Teams | Collaboration | Customer Service | Project Management

What AI enablement means, what a program actually contains, and why starting with where AI already works beats training everyone from zero.

What an enterprise AI strategy contains, how to build one in stages, and why most are written from an assumed picture of how the organization works.

The service desk is becoming a natural proving ground for AI agents. That makes sense. IT support contains exactly the kind of work AI agents are increasingly designed to handle: repetitive employee requests, fragmented knowledge, predictable troubleshooting steps, approvals, system lookups, and actions that need to happen across multiple applications.

An employee wants Friday off. Another needs a payslip. A new hire is waiting for system access. Someone else has moved house and needs to update their details. None of them really wants to “use Workday.” They want the request resolved.

Deploying artificial intelligence in a legacy corporate environment requires constant, real-time coordination across entirely different technical departments. When organizations force brilliant data scientists to communicate through outdated email threads, the entire machine learning pipeline grinds to a devastating halt. The harder companies fight to maintain siloed update methods, the faster their high-profile AI initiatives sink into operational quicksand.

AI is changing what entire organizations can accomplish. As it moves beyond individual productivity to orchestrating entire workflows, the value of software outgrows what seat count alone can capture. Atlassian customers are already realizing tangible business value from AI and automations, from reporting processes that run up to 40x faster with agents to saving 400 hours per month with automations.

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 AI assistant or automation connected to a messaging platform needs a way to act on your behalf: sending a message, managing a channel, pulling context from a conversation. Rocket.Chat 8.8 gives agents a standard way to do that with a native MCP server, so any MCP-compatible agent can work inside your workspace without your team building and maintaining a custom integration for it. This release also brings tighter security and more reliable calling.