Teams | Collaboration | Customer Service | Project Management

AI agents have made more than 19 million tool calls to Miro’s MCP server since February 2026, and the users behind them span product, design, marketing, operations, and project management. When we launched Miro’s MCP server in February, we had AI coding tools in mind.

Shadow IT is the use of software, hardware, cloud services, or other technology for work without an organization’s IT team's knowledge or approval. It can be as simple as an employee sending a document through a personal cloud storage account or creating a WhatsApp group to coordinate with colleagues. These workarounds can help employees solve an immediate problem, but they also move company data outside the systems IT teams are responsible for securing and governing.

Being available has quietly become part of the job description. Nobody writes “check your inbox every seven minutes” into an employment contract. Yet a delayed reply can feel like a small professional failure, even when you were busy doing the work you were hired to do. So you check. Between tasks. Before a meeting. During the few minutes that were supposed to be a break. The uncomfortable part? Staying close to your inbox does not guarantee that important work moves forward.

A market positioning project that used to take a consulting team four to five weeks now takes two and a half days. That's not a forecast. It's what Michael Nenninger, former EVP of digital consulting at msg, described on a recent episode of the Leaders in Consulting podcast. His team built the work as an AI workflow: around 60 prompts, 15 sub-tasks, and a human checking quality along the way. The host did the math on air: that's 5% to 10% of the effort it used to take.

A collections agent signs in from a bedroom in a shared flat at seven in the morning. The VPN connects, the client CRM opens and a screen full of cardholder records appears. For the next eight hours every system log will read as compliant. Not one of them will record that a flatmate walked behind the monitor twice, or that a phone sat propped against a water bottle with the camera pointed at the screen. That is the gap outsourced delivery now lives with.

Slack can still be working for your team when you start wondering if something else would fit better. Maybe the bill has grown. Maybe conversations are easy to start, but decisions are hard to find later. Or perhaps your team needs a simpler way to turn a request into something someone actually owns. The best Slack alternative depends on what you want to improve: cost, ease of use, asynchronous communication, task management, or control over where your data lives.

Your timesheet says the week is full. What it does not say is what happened inside those hours. That gap is where most work visibility problems begin. A logged hour confirms that someone recorded time. It does not confirm what they worked on or what came out of it. More IT services and outsourced delivery firms now want to close that gap. They want to know where working time goes and how it connects to real output. The problem is simple to describe and hard to solve.

California overtime runs on the workday, not just the workweek. Cross eight hours in a single day and overtime is owed even if the week never reaches 40. Cross twelve and double time begins. California is the only state with a statutory double-time rule. Most guides stop once the rates are explained. That is the wrong place to stop, because in California the underpayment is rarely the expensive part.

When we delivered Atlassian MCP a little under a year ago, the idea was simple: let the AI tools your teams already use – Claude, ChatGPT, Cursor – reach the work that lives in Atlassian. The response was immediate. Now, we’re seeing more than 15M calls a day as it’s become the first thing teams reach for when they want to connect AI to their work. But teams have made it clear they want more. More products, more context, and more of the whole job done.

Over the last two decades, millions of teams have run their work on Atlassian, writing code, shipping products, and supporting customers across billions of workflows. Our platform is also where they make the hard calls, prioritizing which features to build, deciding which customer problems to chase, and choosing where to invest their resources.