At Team ’26 Anaheim, Exalate saw rising enterprise demand for bidirectional ServiceNow-to-Jira synchronization, Jira Service Management escalations, migration coexistence, and controlled cross-company collaboration. As Atlassian moves deeper into AI-native teamwork with Teamwork Graph, Rovo, and Agents in Jira, the integration layer becomes more important: AI needs context, but enterprises need control.
When AI Joins the Team, the Sync Layer Matters More
California sun, a packed expo floor, and thousands of Atlassian ecosystem players gathered around one of the biggest questions in enterprise work right now.
What happens when AI becomes part of the team?
At Team ’26 Anaheim, Atlassian put context at the center of the AI conversation. Teamwork Graph, Rovo, Agents in Jira, Rovo Studio, and the broader AI announcements all pointed in the same direction: the future of work depends on how well organizations connect the people, systems, history, and decisions behind every task.
Great. We love a good graph.
But enterprise work has a habit of wandering outside the neat lines: ServiceNow-to-Jira synchronization, JSM escalations into engineering, migration coexistence between old and new systems, and secure cross-company collaboration with vendors and customers.
That is where Team ’26 got interesting for Exalate.
Service management is becoming more central. AI-supported work is moving quickly. Enterprise teams are working across more tools, not fewer. Migrations are still active, sensitive, and full of operational risk.
Every conversation resolved to the same epic: control.
Control over data.
Control over workflows.
Control over migration risk.
Control over cross-company collaboration.
Control over what each side shares, keeps, syncs, and owns.
That is the layer Exalate lives in.
ServiceNow and Jira Are Both Staying in the Room
While the keynotes promised a flawless, unified AI future, the conversations at our booth were grounded in immediate, messy enterprise realities.
The single hottest topic? ServiceNow (SNOW) <—> Jira Service Management (JSM).
Service teams work in ServiceNow. Engineering teams work in Jira. Customer-facing teams may live in Jira Service Management. External vendors may use something else entirely. None of those teams want to lose their system of record. None of them can afford to lose context.
They need the systems to sync securely, reliably, and selectively.
These are daily operating problems, not abstract integration scenarios.
Yet, there are surprisingly few robust options in the market that can handle this specific, high-stakes pipeline.
Then there’s the M-word: Migrations.
You might think the migration wave crested two years ago, but the ground truth says otherwise.
Our migration breakfast, hosted together with our partners Trundl and Isos Technology, was packed.
The room worked because the topic was specific.
Enterprise migrations are rarely a clean, weekend cutover. They involve active tickets and open incidents, deep technical debt, historical compliance records, and external vendor dependencies. Because of this complexity, teams need coexistence. They need old and new systems running side-by-side, validating workflows and keeping engineering aligned while the plane is being built mid-air.
That is where synchronization becomes useful before, during, and after the migration.
The hype cycle might have moved to AI, but enterprise IT is still in the trenches, trying to get its core infrastructure in order.
Uber Freight’s ServiceNow-to-JSM migration showed the same principle in practice: the safest migrations do not ask teams to stop working while systems change. With Exalate, Uber Freight moved around 130,000 tickets into Jira Service Management, kept the service desk running, and used parallel sync to validate the move before cutover.
Trends from the Booth Radar
The patterns that caught our attention.
ITSM-to-dev handoffs
ServiceNow-to-Jira conversations just kept finding us. Service teams work in ServiceNow. Engineering teams work in Jira. When a high-priority incident needs development input, the handoff has to be fast, clean, and visible on both sides. Without sync, teams fall back on copy-paste updates, Slack chasing, and two tickets that drift apart when clarity matters most.
JSM escalations
Jira Service Management often sits close to support, service, and customer-facing teams. Jira sits closer to engineering delivery. When a ticket needs engineering input, the escalation path has to preserve customer context, ownership, and status visibility. Without sync, the support team loses traceability exactly when the customer is waiting for an answer.
Change management
ServiceNow often owns the CAB (Change Advisory Board) approval process. Jira owns the implementation work. When approvals, risk notes, and development progress stay disconnected, teams lose the audit trail between decision and delivery. For compliance-heavy environments, that gap becomes a real risk.
Cross-Company Collaboration
Large enterprises using ServiceNow often need to work with clients, vendors, or delivery partners using Jira. Neither side wants to move systems. Neither side should have to. A controlled sync becomes the bridge that lets both sides collaborate while keeping their own workflows, permissions, and reporting intact.
The Hidden Tax of DIY Sync
Two contrasting stories from the floor made the business cost especially visible.
| The High-Maintenance DIY Engineers build a custom API bridge. ▼ Quietly drains dev capacity with every update and schema change. | The Manual Middleware Problem Teams copy-paste data manually. ▼ Massive loss of time, context, and sanity across departments. |
At first, that sounds like a success story.
The team had a problem. Engineering solved it. The systems connected.
But over time, the integration became its own burden. Every system update, API change, new workflow, new field, or new business requirement pulled engineers back into maintenance mode. The bridge kept running, but only because the team kept feeding it time. The cost of keeping the integration alive started eating into the value it was supposed to create.
That is one failure mode: the custom integration that technically works, but quietly drains engineering capacity over time.
Another large enterprise described the opposite problem.
They were still handling ServiceNow-to-Jira handoffs through email, copy-paste, and manual follow-up. People on both sides were acting as middleware between systems.
Different setup. Same root cause. Enterprise work moves across tools faster than the systems around it can support.
That gap is where teams lose time, context, and control.
AI Needs the Work Story, Not Just the Work Item
Atlassian is pushing deeper into AI-supported work, agents, service workflows, and connected context across its platform. AI agents were presented less like tools and more like participants in work.
That direction increases the importance of synchronization.
When AI supports planning, triage, routing, summaries, or service workflows, it depends on the quality of the context available to it.
A Jira issue without the related ServiceNow incident gives an incomplete operational picture.
A ServiceNow change request without the linked Jira implementation work leaves part of the story outside the system.
A partner escalation without the vendor-side update limits what the team can trust.
For enterprise teams, AI raises a practical question: what can the system see, and can teams trust what it sees?
That question brings the integration layer closer to the center of the workflow.
In AI-supported enterprise work, the synchronization layer is what determines whether agents see a complete work story or only a disconnected work item.
Teams need to know which data moves, which fields stay local, who owns the sync logic, and how changes are tested before they affect live work.
That’s the thing about needs: once they are met, they stop asking for your attention.
The best sync does not make itself the story. It gives teams one less thing to carry.
“The industry is moving from feature-heavy software toward workflow-first ecosystems. AI can reduce friction, but it only earns trust when people stay in control of the logic, the data, and the boundaries. Enterprises do not just want more automation. They want to know exactly what moves, what stays local, and who owns the decision.”
— Francis Martens, CEO of Exalate
Amsterdam Next
Atlassian’s direction is ambitious: AI in the flow of work, agents as teammates, and a system of work that gets smarter as teams use it.
That direction creates huge potential.
It also creates pressure.
Team ’26 Europe is a different opportunity and home ground for us.
The problems enterprises are bringing to conference floors haven’t been solved. ServiceNow and Jira still don’t talk to each other without help. Migrations are still mid-journey, messier than the project plan said they’d be. The bridge still needs to hold.
The future of work will not be powered by AI alone.
It will be powered by AI that understands the right context, acts within the right boundaries, and moves across systems without breaking the trust teams rely on.
That is the layer we care about.
See you in Amsterdam. Bring the messy use case. We’ll keep the details intact.
Questions From the Floor. Answers We Actually Have.
Why does AI make enterprise integration more important?
AI agents rely on connected context. If incidents, change requests, implementation work, and partner updates live in separate data silos, AI can only see part of the operational picture. Cross-system integration ensures your AI tools are working with the full story, not just a fragment.
Why is ServiceNow-to-Jira synchronization a major enterprise use case?
Many enterprises use ServiceNow for ITSM and Jira or Jira Service Management for engineering, support, and delivery work. Synchronization acts as the operational bridge, keeping both sides perfectly aligned in real time without forcing either team to abandon their preferred environment.
What is migration coexistence?
Migration coexistence means old and new systems run in parallel while teams validate workflows, preserve operational continuity, and choose a safer cutover moment.
What does Exalate add to Atlassian’s AI story?
Exalate helps bring reliable data from external systems into Atlassian environments while allowing each side to control what moves, what stays local, and how synchronization logic behaves.