Teams | Collaboration | Customer Service | Project Management

We’ve all been there – toggling between six tabs, copying content from one tool into another, and wondering if anyone actually read the brief. The promise of AI was supposed to fix this. Instead, most teams got a chatbot bolted onto the side of their screen. We think AI should work the way a great teammate does: show up where the work happens, understand what’s going on, and actually move things forward. Not from a separate window. Not after a five-paragraph prompt.

AI is changing how engineering teams work faster than most organizations can adapt. Coding assistants are now part of the daily workflow, agents are starting to own tasks end-to-end, and the way we deliver software is being redefined in real time. With that shift, engineering leaders are facing a new set of questions. Are these tools actually improving outcomes? Where are they falling short? Which teams are seeing value, and which aren’t?

AI agents are only as good as what they know. Right now, most don’t know enough. Not because the AI is broken, but because the data is. Information is scattered across tools, siloed by department, stripped of the human context that makes it useful. Agents guess. They hallucinate. Teams splinter around different versions of the truth. Context isn’t a file or a ticket. It’s the space in between: why a decision was made, who owns it now, what broke last time.

Over the past few decades in the technology industry, some of the biggest constraints to building products have been about having enough engineers, time, or compute. For the first time, that era is ending. Tech teams are experiencing a revolution unlike anything they’ve seen before. The barriers to entry for building have all but disappeared. The constraint no longer comes from producing enough output, but from deciding what to build, and the restraint required to build something good.

The way organizations work is being fundamentally reshaped by AI, evolving technologies, and macroeconomics. And IT leaders are not just responding to this change; they’re defining the strategic direction for how their organizations work. A new commissioned study conducted by Forrester Consulting on behalf of Atlassian, surveying 280 IT leaders globally (44% Directors, 56% VPs and CIOs), revealed a decisive shift in how enterprises are approaching their digital workplace. The mandate is clear.

Engineering teams today are shipping more than ever. Sprint boards move quickly, work items are completed on schedule, and releases move forward with steady momentum. As engineering output scales, so does the time spent across the broader software development lifecycle (SDLC). Jira continues to play a critical role as the system for organizing, tracking, and delivering work.

New research with 308 senior enterprise leaders reveals a counterintuitive finding: the problem isn’t strategic clarity, and it isn’t how often you plan. It’s whether your organization is actually able to act when strategy demands a change.

When Elena Verna joined Lovable, an AI-native startup, she wasn’t chasing another growth role. “I actually wanted to retire before I hit Lovable,” she admits. After leading growth at Dropbox, SurveyMonkey, Miro, and Amplitude, she’d seen the same patterns play out again and again. “I couldn’t do another gig where I felt like I’m doing growth 101. Onboarding flows, lifecycle emails, A/B tests.

96% of companies haven’t seen meaningful business value from AI. And yours might be one of them. IT leaders are spending big anyway – and wondering why projects still slip and service metrics refuse to improve. According to Atlassian’s AI Collaboration Index, 96% of companies haven’t yet seen meaningful business value from AI, despite widespread investment. AI has made it easier to get work done, but not easier to work together.

The learnings in this blog post are based on sessions from Atlassian’s Teamwork in an AI era event featuring Forrester Senior Analyst Will McKeon-White and Atlassian’s Teamwork Lab. You can check out these sessions and others on demand. Everything’s moving faster. Decks are drafted in an afternoon. Customer emails write themselves. Reports that used to take a week now show up in your inbox overnight. But the faster your teams move, the harder it gets to keep everyone on the same page.