Scaling AI across the software development lifecycle (SDLC) is no longer optional; it’s becoming a top priority for engineering leaders under pressure to deliver more with less. While the potential for AI to accelerate productivity, improve quality, and transform developer experience is immense, many organizations are still struggling to move from experimentation to real, scalable impact. Challenges can range from integrating AI into existing workflows and toolchains to gaining developer trust and adoption to demonstrating measurable business value.

Join Tanya Chen, Head of Engineering, Work Management at Atlassian, and engineering leaders across the industry for a discussion on candid perspectives on what’s working, where they’re still hitting roadblocks, and what it really takes to unlock AI’s promise at scale.

• Explore the challenges engineering leaders face when scaling AI across the SDLC, from integration to adoption to measurable outcomes.
• Discover insights and lessons learned from industry leaders on balancing AI’s potential with developer trust, productivity, and long-term business goals.
• Learn actionable strategies for overcoming roadblocks and driving sustainable AI impact across engineering organizations.