Banks are rushing into AI, but Atlassian claims businesses are still struggling to turn the AI boom into real company-wide productivity gains, as the software giant pushes deeper into workplace automation with a new generation of AI agents.
Individual vs. Organisational Productivity Gap
According to the software giant's chief AI officer, Tamar Yehoshua, most companies have moved beyond simply experimenting with AI tools, yet many were still failing to embed them into the day-to-day running of their organisations.
"Individual productivity is increasing, but not the overall productivity of the organisation," Yehoshua told City AM. "That's the big gap right now."
The comments come as firms globally face mounting pressure to justify huge spending on AI software, amid growing scrutiny over whether the technology is genuinely delivering measurable returns. Atlassian's products, including Jira and Confluence, are used by 85 per cent of Fortune 500 companies, as the firm bets that the next phase of AI adoption will be driven by agents.
Atlassian's AI Expansion
The Australian tech company recently announced a raft of new AI products centred around its workplace data layer that maps how companies operate across projects, documents, meetings, tickets and employees. The system now contains more than 154 billion connections spanning Atlassian products and external platforms like Microsoft, Google and Figma, according to the company. Yehoshua described it as "a map of how organisations work".
"We understand the connections between people, projects, documents, tickets and workflows," she said. Atlassian also recently announced it would open the teamwork graph to external AI agents and copilots through new developer tools and integrations with Microsoft Teams and Copilot.
The Rise of Workplace Agents
Silicon Valley is shifting away from AI assistants that simply answer questions and towards systems that can actively perform work. "The agents are more powerful because they take action," Yehoshua said. "You're not doing just a one-off query anymore. You're doing something that has an action associated with it."
She described internal use cases where AI agents analyse customer meeting transcripts, identify recurring complaints, create Jira tickets, assign tasks to engineers and draft follow-up emails automatically. "Nobody writes the first draft of documents anymore," she said. "Product managers don't write help documents anymore. They say: 'Read all the design docs, look at the code and write a draft of this.'"
Mercedes-Benz has already used Atlassian's agents to process bug reports from vehicle test fleets, improving report quality by 90 per cent while cutting duplicate detection time by 85 per cent, according to the company.
Debate Over AI's Impact on Workloads
The push comes amid a wider debate over whether AI will reduce workloads or simply increase expectations on workers. Businesses have been increasingly warned that productivity gains from AI could end up fuelling more work rather than less, a modern version of the 'Jevons paradox', where efficiency gains simply lead to higher output demands.
Yehoshua argued AI should instead free employees to focus on more strategic work: "A product manager used to have to take notes in meetings, send out action items, file bugs and write documentation. They don't have to do those things anymore," she added. "They can spend more time with customers and focus on what we should be building."
Data Privacy and AI Training
The company's AI expansion also comes amid growing scrutiny over how enterprise software groups use customer data to train AI systems. Atlassian recently disclosed plans to collect certain metadata and in-app data from customer cloud products unless enterprise customers opt into stricter controls.
Yehoshua said Atlassian does not build its own large language models and instead routes tasks through an AI gateway, capable of connecting to dozens of third-party models depending on cost, performance and task requirements.
Cultural Adaptation Over Skills Shortage
Despite mounting concerns over job displacement, Yehoshua said the bigger challenge for businesses was adapting culturally to AI rather than dealing with a technical skills shortage. "People have done their jobs in a certain way for decades," she told City AM. "The people who embrace it and say 'this is really cool, I want to learn about it' – they succeed."
