In large software organizations, even a small change can affect thousands of users. Managing changes like ensuring updates are smooth, safe, and well-communicated, is a delicate process that defines how much customers trust the product. At Atlassian, known for its global collaboration tools like Jira and Confluence, this work is central to its success. Helping reshape how it’s done is Abhishek Sharma, Senior Engineering Manager, who has been applying Artificial Intelligence (AI) to make enterprise change management more efficient and predictable.
For years, the organisation’s release process depended on engineers manually reviewing updates, assessing their impact, and creating detailed documentation for customers. It worked, but it was slow and prone to inconsistencies. “Customers want predictability and control,” Sharma says. “But achieving that used to mean a lot of repetitive manual effort.”
To solve this, the professional developed a Knowledge Graph along with his team— a connected data model that links code changes, Jira issues, and Confluence documentation. On top of this, AI systems now automatically assess the potential impact of every change, generate release notes, and route them for review. What once required hours of human effort is now completed in minutes.
As the manager shared, the shift has produced clear results. The firm has achieved roughly 30% cost savings across its release cycle, alongside faster delivery and fewer errors. For customers, the change means more transparent communication and smoother updates. “It’s not just about doing things faster,” he notes. “It’s about building trust. When customers understand what’s changing and why, their confidence grows.”
This transformation wasn’t without challenges. On the technical side, integrating data from multiple platforms into one reliable system required deep engineering effort. On the human side, moving from manual processes to AI-assisted workflows demanded cultural change. Sharma worked closely with teams across the company, leading training sessions and building understanding around how automation could enhance, not replace, human decision-making. “When people see that AI removes repetitive work and helps them focus on what matters, adoption follows naturally,” he says.
Beyond this work, he has contributed to the broader discussion on automation and intelligent systems through his published research papers on software automation, knowledge-driven systems, and scalable AI adoption in enterprise environments, including “Automating Software Release Notes with AI: A Comparative Study of Agent-Based Systems vs. LLM Fine-Tuning Approaches” and “Proactive Change: Integrating Predictive Analytics into Software Change Management Frameworks for Agile, Data-Driven Transformation”.His academic insights continue to inform his practical work, blending theory and real-world application to create smarter, more reliable systems.
This combination of research and hands-on leadership reflects a shift in how companies are approaching technology today. Instead of viewing AI as a distant concept, leaders like Sharma are embedding it into everyday operations to improve speed, quality, and customer experience. “AI gives us the ability to manage complexity without losing control,” he says. “It lets us move fast, but with care.”
Looking ahead, the expert agrees with other industry leaders in seeing a future where enterprise release management becomes even more adaptive. Systems will learn from past data, predict risks, and personalize processes to match customer needs and business priorities. “Change management will move from being reactive to proactive,” he adds. “We’ll spend less time fixing issues and more time preventing them.”
As software delivery continues to change, the above experience offers a glimpse of how the partnership between human intelligence and machine learning can create stronger, more transparent systems. In merging minds and machines, the goal isn’t just smarter technology, it’s building smarter collaboration between the people who create software and those who rely on it every day.
