Abstract: As AI becomes integral to business strategy, many organizations have struggled to navigate the delicate balancing act between technical complexity and business value, especially with the advent of generative AI. This is especially true in high-risk settings like healthcare, defense, and financial services.
In this session, actionable strategies for enhancing AI and data literacy among stakeholders, aligning AI projects with business objectives, and fostering trust between AI builders and users will be explored. While many strategies are applicable to both traditional machine learning and generative AI projects, special considerations for projects incorporating generative AI will also be explored.
Attendees will walk away with practical insights to propel AI projects from the design board to real-world impact and pave the way for a culture of informed and responsible AI innovation within their organizations.
Session Outline:
Participants will learn how to:
· Develop greater AI and data literacy among stakeholders and users
· Align between business outcomes and AI project goals
· Build trust and effective communication channels between AI builders and users
· Identify and communicate the potential risks and unintended consequences that arise from both traditional and generative ML models
Background Knowledge:
Suitable for all backgrounds - especially those looking to communicate more effectively with stakeholders, or stakeholders learning to get more comfortable with technical considerations.
Bio: Cal Al-Dhubaib is a data scientist, entrepreneur, and innovator in responsible artificial intelligence, specializing in high-risk sectors such as healthcare, energy, and defense. He is the founder and CEO of Pandata, a consulting company that helps organizations to design and develop AI-driven solutions for complex business challenges. Their clients include globally recognized organizations like the Cleveland Clinic, Progressive Insurance, University Hospitals, and Parker Hannifin.
Cal frequently speaks on topics including AI ethics, change management, data literacy, and the unique challenges of implementing AI solutions in high-risk industries. His insights have been featured in numerous publications such as Forbes, Ohiox, the Marketing AI Institute, Open Data Science, and AI Business News. Cal has also received recognition among Crain’s Cleveland Notable Immigrant Leaders, Notable Entrepreneurs, and most recently, Notable Technology Executives.
