AI can help teams write more code, faster. But the real question is whether that code is safe, useful, aligned to intent, and ready to deliver the business outcomes teams promised.

In this session, we will showcase a new class of “right of code” DevAI agents that help software teams move beyond raw coding productivity. Through a live demo of AI Planner, Reviewer and an SRE agent working together, we will show how agents can learn from incidents, pull request feedback, human reactions, and past performance, then distil those learnings into memories and standards that improve future reviews and operational readiness.

We will also demonstrate how agentic QA can evaluate software changes against human intent, not just code diffs. By combining Jira requirements, AI planning, app experience walkthroughs, and design system checks, DevAI agents can flag gaps between what was built and what the business or user actually needed, then prompt coding agents to fix the issues. The result is a self-improving delivery loop that helps teams reduce reactive grind, improve quality, and ship changes with greater confidence.

Attendees will see how AI agents can help teams ship with more confidence by reviewing not just the code, but the impact of the change on users, systems, and business goals.

Key takeaways:

• Self-improving agents: Learn how AI Reviewer and SRE agents can turn incidents, reviews, and human feedback into reusable standards and memories that improve over time.

• Intent-driven review and QA: See how DevAI agents can evaluate product experiences against Jira plans, requirements, and design systems, not just against code diffs.

• Less reactive grind: Understand how “right of code” agents can reduce wasted effort, surface risks earlier, and help teams focus on customer and business impact.

In 2025, we shared how Atlassian Williams F1 Team started connecting strategy, work, knowledge, and AI to unlock the potential of a connected System of Work. Now see what happens when they design for Flow. We'll unpack how Williams is rebuilding purpose, work, knowledge, and intelligence flows across the organisation - standardising tooling, streamlining updates, and embedding Rovo-powered agents into critical engineering, IT, and leadership workflows - to turn how their teams work into a performance edge.

• Align strategy, funding, and execution across the enterprise
• Gain real-time visibility into value delivery and investment performance
• Empower leaders with actionable insights for portfolio prioritisation and funding decisions

When a legacy ITSM platform becomes too expensive, too slow, and too rigid, something has to give. That’s why Axpo — Switzerland's leading energy company — decided to migrate 4,000+ users to Jira Service Management in just 4.5 months. The hardest part of that transition? Learning that copying old processes into a new tool doesn’t always translate.

Hear how Axpo tested its legacy-platform exit against real workflows, made difficult tradeoffs during a greenfield rollout, and built enough momentum for other parts of the business, including HR, to follow. Its IT platform is now evolving into a Service Engineering Platform, with CMDB schemas, SLAs, and routing rules versioned in Git and deployed through continuous integration and delivery.

This is an honest, in-progress account that covers the technical debt and limitations that surfaced along the way, as well as the path ahead toward AI agents and infrastructure as code.

Key takeaways:

• How to validate a legacy platform exit against real workflows before committing the business case
• Discover how to navigate the tradeoffs and technical debt of a 4.5-month migration
• How to transform Jira Service Management into an engineered platform by managing CMDB schemas, SLAs, and routing rules as code via CI/CD

In steam turbine field service, a single missed handoff can trigger costly delays — yet the industry has long relied on Excel spreadsheets, paper forms, and email chains that were never built for this level of complexity. In this session, Siemens Energy, a global leader in energy technology, and implementation partner HiQ share how they reimagined field service operations within Jira Service Management, achieving 3x faster throughput with full visibility at every handoff.

You'll hear what drove the change, how the platform was architected for scale across a complex industrial environment, and how Rovo and automation are now layered on top to build a system that doesn't just work, but learns.

Key takeaways:

• How to map a complex industrial field service process onto Jira Service Management, without losing the operational nuance that keeps turbines running
• What actually drove the transformation, and what almost got in the way
• Practical patterns for layering AI augmentation onto a stabilised service workflow, with real examples from production

• See the gap: a live, side-by-side demo of the same agent with and without organisational context
• Set it up yourself: concrete patterns to connect agents to Jira, Confluence, Bitbucket, and third-party sources via Teamwork Collection
• Why Atlassian wins here: the Teamwork Graph is a structural advantage that composes with any coding agent your team already uses

What happens when an enterprise moves beyond AI experiments and becomes an AI-native organisation? Join some of the fastest-growing teams as they share how Rovo is becoming part of everyday work for their teams. Hear how they are using Atlassian Rovo to deploy AI agents across their entire business to reduce operational overhead, saving hours, improving cycle times, and accelerating time to value.

Key takeaways:

• See real customer use cases for agentic workflows across Jira, Confluence, and connected tools

• Take away practical patterns for scaling agentic AI responsibly and predictably

• Learn practical strategies for implementing agentic workflows and accelerating teams with AI-powered tools

The latest platform roadmap - extensibility, AI capabilities, and the broader ecosystem - framed around what's possible and what's coming.

Customer service is often where the richest signals about product quality, incidents, friction, and unmet needs first appear — yet those insights can get trapped in support tools and handoffs. 

In this 15-minute session, we’ll show how Atlassian’s Customer Service Management (CSM) integrates customer service into the Atlassian System of Work. We will show how CSM, powered by AI and the Teamwork Graph, breaks down silos between teams and brings customer insights to the centre of the organisation — resulting in faster resolutions and better products and services.

Artificial Intelligence is only as smart as the context it receives. Without a unified, context-aware foundation, enterprise AI risks delivering fragmented insights and low return on investment.

In this session, learn how the Teamwork Graph serves as the ultimate context layer for your organisation: bridging data across workflows, teams, and tools to power smarter, more intuitive AI experiences like Atlassian Rovo. Discover how shifting to a proactive, context-aware architecture allows you to maximise the ROI of your AI investments while maintaining enterprise governance and trust.

Key Takeaways:

• Understand how connected organisational context dramatically improves AI accuracy, relevance, and value across everyday workflows

• Learn how a grounded context layer shifts your enterprise strategy from reactive AI governance to a proactive, secure foundation

• See how the Teamwork Graph enables enterprise-grade scaling, measurement, and data privacy without sacrificing performance or context depth

Traditional IT support is reactive — employees hit an issue, raise a ticket, and wait. Proactive service management in Jira Service Management changes the game by detecting device issues before they impact employees, automatically remediating where possible, and guiding employees through resolution when automation isn't available.

In this 30-minute session, we'll show how proactive service management brings digital employee experience capabilities into Jira Service Management — from admin setup and sensor configuration to silent saves, consent-based fixes, and guided remediation delivered through Rovo desktop. See how IT teams can reduce ticket volume, cut downtime, and prove ROI with proactive support.

Can't make this session? Be sure to check the schedule as this session will be repeated.

Admins know their organisation better than anyone. As organisations move faster, deploy more AI, and expect more from their platforms, admins become the linchpin behind teamwork, building reliable foundations. With the right tools, they elevate the whole organization.

That’s why we’re investing in expanded capabilities that let admins easily design and secure your system of work while scaling your impact. In this session, senior product leaders walk through the latest administration capabilities designed to help admins work smarter: surface the right insight at the right moment, manage cost and resource consumption as AI scales, automate the routine so the team can focus on higher-value work, and put the controls in place to govern an AI landscape that's expanding fast.

Key Takeaways:

• Manage a growing organisation by automating routine tasks and extending your impact
• Optimise costs and resource consumption, prevent disruptions, and maintain visibility as your environment scales
• Govern complex policies and control what humans and AI can access, share, and do across your platform

• Capture every signal: Bring feedback from customers and customer-facing teams together and let AI help make sense of it.
• Make decisions with evidence: Ground roadmap priorities, problem statements, and product bets in the complete customer picture.
• Discover the real problem: Move beyond counting requests by exploring why customers are asking for something.
• Carry customer context forward: Preserve the rationale as decisions become roadmap and delivery work.
• Build a learning flywheel: Return to customers, measure what happened, and feed new learning into the next decision.

Can't make this session? Be sure to check the schedule as this session will be repeated.

Join us for a first look at what's next from Appfire. At this session we will be unveiling new product innovation availability, spanning the Atlassian platform — from smarter ways to work in Jira and Confluence to AI-native capabilities built to transform how teams manage risk, work, and knowledge. Come see how these innovations connect the dots across your Atlassian ecosystem, and be among the first to hear the news.

This is a sponsored session. Badge scanning is optional. By having your conference badge scanned, you are opting in to be contacted by the sponsor. You will be subject to the sponsor’s communications and privacy policies and must contact them directly if you later wish to change your preferences.

AI agents rarely fail because the model is weak – they fail because the organisation underneath them isn't ready. It's not a technology gap, but an architecture and leadership gap: knowledge nobody maintains, processes that only live in people's heads, no clear line between what a machine may decide and what stays with a human. And it's not just an ITSM problem – it's the same pattern we see across technology, organisation, and people whenever transformation stalls.

In this session, using Jira Service Management (JSM) as the proving ground, we show how to assess how ready your service organisation actually is. We then follow one ordinary ticket end to end – routed, picked up by the right specialist, resolved across the tools involved, every step documented – to make concrete what "AI-ready" looks like before you call anything agentic.

Getting there takes clear analysis, solid architecture, and leadership willing to commit – and staying there is a continuous maturity process, not a one-off fix. This is exactly the kind of transformation we help organisations navigate: in practice, with experience, and to good effect.

This is a sponsored session. Badge scanning is optional. By having your conference badge scanned, you are opting in to be contacted by the sponsor. You will be subject to the sponsor’s communications and privacy policies and must contact them directly if you later wish to change your preferences.

The teams winning right now aren't waiting to figure it out. Join Atlassian leaders to hear their vision for how teams will work, grow, and win in a world where human and AI collaboration changes everything.

Bringing a new vehicle from concept to production depends on thousands of connected decisions across product, procurement, manufacturing, quality, and finance. At McLaren Automotive, many of those critical processes were managed through disconnected spreadsheets, presentations, and siloed systems. Leaders spent more time gathering and reconciling information than acting on it, slowing the teams responsible for developing the next generation of supercars. To move faster, McLaren needed to connect the work, the data, and the decisions behind every vehicle.

Join leaders from McLaren Automotive, alongside their transformation partner Valiantys, as they share how they replaced fragmented, manual processes with a connected system of work on the Atlassian platform — linking product quality directly to parts, suppliers, sourcing, and costs across the entire lifecycle. They’ll get honest about what it took: integrating Atlassian with existing enterprise systems to create a single source of truth, designing workflows that business teams actually prefer over their old spreadsheets, and proving value through improved cash flow, tens of thousands of hours returned to teams, and better margin per vehicle sold.

They’ll also share how this connected data foundation unlocked meaningful AI adoption, with AI-driven insights cutting governance meetings by up to 50% and shifting leadership time from compiling information to making better decisions.

• See the gap: a live, side-by-side demo of the same agent with and without organisational context
• Set it up yourself: concrete patterns to connect agents to Jira, Confluence, Bitbucket, and third-party sources via Teamwork Collection
• Why Atlassian wins here: the Teamwork Graph is a structural advantage that composes with any coding agent your team already uses

• Explore the different modes built for different kinds of tasks and see how knowing when to use each one changes what your team can accomplish with AI every day
• See how Skills and other capabilities extend what Rovo Chat can do in context, so your sessions produce targeted artifacts connected to your team’s work
• Discover how AI Inbox and Spaces give you a single layer to manage your activity, surface approvals, and keep your organisation’s context connected so your team stays in control as AI does more

Additional details coming soon

As AI transitions from passive chatbots into autonomous agents, the true friction today isn’t a lack of model intelligence—it’s the "context wall" that fragments data between separate applications. Join Ed Muthiah, ML Solutions Architect, for a practical, demo-driven discussion designed specifically for Product Managers, Agile Leaders, and Engineering Managers who spend their time between Atlassian tools and Google Workspace.

Every time a team member has to manually track down subject matter experts, dig through comment threads, or schedule synchronization meetings just to identify project blockers or required resources, momentum stalls. You’ll see firsthand how deep integrations between Google Workspace, Gemini, Atlassian, and Rovo allow AI agents to securely share enterprise-wide context across both ecosystems. We will demonstrate how cross-platform agents like Gemini and Atlassian Rovo synthesize information across Gmail, Google Docs, Jira, and Confluence to surface hidden technical blockers, instantly answer complex architectural questions, and eliminate the need for ad-hoc alignment meetings. Learn how to move past the "wait and see" era of AI and turn your everyday applications into active execution partners.

You’ll walk away with:

• A blueprint for building continuous, cross-platform agentic workflows that securely span Google Workspace and Atlassian tools
• A repeatable framework to reduce SME dependency and eliminate alignment meetings by leveraging shared enterprise-wide context
• A practical guide on how to get product and development teams to trust, adopt, and collaborate with autonomous digital coworkers

This is a sponsored session. Badge scanning is optional. By having your conference badge scanned, you are opting in to be contacted by the sponsor. You will be subject to the sponsor’s communications and privacy policies and must contact them directly if you later wish to change your preferences.

85% of knowledge workers use AI. But only 6% of executives can point to clear ROI.

Join Atlassian's Chief People and AI Enablement Officer Avani Prabhakar and VP of Presales and Value Management Mark Nolan for a candid conversation about the questions every leadership team is wrestling with: How do you get more from AI? How do you bring your people along? And what does meaningful ROI look like?

Drawing on Atlassian’s research, our own AI journey, and lessons from the field, they’ll show why context is the competitive advantage: connecting AI to your teams’ goals, knowledge, people, and workflows so humans and agents can coordinate around shared outcomes. You’ll leave with a practical framework for moving beyond pilots to AI-powered teamwork that delivers measurable impact.

Most strategies do not fail in the planning room. They lose shape as AI changes the velocity of work. See how Strategy Collection keeps strategic context connected across priorities, organizations, people, funding, work, decisions, and AI-assisted updates, so leaders can spot drift, understand what changed, and act before outcomes slip.

Can't make this session? Be sure to check the schedule as this session will be repeated.

Key Takeaways:

• Start with the business, not the technology — how an onsite workshop with the CMO and 7 marketing leaders identified the use cases with the highest measurable impact, anchoring AI adoption to real business priorities from day one.
• From ideation to deployment through partnership — how VodafoneZiggo collaborated with Atlassian's AI specialist to design and deploy Rovo agents that drove 20x growth in agent interactions and eliminated manual quarterly-planning overhead for marketing squads.
• Value that scales beyond marketing — how the same patterns expanded into tech teams, proving that a focused starting point (one workshop, one function) can become a cross-functional accelerator across the enterprise.

Large corporates in regulated industries in Europe have a dilemma. They want and must harness the power of AI, but it must also be compliant also. What does this mean in the European context, what are the implications and solutions?

• Definition of Sovereignty: Is Sovereignty a switch, or a dial. What are the dimensions of sovereignty. How does the European Commission defines Sovereignty. How does Accenture defines Sovereignty.
• Applying Sovereignty: Having the S-talk. Cristalizing the top S-criteria. Impact of the US Cloud Act. Reflecting on the Sovereignty spectrum and shaping a solution
• Moving to a Sovereign Cloud: Typical building blocks of a Migration
• Harnessing AI in a sovereign Cloud to boost SDLC

This is a sponsored session. Badge scanning is optional. By having your conference badge scanned, you are opting in to be contacted by the sponsor. You will be subject to the sponsor’s communications and privacy policies and must contact them directly if you later wish to change your preferences.

AI is transforming how businesses operate and leaders are being held to higher expectations. Service must be unified, intelligent, and resilient across your entire organization, not patched together and slowed down by legacy constraints. Learn how Atlassian’s AI-powered Service Collection, including Jira Service Management, Customer Service Management, Assets, and Rovo, enables teams to meet this moment.

Would you let an AI agent act on your behalf if you weren't sure what it actually knows? That's the question every IT and Security leader is quietly sitting with right now, and it's the question this session answers.

We'll open with something most vendors won't show you on stage: the same request, run live, once through a Rovo agent and once through a general-purpose AI assistant, both pulling from the exact same asset data. One of them wins, clearly and immediately, and the reason why is the whole point of this talk. It comes down to what's underneath the agent, not what's inside the prompt. Specifically, whether that data is complete, consistent, and current, the standard Lansweeper was built to deliver and most environments quietly fail to meet.

This isn't a feature demo. It's a working case for a bigger idea: human-AI collaboration doesn't fail because the model isn't smart enough. It fails at the moment a person has to decide whether to trust what the agent just told them, and that decision is only ever as good as the context behind the answer.

If your organization is betting on Rovo, or evaluating whether to, you'll leave this session with a sharper question to ask about every AI initiative on your roadmap: not "what can this agent do," but "is the data behind it complete, consistent, and current enough to trust?" That question is the difference between an agent your team supervises and one your team works alongside.

Key Takeaways:

• An AI agent is only as good as the context behind it: data that's complete, consistent, and current enough to actually mean something.
• A live, side-by-side comparison shows what that context standard buys you in speed and reliability, not just in theory.
• Attendees leave with a sharper evaluation question for their own AI initiatives: does this agent have the context to be trusted with the answer?

This is a sponsored session. Badge scanning is optional. By having your conference badge scanned, you are opting in to be contacted by the sponsor. You will be subject to the sponsor’s communications and privacy policies and must contact them directly if you later wish to change your preferences.

Teams don't lack information - they lack the right, connected context to move their work forward. In this keynote, see how Atlassian turns scattered knowledge into a compounding advantage. Powered by the Teamwork Graph – unifying seven layers of context – accelerated by Rovo agents, we'll show how connected workflows across Jira, Confluence, Loom and Rovo unlock work and compound value so your teams and agents deliver better outcomes with every loop. All teams. Any project.
On one foundation. Set a new standard for work with a collection designed for human+AI collaboration.

Is your AI hallucinating or helping? The difference is your Teamwork Graph. We’re moving beyond documentation as a chore and treating it as a high-leverage business asset. Learn how to structure your Atlassian stack so LLMs can amplify your team's best work, keep context intact, and bridge the gap between messy internal workflows and polished business outputs.

This is a sponsored session. Badge scanning is optional. By having your conference badge scanned, you are opting in to be contacted by the sponsor. You will be subject to the sponsor’s communications and privacy policies and must contact them directly if you later wish to change your preferences.

• How view-aware AI turns a roadmap or Now/Next/Later board into a planning conversation, summarize it, spot the patterns, decide what to move next.
• Practical ways to go from planning artifact to stakeholder update in seconds, grounded in the exact view you’re already using.
• Why anchoring AI in connected, permission-aware context is what makes it feel fast, trustworthy, and genuinely useful for product teams.

AI adoption is everywhere. AI-native operations are not. While organisations are rapidly introducing chatbots and isolated agents, many still struggle to translate experimentation into measurable business value. The problem is rarely access to technology. The problem is that AI is being added to existing work without fundamentally redesigning how that work flows. That creates a hidden cost: individual, inefficient prompting can not only consume credits, but also time and attention without producing reusable capability or measurable outcomes. AI-native workflows are not free either, but they make AI spend more deliberate, governable and optimisable by reusing context, choosing the right level of automation and measuring cost against business value.

In this session, we will explore the growing gap between AI adoption and operational transformation, define what AI-native actually means, introduce a practical maturity model and explain why the workflow—not the individual prompt—is the true unit of AI transformation on the Atlassian Platform. You will discover what organisations need to connect people, agents and trusted organisational context responsibly, and why platform expertise, process understanding, transformation capability and people enablement must come together.

Bring us one workflow your team complains about every week. At our booth, we will demonstrate a live agentic workflow and help you identify where AI could create lasting value in your organisation.

This is a sponsored session. Badge scanning is optional. By having your conference badge scanned, you are opting in to be contacted by the sponsor. You will be subject to the sponsor’s communications and privacy policies and must contact them directly if you later wish to change your preferences.

At TBC Bank, 155 agile teams support 451 systems and more than 200 digital banking services. Get an inside look at how the bank is moving from AI-assisted tasks toward AI-first ways of working across the SDLC and ITSM — from requirements, testing, and deployment to incidents, problem management, and service governance. Learn how Rovo, combined with third-party agents, creates an ecosystem that can collaborate across Atlassian and external platforms while remaining grounded in governed enterprise data and workflows. You’ll walk away with a proven model for moving from standalone AI assistance to coordinated human-agent workflows.

Key takeaways:

• How Rovo and specialised third-party agents collaborate across software delivery and technology service management — and how to measure their value
• How AI-first development is changing team roles, responsibilities, skills, and everyday ways of working
• How trusted context, clear boundaries, governed handoffs, and human approval enable scalable agents

Last year, Atlassian’s first State of Product report revealed a paradox: product teams were adopting AI faster than ever, yet felt more disconnected from strategy than before. Burnout was up. Confidence was down. And the relentless push toward profitability was squeezing out the work PMs actually signed up to do.

So what’s changed? In this panel, Axel Sooriah (Atlassian) sits down with product leaders to unpack the findings from Atlassian’s second annual State of Product report. Drawing on survey data from 1,000+ product professionals, the conversation goes beyond the numbers — into what’s actually working inside high-performing product teams, where AI adoption is paying off (and where it’s still falling short), and what the best product orgs are doing differently to close the gap between speed and strategy.

Key takeaways:

• How the most effective product teams are using AI to reclaim strategic time — not just automate tasks

• Why the gap between product teams that experiment and those that don’t is widening, and what that means for outcomes

• What product leaders are doing to rebuild confidence and focus amid growing pressure to deliver business impact

Predicting where AI goes next is nearly impossible. What you can control is how ready your organisation is when it gets there.

Agents are already a way of life for enterprise teams — automating workflows, making decisions, and accessing sensitive data across your organisation. Governing that is table stakes. But technology keeps evolving, and the organisations that will win with AI aren’t the ones who predicted every change. They’re the ones who built a foundation flexible enough to handle whatever comes next.

In this session, we will share how leading enterprises are shifting from reactive AI governance to a proactive foundation of context-aware protections that give teams the confidence to move fast. We’ll cover what it looks like in practice to stop chasing AI and start setting the conditions for it to flourish across teams, regions, and sensitive workflows.

You’ll leave with a concrete framework for building a governance foundation that doesn’t slow innovation down. It’s what makes innovation possible.

This session is designed for IT leaders, security teams, and compliance professionals responsible for scaling AI adoption across regulated environments.

Everyone bought the AI coding tools… then watched throughput flatten because typing code was never the real bottleneck. In this breakout, Chelsea Bullock and Richard Sworder show you how Rich's teams at Atlassian Williams F1 Team actually solved this in a high-complexity, high-stakes development environment. We'll walk the real loop live: a spoken Loom becomes structured Jira work, Rovo and the Teamwork Graph assemble context (with the expertise of in-house analysts but for no additional cost)-- with high token spend reserved exclusively for building-- then the solution ships through Bitbucket Pipelines with instant rollback. The result? Work once quoted at 2 months is now delivered in 2 hours. Come for the inspiration and stay for the practical plays you can run on Monday.

Note: please do not publish until customers are finalized

What does it actually take to build a developer experience program that earns trust from engineers, drives measurable AI and productivity gains, and gives leadership the data they need to make confident investment decisions? In this fireside chat, two of Europe's most respected engineering organizations share how they stood up their DevEx programs, made the case for AI tooling, and learned to measure whether it was actually working.

Booking.com and Adyen will walk through the full arc of their journeys: the early challenges of measuring developer productivity, how they rolled out AI code assistants to skeptical engineering teams, and what change management looked like in practice. They’ll dive into how DX’s data ultimately shifted the conversation from gut feel to evidence. 

The conversation will explore how Booking.com found that daily active users of their AI tool had 16% higher change throughput than non-users, and later drove a 65% increase in AI adoption through targeted enablement. The panelists will also explain how Adyen is now using the same data-driven approach to guide their own AI rollout.

This session will be moderated by Lizzy Rosen, VP of Customer Experience at DX, and features speakers from Booking.com and Adyen (TBD). Attendees will leave with concrete recommendations for building or maturing their own DevEx and AI measurement programs, grounded in real outcomes from two organizations that have done it at scale.

Key takeaways:

• How to measure the actual productivity impact of AI tools, and use that data to drive smarter vendor and investment decisions
• What change management looks like when rolling out AI tooling across large, distributed engineering teams
• How to move from surface-level surveys to quantitative and qualitative data that drives real decisions at every level of the organization

Most strategies do not fail in the planning room. They lose shape as AI changes the velocity of work. See how Strategy Collection keeps strategic context connected across priorities, organizations, people, funding, work, decisions, and AI-assisted updates, so leaders can spot drift, understand what changed, and act before outcomes slip.

AI in IT operations has mostly meant detection and recommendation: flagging anomalies, suggesting fixes, and routing tickets faster. The harder problem is acting on what you find. This session examines how AI agents close that gap, resolving technical incidents end to end, working with the tools teams already run instead of replacing them. We'll look at what that shift means for the technicians it elevates, the business it accelerates, and the governance that autonomy necessitates.

This is a sponsored session. Badge scanning is optional. By having your conference badge scanned, you are opting in to be contacted by the sponsor. You will be subject to the sponsor’s communications and privacy policies and must contact them directly if you later wish to change your preferences.

Three years ago, Roche Pharmaceuticals faced a familiar but daunting challenge: 60,000 users across disconnected Atlassian instances, no standardised platform, and one of the most regulated operating environments in the world.

Hear how they embarked on a journey to consolidate that sprawl into a single, governed Cloud Enterprise platform — spanning medical device development, digital medicine, and pharma R&D. Learn how they designed for user diversity at scale, maintained GxP compliance throughout, and sequenced adoption from core Jira and Confluence through to Jira Product Discovery and Rovo.

Key takeaways:

• How to consolidate multi-instance sprawl into a single, governed Cloud Enterprise platform
• A framework for designing a cloud environment that serves diverse user needs across regulated and non-regulated teams
• How to sequence adoption to deliver value at every stage of a multi-year migration

Jira tracks work, but the conversations that move it forward happen in Microsoft Teams and Outlook. Updates are shared in channels, decisions get made in chats, and meetings happen in calendars, while the Jira work item only captures the final outcome.

We'll show how to connect Microsoft 365 collaboration directly to Jira work items, so updates and discussions stay tied to the work automatically. This creates the context foundation AI needs to understand the work, its history, and the decisions behind it.

Key takeaways

• How to keep collaboration structured by default, so Jira reflects what actually happened

• How structured updates improve handoffs, visibility, and decision traceability
• How the same setup supports both Jira Software and Jira Service Management workflows

This is a sponsored session. Badge scanning is optional. By having your conference badge scanned, you are opting in to be contacted by the sponsor. You will be subject to the sponsor’s communications and privacy policies and must contact them directly if you later wish to change your preferences.

Two dimensions can be crystalized:

• Current setup where given roles use AI along the life of a typical feature. This demo shows the power of AI in a classical SDLC modus, speeding and improving traditional tasks.
• Empowered setup with agentic SDLC
  • Architecture
  • Marketplace / Vendor skills
  • Agentic SDLC
  • MCPs closing the loop (doc in Confluence etc.)
• How to get there
• FinOps and Tokenomics

This is a sponsored session. Badge scanning is optional. By having your conference badge scanned, you are opting in to be contacted by the sponsor. You will be subject to the sponsor’s communications and privacy policies and must contact them directly if you later wish to change your preferences.

• Capture every signal: Bring feedback from customers and customer-facing teams together and let AI help make sense of it.
• Make decisions with evidence: Ground roadmap priorities, problem statements, and product bets in the complete customer picture.
• Discover the real problem: Move beyond counting requests by exploring why customers are asking for something.
• Carry customer context forward: Preserve the rationale as decisions become roadmap and delivery work.
• Build a learning flywheel: Return to customers, measure what happened, and feed new learning into the next decision.

Can't make this session? Be sure to check the schedule as this session will be repeated.

The first minutes of any incident are wasted: responders context-switch between Slack, monitoring dashboards, runbooks, Jira, and deployment history before meaningful action begins.

This 15-minute session shows proactive ops in Jira Service Management, powered by Ops Expert, Atlassian's AI agent for IT operations. Unlike tools that wait to be asked, Ops Expert operates continuously across the surfaces teams already use, carrying context throughout the full incident lifecycle. It draws on the Teamwork Graph, including service ownership, change history, past incidents, and runbooks, to act with the right context at the right time.

See how Ops Expert handles the full spectrum of incidents – from simple to complex – and continuously feeds resolution insights back into runbooks, deployment practices, and change management. Walk away with three ways you can deploy Ops Expert across your incident workflows to detect and resolve incidents before your customers ever feel the pain.

Key takeaways:

• What end-to-end AI-native ops looks like in practice
• How Ops Expert reduces MTTR today
• Where the proactive ops vision is headed in Jira Service Management

Key takeaways:

• Atlassian's compliance coverage across DORA, NIS2, BSI C5, GDPR, and EUCS
• What's available today and what else is shipping this year
• Three actions you can take this quarter

Complex programmes fail not because of bad code, but because of coordination breakdown. When delivery spans multiple teams, multiple vendors, and multiple workstreams, the friction lives between the agents — human and AI alike. Today's enterprises are deploying AI agents across their SDLC — code generation, testing, security scanning, documentation — but without a shared orchestration layer, these agents create fragmented outputs that programme leaders must still reconcile manually.

NTT DATA's approach treats Atlassian as the agent control plane for programme delivery — the single system of work where Rovo agents, third-party AI tools and human decision-makers coordinate across workstreams in real time. Grounded in the Teamwork Graph, our multi-agent workflows understand team structure, capacity, dependencies, and historical delivery patterns — turning isolated AI capabilities into a governed delivery pipeline. In this session, we'll bring to life multi-agent orchestration triggered at the programme level: from ideation to delivery to release and everything in between!

Key Takeaways:

• Multi-agent orchestration in practice — How to design delivery workflows where multiple specialised agents (Atlassian-native and third-party) delegate, sequence, and validate each other's work across a complex programme, with Jira as the orchestration engine.
• The Teamwork Graph as context backbone — Why grounding agents in organisational context (team structure, historical velocity, dependency maps) delivers materially better outcomes than prompt-engineering alone, and how this applies to cross-team programme coordination.
• Governing AI in delivery without replacing human judgement — A practical framework for where agents decide autonomously, where they escalate, and how programme leaders retain control while eliminating 30%+ of manual coordination overhead.

This is a sponsored session. Badge scanning is optional. By having your conference badge scanned, you are opting in to be contacted by the sponsor. You will be subject to the sponsor’s communications and privacy policies and must contact them directly if you later wish to change your preferences.

• Learn how FastShift, Atlassian's migration accelerator, can help bring your critical customisations to Atlassian Cloud, supporting your unique needs and helping you realise cloud value faster
• Gain practical guidance on evaluating existing Data Center customisations and deciding what should be retired, rebuilt, or reimagined
• Discover how the Atlassian Platform and Forge can help overcome complex technical challenges, modernise existing functionality, and unlock new opportunities beyond the Data Center environment

Traditional IT support is reactive — employees hit an issue, raise a ticket, and wait. Proactive service management in Jira Service Management changes the game by detecting device issues before they impact employees, automatically remediating where possible, and guiding employees through resolution when automation isn't available.

In this 30-minute session, we'll show how proactive service management brings digital employee experience capabilities into JSM — from admin setup and sensor configuration to silent saves, consent-based fixes, and guided remediation delivered through Rovo desktop. See how IT teams can reduce ticket volume, cut downtime, and prove ROI with proactive support.

• Explore the different modes built for different kinds of tasks and see how knowing when to use each one changes what your team can accomplish with AI every day
• See how Skills and other capabilities extend what Rovo Chat can do in context, so your sessions produce targeted artifacts connected to your team’s work
• Discover how AI Inbox and Spaces give you a single layer to manage your activity, surface approvals, and keep your organisation’s context connected so your team stays in control as AI does more

Native automation, Rovo Studio, and ScriptRunner can all solve an automation problem, but which one works best for which problem? In this 15-minute session, we walk through a simple selection framework for deciding which approach fits a given piece of work, using examples routed through it in real time.

Rather than a feature by feature challenge, the examples are framed around teams shared work, the kind of collection of processes, approvals, and edge cases any Jira admin will recognise. As each example runs through the framework, you'll see exactly what to use when, and why.

You'll also leave with an open invitation to bring your trickiest scenarios to the booth afterwards so we can work through the framework with you.

• A practical, repeatable framework for deciding between native automation, Rovo Studio, and ScriptRunner for a given task.
• A clear-eyed view of what Forge custom apps add to the mix, and the maintenance effort, skills, and time they require compared with the other options.
• Examples drawn from a team workflow, showing where each tool is the strongest fit for the job, plus a standing invite to bring your own scenario to the booth.

This is a sponsored session. Badge scanning is optional. By having your conference badge scanned, you are opting in to be contacted by the sponsor. You will be subject to the sponsor’s communications and privacy policies and must contact them directly if you later wish to change your preferences.

Portfolio reporting remains one of the last manual processes in many delivery organisations: assembled manually, often late, and open to challenge.

This session shows how Automation Consultants built a 12-agent AI estate to support PMO work across 11 concurrent client engagements, releasing roughly 25% of delivery capacity, and tripling throughput without adding headcount. Working across Jira, Confluence, Loom, and Tempo, with Rovo at the centre, and Anthropic’s Claude as the reasoning layer, the agents support knowledge capture, risk and issue management, budget tracking, status reporting, lessons learnt, resourcing, project provisioning, and proposal drafting.

You’ll see how the system is governed in practice, from the single orchestrating “super agent” that screens every finding, to the Human-in-the-Loop approval gate that keeps people in control before anything reaches Jira, Confluence, or a client inbox. The session will also cover why agent memory lives in state files rather than conversation history, making the setup easier to retire, rebuild, or move between models without losing operational context.

Key takeaways

• How to structure a 12-agent PMO in practice, including which PMO disciplines are safest to automate first.
• Why a single orchestrating agent makes severity, scope, and human approval easier to govern.
• How durable agent memory helps AI workflows survive model, version, and vendor changes.

This is a sponsored session. Badge scanning is optional. By having your conference badge scanned, you are opting in to be contacted by the sponsor. You will be subject to the sponsor’s communications and privacy policies and must contact them directly if you later wish to change your preferences.

Join us to close Team '26 and hear from customers who are reimagining what becomes possible when every person, project, and piece of work is finally connected — then stay for a surprise guest we think you'll love.