moved from experiments into real business use. Enterprises are now embedding agents into sales, customer service, and reporting workflows to qualify leads, automate follow-ups, generate regular reports, and run simple decision tasks without constant

AI story (short summary) Autonomous AI agents — software that can plan, act, and follow up across systems without constant human prompts — are crossing a tipping point. What used to be experiments in R&D labs is now being used by sales, operations, and finance teams to do real work: draft outreach, book meetings, reconcile

Short summary Over the past year we’ve stopped talking about “can AI do this?” and started seeing AI agents actually run parts of the business — from drafting sales outreach and triaging customer support tickets to generating recurring reports and orchestrating simple workflows across apps. Major vendors and low-code platforms now offer agent frameworks and

AI story (short summary) AI “agents” — small, task-focused AI assistants that can access company tools and data, take actions, and run multi-step workflows — have gone from experimental demos to real business deployments. Sales teams are using agents to triage and qualify leads, customer service teams to resolve routine tickets, and operations teams to

Short summary AI agents — software that can act on your behalf, chain tasks together, and pull answers from your data — have moved from demos to real business pilots. Major platforms and startups now offer agent frameworks and integrations with CRMs, databases, and BI tools. That means teams can automate multi-step work (like lead

Summary AI “agents” — autonomous, task-focused AI that can read systems, take actions, and follow rules — are moving from tech demos into real work. Over the last 18 months, major platforms and low-code tools have made it easier for companies to build agents that do things like draft and send personalized outreach, assemble weekly

Short summary AI “agents” — small, goal-driven systems that can fetch data, run rules, write summaries, and take actions — are moving from labs into real business tools. You’ve probably seen early examples in BI and CRM products (think Power BI/CRM copilots and vendor-built agents). More companies are now using agents to automate routine work:

Short summary The EU’s AI Act — recently finalized and now moving into implementation — changes the rules for how companies build, buy, and run AI systems. It doesn’t ban tools; it sets risk-based requirements around safety, transparency, data handling, and human oversight. For businesses using AI agents, automated workflows, or AI-powered reporting, the law