AI Con USA 2026 - AI Leadership

AI in software delivery is no longer just about experimenting with copilots or generating code faster. It is about changing how software is imagined, specified, generated, validated, governed, and improved. As AI continues to be used for producing prototypes, requirements, code, tests, documentation, deployment artifacts, and operational insights, the software lifecycle shifts from a sequence of handoffs into a continuous learning loop. The real opportunity is therefore not only about leveraging AI tools, but adopting a new working model for transforming intent into trusted outcomes. Join...

Scientific discovery faces a major bottleneck: while generative AI has transformed information processing, it has not yet unlocked comparable acceleration in understanding the physical world. Traditional computational chemistry and materials modeling remain too slow, expensive, and limited to power large-scale innovation. SandboxAQ tackled this challenge by developing Large Quantitative Models (LQMs) — a new class of AI models that merge machine learning, physics-based simulation, and quantum-inspired algorithms to model molecular and material interactions at unprecedented speed and...

Advances in robot learning and affordable general-purpose hardware are changing physical work faster than any past wave of automation. Industrial robot arms transformed repetitive factory tasks, but they could only operate in tightly controlled settings. Now, new learning methods and off-the-shelf mobile robots make it possible to teach machines to perform many kinds of hands-on work in warehouses and logistics facilities. This session looks at where the technology stands today, what has changed, and what the next few years will bring. Attendees will learn how to spot real opportunities...

We are entering a defining chapter for bioscience—one where AI is no longer an accessory, but a core engine of discovery. At the Allen Institute, AI is being woven throughout the scientific process empowering research teams to analyze complex biological systems at scale. Their teams are collaborating to develop frontier AI applications like advanced computer vision to interpret high-resolution imaging data, multimodal models that integrate complex molecular, cellular, and physiological signals, as well as intelligent systems to assist researchers as they navigate and synthesize vast...

Learn how to move faster and safer with your AI projects. Whether you are using AI to help create applications with Github Co-pilot, Cursor, one of the other expanding code generation AI tools, or you are developing agents and utilizing various LLMs to support them, using feature flags can provide the ability to test multiple variations in production while providing a safety net that allows you to quickly resolve issues in production. AI is moving fast and the number of options available to you is increasing daily. Join the session to learn how you can validate and experiment with various...

Borrowing from tabletop games, this session transforms AI leadership into a live-action adventure. Each team faces challenges drawn from real-world case studies: biased data, budget cuts, regulatory chaos, and “move-fast” culture. Every choice (and dice roll) reveals how easily good intentions can drift into poor outcomes. You’ll leave understanding why alignment isn’t a compliance checkbox, it’s a continuous act of human judgment. Key takeaways include: experience on how small trade-offs create large ethical ripple effects, applying alignment frameworks that balance business speed with...

Traditional software testing is fundamentally deterministic: the same inputs must always produce the same outputs. Yet many teams introduce AI into their testing without first defining the problem the AI is meant to solve, leading to brute-force experimentation and unreliable results. Google’s 2025 DORA report highlights that user-centricity is a prerequisite for AI success and that AI is most effective when it is pointed at a clear problem. AP shows you how that insight applies technically to testing. Before AI can be used as a testing tool, it must first be tested and understood in the...

Successful AI adoption is 10% technology and 90% organizational change—and most organizations are failing at the 90%. In this dynamic, experience-driven session, we will cut through the hype and get honest about what it actually takes to move AI from promising pilot to measurable business impact. Drawing on nearly three decades of technology leadership and his background as a U.S. Army Ranger, Shawn brings a battle-tested perspective to the modern boardroom: the same principles that forge elite units into high-performing teams are exactly what today's organizations need to win the AI...