Teams | Collaboration | Customer Service | Project Management

Azure DevOps Ticketing System: How to Turn Support Tickets into Work Items

Azure DevOps is often considered for ticket management because it gives teams a way to record issues, assign work, and track progress. The question for IT organizations is how well it supports service requests and incidents, particularly when resolving an issue requires work from a development team. The core purpose of Azure DevOps is managing software development, even though it can track support-related work.

AI is exposing the missing layer in strategic planning

AI is making teams faster, but not organizations. The gap is a missing layer: governed work context that turns a change in strategy into a change in what happens next. AI is making teams faster but that doesn’t necessarily mean it is making organizations faster. That distinction matters. In a recent 451 Research survey, 88% of organizations using AI in workplace tools report productivity gains.

Meet Employee Service AI Agents: Automate HR support and action flows | Zendesk

Discover how Zendesk's employee service AI agents go beyond answering questions to complete tasks directly within tools like Slack. In this video, see how AI agents handle employee requests from start to finish—whether instantly approving policy-compliant time off or routing leave requests to managers for manual review. Learn how HR teams can easily build these automated workflows using Advanced Action Flows.

Asana AI Teammates for Strategic Operations

Meet the AI Teammates built for Strategic Operations in Asana. See how the Executive Reporter turns account data into leadership-ready updates, the Portfolio Advisor flags risks before they become problems, the Program Ops Manager keeps PMO intake moving, and the Capacity Planner balances your team's workload — all learning and improving as they collaborate with your team. Key moments.

WTF Is an MCP Server? (And Why You Should Care)

So, MCP servers. You’ve probably heard about them by now. Maybe someone mentioned them in a meeting, you read about them on LinkedIn, or one popped up in a product update from one of the tools you use at work. And maybe you nodded along like you knew what it meant. No judgment. We’ve all done it. (I’ve done it more than I’d like to admit.) But the problem is, most explanations of MCP servers I’ve read are written by developers, for developers.

Your Enterprise Data Shouldn't Go to a Public AI Endpoint #AI #SLM

Bigger AI models aren't always better for business. Here's why enterprise AI is going small. For years, the AI race focused on larger models with more parameters and broader capabilities. But enterprises have different priorities: data privacy, lower inference costs, faster responses, and control over their own infrastructure. Enter Small Language Models (SLMs). In this video, we explore why businesses are considering smaller, specialised AI models and how they could change the way enterprises deploy AI.

Zendesk Employee Service AI Agents: They get the work done

Ever feel like getting access to basic software tools takes longer than completing the actual project? You’re not alone. In this episode of Office Confessions, we look at the frustration of slow internal approval processes and how to solve it. With Zendesk Employee Service AI Agents, your team doesn't just get answers to questions — they get real work done fast. Learn how Zendesk can help eliminate internal bottlenecks and empower your employees to move faster.

Say yes to AI context without losing control: a new way to set up and govern connectors in Atlassian Administration

Maya runs IT for Beaconstone Financial, a fintech company with 2,000 employees. Her engineering teams work in Jira and GitHub. Sales lives in Salesforce. Most decisions happen in Slack threads, Google Docs, and SharePoint folders that nobody can find six months later. Leadership wants Rovo to answer questions across all of it. Her head of sales has asked for account briefs that pull in the latest Salesforce opportunity data and last week’s customer call.

AI Resource Management for Operations Leaders

Resource management is mostly admin. Checking who’s overbooked, finding cover when someone’s off, or moving every date when a client slips. AI can now take on a lot of that work, from answering questions about your schedule to actually making the changes. This guide covers what AI in resource management usually handles today, and the data it needs before you can trust it to reschedule your people.