The AI Con USA Virtual Attendee Experience

K1

Erica Greene
Yahoo News

KEYNOTE | Best Practices for Using AI for Structured Data Extraction

Structured data extraction, or data tagging, is one of the easiest and impactful applications of modern AI. Before the wide availability of pre-trained AI models, the process of “understanding” unstructured data either required constructing complex heuristic logic or investing in a machine learning team who could train models in-house. Now, cheap and powerful tagging machines are an API call away, redefining what is possible for how we can understand our data. In this talk, I'll share how we’ve used AI at Yahoo News to improve our content understanding pipelines. Yahoo was a pioneer in applying machine learning to large-scale content understanding problems, giving us a fascinating case study to compare systems built with traditional ML approaches to solutions built on modern AI techniques. (Preview: LLM-only solutions are not always the best tool for the job). I’ll share our successes, failures, how the hell to evaluate these things and what we’ve learned along the way.

K2

Sida Peng
Microsoft

KEYNOTE | The Impact of AI on Developer Productivity

Generative AI tools hold promise to increase human productivity.  In the world of software development, GitHub Copilot was one of the first practical applications of the use of generative AI to support developer productivity.  However, measuring software productivity is non-trivial.  For example, developer productivity gains is more than just producing code faster. If these artifacts don’t meet quality standards or themselves bring cost efficiency challenges then there may not be much overall improvement. To truly understand the benefits and challenges of AI-powered copilots requires real-world experimentation.  Join Sida Peng as he presents results from a controlled experiment on GitHub Copilot. During this controlled experiment, recruited software developers were asked to implement an HTTP server in JavaScript as quickly as possible. Programmers with access to the AI pair programmer using generative AI completed the task 55.8% faster than those who did not have access. But what does this mean for us as software practitioners?  Is our future destined to be filled with AI pair programmers? Will they only support junior engineers transitioning into software development, or are they sophisticated enough to also help more senior engineers grow in the discipline? Sida will explore these topics and more surrounding the future of AI for software development.

K3

Andreas Bohman
University of Washington

KEYNOTE | AI at Scale: Balancing Innovation, Governance, and Risk in Large Organizations

As AI reshapes industries, large organizations must scale innovation while upholding governance, security, and ethical responsibility. Deploying AI at scale isn’t just a technical challenge—it’s a strategic balancing act between agility and compliance, risk and reward. Andreas Bohman, CIO at the University of Washington, will discuss strategies to drive AI-powered innovation without compromising regulatory obligations, operational effectiveness, or public trust. He will share governance strategies that enable innovation rather than restrict it. He’ll also talk about addressing critical risks like bias, data security, and compliance while ensuring that the way you apply AI aligns with organizational goals. Drawing from real-world experience, Andreas will explore how to navigate stakeholder expectations, foster trust in AI-driven decisions, and build a culture that embraces responsible AI at scale. Whether you're a technology leader, policymaker, or practitioner, this session offers a candid look at the complexities of enterprise AI adoption—and how to get it right.

K4

Dona Sarkar
Microsoft

KEYNOTE | AI for Real People—Panel

We have heard a LOT of hype about AI and AGI and ASI and all of the nonsense. But in year 3 of Generative AI, people are actually moving beyond talking and finding real value in AI. Come and hear from REAL AI implementers about how AI is having an impact on businesses across the board including small businesses, non-profits, big companies, and more.

K5

Venkata Kampana
Amazon Web Services

Tim Collinson
11:59

KEYNOTE | AWS Public Health Modernization: Leveraging GenAI for Government Innovation

Join Venkata Kampana, Senior Solutions Architect from the AWS Health and Human Services team, and Tim Collinson, the CTO of 11:59, an AWS consulting partner, for an insightful discussion on transforming public health systems across federal, state, and local governments. This session will showcase real-world implementations of GenAI and AWS technologies that are revolutionizing public health operations. They will demonstrate innovative solutions, including their IDP implementation utilizing Bedrock's Data Automation (BDA) feature with confidence scoring and bounding box capabilities, extraction of critical health data from electronic case reporting (eCR) documents via Bedrock, and advanced visualizations powered by Amazon Q in QuickSight. Through practical case studies, attendees will gain valuable insights into how these technologies can enhance data processing, analysis, and decision-making in public health environments.

K6

Mary Thorn
S&P Global

KEYNOTE | Five Ways to Operationalize AI at Scale

Enterprises often struggle with how to incorporate AI and machine learning in a repeatable, sustainable manner. In today’s competitive landscape, AI is no longer just a trend but a necessity. Generative AI has quickly become an essential tool for businesses—and with companies expected to explain its usage and justify any lack thereof—organizations are looking for ways to leverage AI at scale. This keynote provides a strategic roadmap to unlock the full potential of AI within organizations, focusing on cultural readiness, enablement, ethical considerations, and addressing biases. Attendees will gain actionable insights and frameworks to effectively and ethically operationalize AI.

K7

Marshall Belcher
Google

KEYNOTE | The Future of AI Agents

The future of AI agents is rapidly evolving, with increasing importance across diverse sectors. AI agents, defined by their current capabilities, are poised for significant transformation. Several key trends are shaping this future. Advancements in models are enhancing AI agent communication. Agent frameworks are evolving to make AI Agents easier to create and manage. Personalization and adaptability are driving the development of AI agents that learn user preferences and adapt accordingly. Simultaneously, ethical guidelines and responsible AI development are gaining prominence. Applications span industries such as healthcare, where AI agents aid in patient monitoring, diagnosis, and personalized treatment; finance, where they detect fraud, manage risk, and offer financial advice; customer service, where they automate support and enhance customer experience; and education, where they personalize learning. Challenges include the need for robust data protection and safety measures. Opportunities lie in fostering human-AI collaboration to maximize productivity. In conclusion, AI agents possess transformative potential, necessitating a forward-thinking approach to their development and adoption.