Teams | Collaboration | Customer Service | Project Management

What an AI governance framework contains, how to build one in stages, and how to check whether the policy matches what people are actually doing.

Every missed business call represents an unanswered question, a frustrated customer, or a potential sale that may go elsewhere. Yet answering every call is difficult, especially for small teams. Employees may be helping customers, working on-site, attending meetings, or simply unavailable outside normal business hours. Technology can solve part of this problem, but businesses are often presented with two different categories of solutions: business phone systems and AI receptionists.

OpenAI's new Apple Messages plugin gives ChatGPT access to the Messages application on a Mac. Once enabled, users can ask ChatGPT to find conversations, summarize them, draft replies, and send messages. That has understandably raised questions about what it means for iMessage privacy. The starting point is understanding what the plugin does and, just as importantly, what it doesn't do.

AI makes it quick and easy to turn rough notes into a clean, easy-to-read document. Job well done, right? Think again. Atlassian’s Teamwork Lab suspected that this professional veneer—what we call “AI polish”—makes it harder to spot foundational flaws and give feedback, so we tested it. We wanted to know: Does AI polish make it harder to identify problems in early drafts? How can we solve for this blind spot?

Email is one of the few workplace tools that creates more work simply by being available. Every message asks for a small decision: open it now or later, reply or ignore, archive or keep, delegate or handle personally. None of these decisions seems particularly demanding on its own, but together they can consume a surprising amount of time and attention. The problem is not always the number of messages.

ServiceNow AI is no longer just about Virtual Agent. Today, its AI stack includes Virtual Agent, Now Assist, AI Agents, AI Agent Studio, and Otto—covering everything from conversational self-service to autonomous task execution. For IT and HR leaders, the real question is not whether ServiceNow can use AI.

There’s a concept in software engineering called a software factory – a structured, repeatable pipeline that takes raw inputs (requirements, code, tests) and reliably produces high-quality outputs (working software). The magic isn’t just automation. It’s the combination of standard tools, curated configuration, and encoded expertise that makes every run predictable, consistent, and improvable over time.

Agentic AI for business uses AI agents to analyze workforce data, identify productivity trends, automate insights, and help managers make faster, data-driven decisions.