Teams | Collaboration | Customer Service | Project Management

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.

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.

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.

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.

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.

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.