KEYNOTE Speaker
CORPORATE KEYNOTE SERIES
Dr. Kiran Tomlinson
(Senior Researcher, Microsoft Research)
Abstract: With generative AI emerging as a general-purpose technology, understanding its economic effects is among society’s most pressing questions. Existing studies of AI impact have largely relied on predictions of AI capabilities or focused narrowly on individual firms. Drawing instead on real-world AI usage, we analyze a dataset of 200k anonymized conversations with Microsoft Bing Copilot to measure AI applicability to occupations. We use an LLM-based pipeline to classify the O*NET work activities assisted or performed by AI in each conversation. We find that the most common and successful AI-assisted work activities involve information work—the creation, processing, and communication of information. At the occupation level, we find widespread AI applicability cutting across sectors, as most occupations have information work components. Our methodology also allows us to predict which occupations are more likely to delegate tasks to AI and which are more likely to use AI to assist existing workflows. Finally, we see an increase in occupation-level AI applicability our 9-month data period, driven primarily by people using AI for more varied tasks.
Dr. Rajesh Parekh
(Vice President of AI/ML, Intuit)
Prior to Intuit, Dr. Parekh was Director of Engineering at Google, where he led teams building large-scale computer vision and machine learning systems to create a highly accurate digital model of the real world. This geospatial model powers key Google products including Maps, Local Search, Ads, and Automotive Services. His work helped unlock the value of Google’s geospatial data assets, contributing over $1B in incremental Local Ads revenue.
Before Google, Dr. Parekh led Data Science and Analytics at Facebook (now Meta) for Applied Machine Learning and Video initiatives, where he played a key role in launching and scaling Facebook Live. He has also held leadership roles managing global engineering and data science teams at Groupon and Yahoo!. Earlier in his career, he developed data mining products for e-commerce at Blue Martini and advanced data science solutions for insurance at Allstate.
Dr. Parekh earned his Ph.D. in Computer Science with a specialization in Artificial Intelligence from Iowa State University. He remains active in the academic community, delivering keynote talks, serving on organizing committees for leading international conferences, authoring more than 30 peer-reviewed publications, and filing multiple patents.
Title of the talk: From “Do-It-Yourself” to “Done-For-You”: Architecting AI and Human Intelligence for 100 Million Customers
Abstract: For decades, managing personal and business finances has been defined by manual data entry, complex paperwork, and high anxiety. Today, the expectation has shifted: customers no longer want software that helps them do the work; they want intelligent systems that do the work for them.
In this talk, I will share the company’s transformative journey in building an AI-driven expert platform that delivers seamless, “done-for-you” experiences to approximately 100 million consumers and businesses with TurboTax, Credit Karma, QuickBooks and Mailchimp. By uniquely combining Artificial Intelligence with Human Intelligence (HI), Intuit is redefining financial technology experiences. The impact of this architecture is massive: for example, AI-driven automated tax filing within TurboTax saved consumers an estimated 6 million hours of work in a single tax season and our AI-powered agents enabled small business owners to save up to 12 hours every month that could be reinvested in growing their business.
Moving from high-level strategy to technical execution, I will take a deep dive into the advanced document intelligence technology behind the frictionless experience Intuit delivers for tax filers, and the AI agents that use AI and HI to deliver autonomous workflows for “done-for-you” accounting intelligence.
Aurelie Saada
(AI Transformation ,Microsoft, USA)
Bio: Aurélie Saada is a global leader in AI business transformation and Director of Business Operations at Microsoft. She leads large-scale initiatives to operationalize agentic AI, helping organizations move from experimentation to measurable business impact. Her work combines AI adoption, governance, and ROI frameworks to drive scalable transformation across enterprise environments. She specializes in operationalizing AI, from strategy to execution, helping organizations translate emerging technologies into measurable business outcomes.
Aurélie has deployed multiple AI-driven solutions that have delivered significant productivity gains and improved decision-making across global teams. With over two decades of experience across financial services and technology, she brings a strong foundation in risk, operations, and strategic execution, redesigning ways of working.
A passionate advocate for human-centered transformation, Aurélie focuses on empowering individuals and leaders to embrace AI with clarity, confidence, and purpose. She is also a leader in the Women at Microsoft community, championing inclusive innovation and the next generation of digital leaders.
Title of the talk: Turning AI Innovation into Enterprise Scale: Why AI Transformation Is a Human Problem
Abstract: AI transformation is not failing because of technology, it is failing because organizations are not redesigning how people work. This keynote explores how enterprises move from AI experimentation to real business impact, based on hands-on experience deploying AI agents and transformation frameworks at scale. It introduces a practical playbook built on three pillars: uncovering hidden AI talent within teams, starting with focused pilots that prove ROI, and building a culture of experimentation that drives adoption. The session emphasizes a critical shift: from asking ‘What can AI do?’ to reimagining how AI elevates human potential. It demonstrates why human-centered leadership and inclusive approaches are not optional, but the key differentiator for successful AI transformation.