Chicago CDAO Virtual Executive Summit

With the growing spotlight on data usage, data protection and responsible AI are now business imperatives. Hear how data leaders can implement responsible AI policies while balancing the needs of the business with ethical data use practices.

This boardroom discussion will explore:

• Addressing ethical challenges in AI for earning stakeholder trust
• Developing an organizational plan to address shifting regulations
• Managing the legal, practical and ethical consequences of responsible AI

Data literacy is essential for employing self-service analytics, yet many organizations continue to suffer from a lack of strategic prioritization.  Learn approaches on how to successfully improve data literacy and self-service analytics throughout your organization.

In this session you will explore strategies for: 

• Optimizing business data literacy to achieve an empowered analytics-driven culture

• Expanding data and analytics core competencies to increase self-service capabilities

• Providing quality data in an agile manner that accelerates value delivery

Join this informal and interactive networking session to connect with your Chicago CDO peers. In this session, the Chicago community will have the chance to share their takeaways from the program in small groups and walk away with at least one new connection.

The role of the CDO is repeatedly reimagined due to adapting business models, operations, and organizational challenges. Despite these rapid changes, foundational elements need to be in place to add business value and ensure the future success of the CDO. Join this session to hear how the trajectories of Christopher Boone from Abbvie and Kevin Salzmann of BMO Harris have been shaped by their backgrounds and where they see the CDO role going next in the face of faster and smarter transformations and data ecosystems. 

Machine learning models can turn from asset to liability when faced with conditions not encountered in training data sets. Currently, most companies do not understand the need for operationalizing ML, or are struggling to deliver, observe and improve production of ML solutions. As ML matures from research to applied solutions, MLOps can be introduced to trace the data pipeline for improved overall model quality while accommodating for changing conditions and robust governance frameworks.

In this session you’ll explore:

• Challenges to deploying machine learning models and how to overcome them
• Mastering an adaptive governance framework to minimize risk and accommodate evolving regulatory compliance
• Capturing and quantifying value realized by implementing MLOps solutions

2020 has turned predictive models on their heads. Machine learning and AI tools are more important than ever, as they are increasingly embedded in customer analytics and digital experience platforms. Learn from your peers about how they are using new technologies to improve these customer experiences in the new era.

In this session we’ll discuss:

• Use cases for augmented analytics
• Benefits from these technologies and how to measure their success
• Personalization and privacy issues to avoid along your AI/ML journey

Today’s leaders are challenged to re-envision business models, embrace new ways of engaging customers, empower employees, optimize operations and transform products and services. Hear how your peers are employing new technologies that fuel data driven solutions to these challenges within their organizations.

In this session, explore strategies for:

• Building a confident employee community that uses data to fuel innovation and critical decision making
• Balancing broad access and use of data with governance, compliance and ethical use
• Utilizing best in class technologies to improve scalability and productivity of data management activities