At the recent Team ‘26 Europe gathering, Atlassian shone a spotlight on organizations that are reshaping the way work happens in an AI‑first era. The Impact Maker Awards recognized companies that have moved beyond experimentation to embed Atlassian’s platform deep into their operating models, delivering measurable gains in speed, quality, and employee experience. By honoring a diverse mix of global banks, utilities, telecoms, travel tech giants, automakers, media houses, and innovative startups, the awards illustrate how a unified system of work can serve as a catalyst for transformation across industries. The event underscored a clear message: when teams are equipped with tools that understand their context—knowledge, processes, and goals—they can break down silos, accelerate decision‑making, and focus on value‑creating activities. This year’s winners collectively demonstrate that technology adoption is most powerful when it aligns with strategic objectives such as regulatory compliance, sustainability, or customer experience, and when it is rolled out with thoughtful change management. The stories shared on stage provide a roadmap for any leader looking to harness the full potential of AI‑driven collaboration while keeping human ingenuity at the center. Leaders left the event with concrete examples of how aligning technology investments with clear business outcomes can create sustainable competitive advantage, encouraging them to replicate similar frameworks in their own contexts.
Beyond the celebration, the Impact Maker Awards serve as a benchmark for what mature AI integration looks like in large enterprises. Judges evaluated nominees on their ability to connect people, knowledge, and work through Atlassian’s suite—Jira, Confluence, Jira Service Management, and the newer Rovo assistant—while achieving concrete outcomes such as reduced cycle times, higher defect detection rates, or lower operational overhead. The winners illustrate a shift from point solutions to platform‑wide standardization, where data flows freely between development, service, and business functions. This interconnectedness fuels the emergence of agentic workflows, where AI agents can retrieve relevant documentation, suggest next steps, or automate repetitive tasks without pulling employees out of their flow. Moreover, the awards highlight the importance of measuring impact: winners reported quantifiable improvements like saved hours per month, increased adoption rates, or accelerated release cycles, providing a template for others to build business cases around AI investments. For technology leaders, the takeaway is clear—successful AI enablement hinges on a foundation of clean data, governed processes, and a culture that encourages experimentation and learning. Decision‑makers should therefore start by establishing baseline metrics and defining success criteria before launching any AI‑enabled initiative, ensuring that progress can be tracked and communicated effectively.
Morgan Stanley’s journey exemplifies how a financial institution can modernize its software delivery lifecycle at scale while preserving the rigor required in regulated environments. By migrating tens of thousands of developers from legacy on‑premise tools to Atlassian Cloud, the bank created a single source of truth for code, documentation, and project tracking. This consolidation eliminated the fragmentation that had previously hampered roll‑up reporting and made it difficult to enforce consistent practices across global teams. In parallel, Morgan Stanley rolled out Atlassian Rovo to thousands of practitioners—including developers, scrum masters, squad leads, and project managers—giving them an AI‑powered companion that can surface relevant knowledge, automate status updates, and recommend best practices based on historical data. Early feedback indicates that teams are spending less time searching for information and more time on coding and review, translating into higher throughput and improved code quality. The initiative also demonstrated the value of change enablement: targeted training, champion networks, and clear governance helped drive adoption without disrupting ongoing projects. For other financial services firms, Morgan Stanley’s approach offers a blueprint for balancing innovation with compliance, showing that a cloud‑first platform can coexist with strict audit trails and data residency requirements. Practitioners considering a similar migration should prioritize data cleansing early, establish a center of excellence for ongoing platform governance, and leverage pilot groups to refine rollout tactics before scaling enterprise‑wide.
Axpo, a leading European renewable energy producer, tackled a classic IT service management bottleneck by replacing an aging ITSM tool with Jira Service Management in under five months. The rapid migration was driven by a clear pain point: legacy systems were creating silos that slowed incident resolution and obscured visibility across IT, HR, and other support functions. By moving to a cloud‑native service desk, Axpo established standardized workflows, automated routing rules, and a self‑service portal that empowered employees to find answers without waiting for tier‑one support. The shift also unlocked the ability to link service requests with development work in Jira, enabling a seamless handoff when infrastructure changes are required. As a result, Axpo reported faster mean time to resolution, a reduction in duplicate tickets, and a noticeable uptick in employee satisfaction scores. Importantly, the project served as a catalyst for broader adoption: HR and finance teams began exploring similar Atlassian‑based solutions to streamline their own processes, demonstrating how a successful IT transformation can create a ripple effect across the enterprise. Axpo’s experience underscores the importance of aligning service management goals with overall digital‑workplace ambitions, especially in industries where uptime and sustainability are paramount. Organizations aiming to replicate this success should map existing service processes, identify quick‑win automation opportunities, and involve end‑users in design to ensure the new tools meet real‑world needs.
VodafoneZiggo pursued a different but equally impactful objective: strengthening collaboration between its business, marketing, and technology units to accelerate go‑to‑market initiatives. Recognizing that misaligned priorities often led to duplicated effort and delayed campaigns, the telecom operator invested in AI enablement through Atlassian’s Rovo and Loom video updates. By embedding Rovo into their Confluence pages and Jira boards, teams gained instant access to context‑aware summaries, actionable insights, and automated meeting notes, cutting the time spent on status‑gathering by an estimated 80%. Loom’s asynchronous video capabilities allowed product managers to convey complex ideas quickly, reducing the need for lengthy live meetings and accommodating diverse schedules across regions. Within five months, VodafoneZiggo observed a twenty‑fold increase in AI‑assisted interactions, correlating with a measurable drop in redundant work and a rise in cross‑functional initiative velocity. The initiative also fostered a culture of transparency, as recorded updates became searchable knowledge assets that new hires could leverage immediately. For organizations seeking to break down silos between commercial and technical teams, VodafoneZiggo’s strategy illustrates how lightweight AI tools, paired with clear communication norms, can transform collaboration without requiring massive process overhauls. Leaders should consider starting with a small pilot team, measuring time saved on routine updates, and gradually expanding the AI‑assisted workflow as confidence and proficiency grow.
Amadeus, a global travel technology provider, leveraged Atlassian Cloud to unify more than twenty thousand employees under a single digital workplace, thereby eliminating the fragmentation that had historically impeded cross‑border collaboration. The migration involved moving diverse teams—from airline IT specialists to airport operations staff—onto a common set of tools for project tracking, documentation, and agile planning. This consolidation enabled standardized practices such as shared sprint calendars, uniform definition of done, and centralized release dashboards, which in turn improved visibility into dependencies across regions. By retiring multiple legacy wikis and ticketing systems, Amadeus reduced the cognitive load on employees who no longer needed to juggle disparate interfaces to find information. The platform’s built‑in search and linking capabilities also facilitated knowledge reuse, allowing teams to build on prior work rather than starting from scratch. Amadeus reported accelerated delivery of new travel‑related features, higher employee engagement scores, and a clearer line of sight from strategic objectives to day‑to‑day tasks. Their experience highlights that a successful cloud migration is not merely a technical exercise but an opportunity to redesign how work is coordinated, especially for organizations with complex, geographically distributed product lines. Decision‑makers should conduct a thorough inventory of existing collaboration tools, define a target operating model, and implement a phased migration plan that includes comprehensive training and feedback loops to ensure adoption sticks.
Daimler Truck and Autodesk, though operating in different sectors, share a common pursuit: engineering excellence upheld by rigorous standards and innovative tooling. Daimler Truck, rooted in over a century of automotive manufacturing, undertook a modernization of its software engineering processes while adhering to strict safety and compliance mandates. By migrating to Atlassian Cloud, the company established unified version control, automated build pipelines, and integrated test reporting that collectively reduced the risk of non‑compliant code slipping into production. Simultaneously, Autodesk, a leader in design and creation software, shifted its enterprise footprint to the same cloud platform to foster more connected workflows across its global design studios. The move enabled real‑time co‑authoring of design documents, streamlined feedback loops between engineers and artists, and provided a single source of truth for asset versions. Both organizations emphasized change enablement—Daimler Truck through compliance‑focused training and Autodesk via purposeful adoption campaigns—to ensure that the new tools were embraced rather than resisted. The outcomes include shorter development cycles, higher first‑pass quality rates, and improved ability to scale engineering capacity in response to market demand. For engineering‑heavy enterprises, these cases demonstrate that a cloud‑based development platform can coexist with, and even enhance, the rigor required by industry‑specific standards. Leaders should invest in automated compliance checks, create cross‑functional communities of practice, and regularly review metrics such as lead time and escape defects to gauge the impact of their tooling changes.
Axel Springer, a multinational media conglomerate, took a distinctive approach by weaving Atlassian’s Teamwork Graph directly into the developer experience to curb context‑switching. By linking design assets, documentation, and delivery data within Jira and Confluence, creators could access the full provenance of a piece of content without leaving their workflow. This integration reduced the time spent searching for brand guidelines, image rights, or previous versions, allowing editors and designers to stay focused on creative refinement. Early metrics showed a notable drop in interruptive tasks and a corresponding increase in content output per sprint. Stellantis, on the other hand, tackled the challenge of coordinating software development across its multitude of automotive brands. The company consolidated a myriad of legacy tools into a single Atlassian‑based platform serving sixteen thousand engineers, thereby enabling cross‑brand code sharing, earlier detection of defects through shared test suites, and more predictable release cycles. The unified platform also facilitated the reuse of common components—such as infotainment modules or ADAS libraries—across different vehicle lines, driving cost savings and consistency. Both examples illustrate how a well‑architected toolchain can serve as a connective tissue, whether the goal is to preserve creative integrity in media or to synchronize complex product lines in automotive manufacturing. Leaders looking to harness similar benefits should map the information flow between creative and technical teams, identify integration points where a shared graph can reduce look‑ups, and pilot the approach in a single product line before scaling to the broader portfolio.
Santander’s award‑winning initiative centered on establishing a unified Application Lifecycle Management (ALM) and Software Development Life Cycle (SDLC) Center of Excellence to bring governance and compliance to the forefront of its retail and commercial banking technology stacks. By standardizing on Atlassian tools across thousands of developers, the bank created repeatable processes for code review, security scanning, and release management, which helped mitigate risk while accelerating delivery. The centralized CoE also provided a platform for sharing best practices, conducting audits, and aligning diverse teams on common metrics such as lead time and change failure rate. In parallel, DeepL, a company renowned for its AI‑driven translation engine, chose Atlassian as a scaling partner to support its rapid growth. Rather than building internal tooling from scratch, DeepL leveraged Jira and Confluence to manage product roadmaps, track linguistic model improvements, and coordinate global release schedules. The partnership allowed DeepL’s engineering teams to focus on advancing core AI research while relying on Atlassian for reliable project tracking and knowledge sharing. Both stories reinforce the idea that a robust work management foundation can serve disparate purposes—whether enforcing stringent financial regulations or empowering cutting‑edge AI innovation—by providing structure, transparency, and scalability. Executives should consider establishing a center of excellence that defines standards, provides ongoing support, and measures compliance alongside velocity, ensuring that speed does not come at the expense of risk management.
Canal+, a global media and entertainment group operating in seventy countries, used Atlassian Cloud to knit together its European broadcasting operations, consolidating service discovery and workflow management onto a high‑velocity, resilient foundation. By migrating disparate scheduling, rights management, and content delivery systems onto Jira‑based workflows, Canal+ gained real‑time visibility into program status, licensing constraints, and audience metrics. This transparency allowed the organization to react swiftly to market shifts, optimize ad inventory, and reduce the manual coordination that previously consumed significant operational bandwidth. The shift also facilitated the adoption of agile practices within traditionally waterfall‑driven broadcast teams, improving speed to market for new channels and on‑demand offerings. BarmeniaGothaer, an insurance carrier navigating a major industry merger, pursued a similar consolidation goal but with a focus on end‑to‑end service visibility. By migrating its complex insurance operations—claims processing, policy administration, and customer support—to a centralized Atlassian platform, the insurer achieved a single pane of glass for tracking incidents, managing SLAs, and reporting regulatory compliance. The unified system eliminated redundant data entry, improved handoff quality between departments, and provided actionable insights for process optimization. Both cases demonstrate that when organizations prioritize connectivity and transparency, they can unlock operational agility even in sectors traditionally viewed as legacy‑laden or heavily regulated. Leaders should start by charting end‑to‑end processes, identifying data silos, and selecting a platform that can support both structured workflows and flexible collaboration, then measure improvements in cycle time and stakeholder satisfaction to validate the investment.
AKDB, a provider of IT services to highly regulated EMEA public sector entities, showcased how strict data residency and security requirements can be met while still embracing cloud‑based modernization. By designing a deployment that kept sensitive data within designated jurisdictional boundaries and leveraging Atlassian’s enterprise‑grade security controls, AKDB delivered a trusted platform for citizen‑facing digital services without compromising compliance. Their framework has become a reference for other public‑sector organizations seeking to balance innovation with accountability. SpotOn took a more tactical route, deploying a single Atlassian Rovo agent to automate repetitive tasks such as ticket triage, knowledge base updates, and cross‑tool notifications. The agent’s ability to pull information from Jira, Confluence, and external systems and surface relevant insights saved the company roughly forty hours per month, allowing IT staff to redirect effort toward strategic projects like platform enhancements and customer‑facing feature development. Barclays, a global banking giant, used Atlassian as the backbone of its System of Work to scale engineering productivity and service management across a massive, geographically dispersed infrastructure. By standardizing on Jira Software, Jira Service Management, and Confluence, Barclays achieved clearer alignment between development and operations teams, reduced mean time to restore service, and fostered a culture of continuous improvement through shared metrics and retrospectives. Together, these narratives illustrate that whether the priority is regulatory adherence, time‑saving automation, or enterprise‑scale coordination, a flexible work management platform can be tailored to meet diverse objectives. Decision‑makers should evaluate their specific regulatory constraints, pinpoint repetitive tasks ripe for automation, and define clear ownership for platform governance to ensure sustained value.
The deepened alliance between Google Cloud and Atlassian, highlighted by Google Cloud’s recognition at Team ‘26 Europe, signals a growing trend toward best‑of‑breed cloud collaborations that combine infrastructure strength with specialized work‑management capabilities. By running Jira and Confluence on Google Cloud’s robust platform, organizations gain the scalability, reliability, and advanced data‑analytics services of Google’s infrastructure while retaining the collaborative intelligence of Atlassian’s suite. The integration of Google’s Gemini AI models further enriches the ecosystem, enabling smarter suggestions, automated content generation, and enhanced search relevance directly within the tools teams use daily. For leaders looking to emulate the award‑winning examples, the path forward involves three practical steps: first, conduct a thorough assessment of existing tool fragmentation and identify high‑impact use cases where a unified platform could reduce friction; second, invest in change enablement—training, champions, and clear governance—to ensure adoption sticks; and third, define measurable outcomes up front (time saved, defect reduction, release acceleration) and track them rigorously to demonstrate ROI and sustain momentum. By following this framework, any organization can begin to translate the promise of AI‑powered work management into tangible competitive advantage, just as this year’s Impact Maker Award winners have done. The final encouragement is to start small, learn fast, and scale what works, keeping the human element at the heart of every transformation.