Teams | Collaboration | Customer Service | Project Management

Transforming the workforce (not just the technology) with AI strategist Jamie Pride

Most AI talks are about the technology. Jamie Pride opened the afternoon at Canvas 26 Sydney by promising the opposite: A session about AI without really talking about AI. Jamie is CEO of Humanly Agile, and he’s had a front-row seat to a few technology waves as the CEO of REA Group, Partner at Deloitte, and one of the first employees at Salesforce. These days he works with boards, C-suites, and executives on the part of AI most strategies skip: People.

78% faster response time, 94% CSAT with #ZendeskAI | Zendesk customer story: Sinch Engage

How Sinch Engage transformed global support Sinch Engage is a global communications connector — helping businesses reach customers through SMS, email, voice, WhatsApp, RCS, and any channel of choice, anywhere in the world. Supporting 70,000 business customers across 12 brands with 24/7 global coverage, their support team needed a platform that could move fast, empower team leads, and scale without requiring developers for every change.

Agentic AI for email: Quickly resolve complex email threads with AI agents | What's New

Agentic AI for email helps AI agents resolve complex customer email requests with less back-and-forth and minimal setup. Built specifically for email support, AI agents can understand customer intent, answer multiple questions in a single response, execute business procedures through system integrations, and proactively gather missing information to move requests toward resolution faster. When needed, conversations escalate seamlessly to human agents with full context included.

For You Page for all your AI sessions in Jira | Atlassian

All your AI sessions in one place. The For You page in Jira gives you a real-time view of everything your agents are doing, what's running, what's finished, and what needs your attention. Review completed coding sessions, approve pull requests, and kick off new agent sessions directly from the page. Stay on top of your AI-powered workflow without hunting across tools. Watch to see how it works.

Leena AI vs Moveworks Comparison 2026 | Best HR AI Platform for Enterprise vs Mid-Market

Choosing between Leena AI and Moveworks? In this video, we compare two of the leading HR AI platforms to help you decide which solution best fits your organization. We'll cover: Features and capabilities HR AI automation and workflow execution Employee self-service experience Integrations and scalability Best fit for enterprise vs. mid-market companies Pricing considerations and ROI A powerful alternative built for growing businesses.

New research reveals how AI is making jobs bigger

When a tool can do in seconds what used to take hours, it’s natural to wonder if there will be any work left for humans. But new research from Atlassian’s Teamwork Lab suggests the opposite: Rather than shrinking an employee’s remit, AI appears to be expanding both the breadth of what employees take on and the depth at which they operate.

How Rovo helps finance close the books faster | Atlassian

Managing financial systems at scale is complex. Multiple SaaS applications, ERP integrations, transaction flows, and month-end close activities must work seamlessly to ensure data integrity and reporting accuracy. In this video, Alex Auerbach, on the Finance AI and Enablement team at Atlassian, shares how they built Finance360, a Rovo agent that delivers real-time monitoring, proactive alerts, and intelligent troubleshooting across critical financial systems.

AI ROI in professional services: Why capacity isn't converting to margin

There's a question that consulting leaders don't ask themselves enough: if AI created 10% more delivery capacity in your teams tomorrow, would you actually know where to deploy it? That provocation sat at the heart of the session I ran at Leaders in Consultancy Munich, and judging by the room, it landed.

AI at scale: powering the digital workplace (summit recap)

Most enterprise AI programs don’t fail at the model level. They fail at the foundation — the data strategy, governance model, access controls, and measurement discipline that determine whether a pilot ever becomes a production system. The organizations scaling AI well did the unglamorous work first.