CDO Institute: USA

As businesses & society alike continue to embrace the vast potential of Artificial Intelligence, ethical considerations are becoming increasingly crucial. From the ethical collection and use of data to the responsible deployment of AI technologies, striking a balance between innovation and moral responsibility has emerged as a pressing concern for data professionals globally. .

This panel discussion will bring together leading experts & thought leaders from various fields to delve into the complex intersection of Data, AI, and Ethics. The panelists will explore some of the following key topics:

• How can we ensure that data is collected responsibly, while safeguarding individual privacy and preventing potential misuse?
• AI systems are only as unbiased as the data they are trained on. How can we address algorithmic bias and ensure that AI technologies promote fairness and inclusivity?
• As AI systems become more complex, the "black box" nature of some algorithms raises concerns about transparency and accountability. How can we enhance explainability and interpretability in AI models?
• With AI increasingly influencing critical decisions in various domains, including healthcare, finance, and criminal justice, how can we establish robust frameworks to ensure these systems do not lead to unintended consequences or reinforce existing biases?

This session delves into essential strategies that Data professionals must adopt to facilitate widespread access to valuable insights, enabling organizations to make well-informed decisions efficiently.

Key discussion points include:

• Educating stakeholders on the significance of data and equipping employees with data-driven insights to foster informed decision-making throughout the organization.
• Leveraging advanced analytics techniques and machine learning models to identify patterns, trends, and predictive insights within the data.
• Promoting a collaborative and data-driven environment by granting all stakeholders across the organization access to valuable data.
• Developing intuitive self-service analytics platforms that enable stakeholders to autonomously access and derive insights from data, streamlining the decision-making process.

Join this session as we explore how to effectively communicate the value of AI and data analytics projects to leadership, specifically focusing on demonstrating ROI and quantifying the benefits to the organization. We will explore key elements of a successful communication strategy, encompassing understanding your audience, framing your message, and utilizing data to substantiate your claims.

Key discussion points include:

• Discover how to construct a clear and persuasive business case for your AI and data analytics projects by utilizing data-driven metrics to measure success. Learn how to effectively showcase the tangible benefits and demonstrate a strong ROI.
• Leveraging Effective Storytelling Techniques: Master the art of storytelling to captivate leadership's attention and effectively communicate the value of your projects. Understand how to craft a narrative that highlights the impact of AI and data analytics on strategic business outcomes.
• Identifying quick wins within your use cases to showcase immediate ROI. Explore how highlighting early successes can build confidence, gain buy-in, and pave the way for broader project support.
• Articulate how your AI and data analytics projects directly contribute to driving strategic business outcomes. Learn how to align your initiatives with the organization's goals and priorities to secure leadership's endorsement and support.

Hosted by Chitrang Dave, Senior Director, Enterprise Data & Analytics with Edwards LifeSciences.

Hosted by Husain Misherghi, Director of Analytics & Analytics Engineering at Upstart.

In this session we will be discussing how best to help businesses design and implement data strategies that improve decision-making, customer experience, and operational efficiency. Thanks to information provided by data experts, we'll be aiming to identify and discuss the variety of opportunities that there are to use data more effectively and implement innovative data solutions that deliver tangible results.

Increasingly senior executives are pushing new machine learning initiatives to drive business value, leaving Chief Data Officers responsible for finding new ways to accelerate its adoption across the entire lifecycle, from data preparation to model deployment. This session will explore key strategies that CDOs must take to build a framework that enables them to develop, test, and deploy machine learning models at scale.

• What are the best tools for data cleaning and transformation in order to pre-process raw data?
• Creating a structured data pipeline that can handle large volumes of data.
• Developing and testing machine learning models, focusing on accuracy, performance, and scalability
• Deploying and scaling machine learning models effectively.
• Implementing a Continuous Integration and Deployment pipeline for machine learning models, allowing for automated testing, deployment, and monitoring
• Considering ethical considerations including bias, fairness, and transparency to ensure that models are ethical and unbiased.

Join this engaging session to discuss the pivotal role of the CDO in successfully implementing and integrating Artificial Intelligence AI solutions in order to reduce costs and identify opportunities. As organizations navigate an increasingly complex and data-driven landscape, the CDO's expertise in AI utilization is vital for driving organizational efficiency and functionality across various business domains. Throughout this session, we will explore how the CDO can leverage AI to identify and mitigate risks, such as fraud detection, cybersecurity threats, and compliance breaches. By harnessing the power of AI, organizations can proactively address these challenges, ensuring enhanced security, streamlined operations, and improved risk management.

• Highlighting how AI can optimize operational processes, automate routine tasks, and improve overall efficiency, allowing organizations to allocate resources more effectively and focus on strategic initiatives.
• Exploring the broad return on investment potential of AI-powered risk management, including cost savings, revenue growth, improved decision-making, and enhanced customer experiences.
• Discussing how AI can provide organizations with a competitive edge, enabling them to adapt to changing market dynamics, identify emerging trends, and make data-driven decisions for long-term success.

Instances of weak insights, data breaches, and ethical concerns have eroded trust in data strategies. In response, data leaders are actively working to regain this trust through comprehensive data strategy reviews. This session emphasizes the importance of collecting the right data, enhancing accessibility, and promoting data literacy across the organization. Join us as we provide practical insights and strategies to empower you to rebuild trust in your data strategy.

Key Discussion Points:

• Focus on a foundation built with core pillars of governance, transparency, and accountability to restore confidence in data strategies.
• Implement robust data governance frameworks and improve data transparency and communication to ensure data integrity and compliance.
• Foster ethical data practices and responsible decision-making to establish a trustworthy data strategy.
• Partner with communications to distribute data-driven insights effectively through compelling data storytelling, ensuring meaningful understanding and impact.

Join this insightful panel discussion as industry leaders share their experiences and expertise in harnessing the power of data, analytics, and AI to drive innovation and success. The session will delve into real-world case studies, showcasing how organizations have effectively utilized data and cutting-edge analytics to achieve strategic objectives. Additionally, the panellists will shed light on the role of emerging technologies in reshaping the landscape of data-driven decision-making and the future possibilities they present.

Key Discussion Points:

• Real-Life Case Studies of Data and Analytics Success
• Leveraging AI and Emerging Technologies: How AI and other emerging technologies are reshaping the data landscape.’
• Insights into building a data-centric culture within organizations.

The increasing prevalence of artificial intelligence (AI) in our daily lives, from customer service chatbots to autonomous vehicles, has raised critical questions about its ethical implications. In response to these concerns, AI impact assessments have become a vital tool for organizations to evaluate the ethical maturity of their AI systems. This presentation explores the necessity of an "Ethics 1st AI Score," a novel approach to assessing data and AI ethics maturity from the perspectives of customers and employees. We will delve into existing AI maturity models for enterprises, highlighting their limitations and showcasing how our Ethics 1st AI Score stands out as a unique and much-needed solution. Join this Keynote address hosted by Shilpi Agarwal, CEO & Founder of DataEthics4All for an insightful exploration of Ethical Data Practise in the present day, and into the future.

Join us for this session as we explore the crucial role of data virtualization in driving digital transformation for organizations. CDOs must utilize the right tools to effortlessly connect diverse structured and unstructured data sources, creating adaptable data models that cater to consumer needs across multiple platforms. Discover how data virtualization can be a key enabler in supporting your organizational digital objectives.

Key Discussion Points:

- Insights into your entire data ecosystem by cataloguing and mapping various data sources and their interrelationships, fostering a comprehensive view.

- How to create a unified and coherent view of data by seamlessly connecting disparate data sources, enhancing data accessibility and usability.

- Best practice to enable real-time access to data, empowering agile decision-making and facilitating rapid response times.

Consistent data quality and availability are key challenges faced by CDOs and other Data Professionals. Access to accurate, complete, and readily available data is crucial for organizational agility and adaptability. In this session, we explore how CDOs can establish a robust data quality framework to unlock the full potential of analytical operations.

Key Discussion Points:

• Establishing data quality standards, defining data ownership, and assigning data stewardship responsibilities. Developing policies and procedures for data management, security, and compliance.
• Implementing data quality controls to monitor accuracy, completeness, and consistency, enabling regular data audits for reliable insights.
• Best practices for integrating data across the enterprise, enabling seamless access across departments and applications.
• Harnessing data analytics to uncover patterns, trends, and actionable insights that inform strategic business decisions.
• Exploring available data visualization tools to present information in a meaningful and intuitive manner.
• Strategies for comprehensive training on data management best practices to empower employees at all levels of the organization.

In today's rapidly evolving business landscape, enterprises across diverse industries are actively seeking opportunities to enhance operations, improve efficiency, and elevate customer experiences. Among the most promising technologies for achieving these goals is generative Artificial Intelligence, but what are the potential pitfalls of this new technology for a business and what can be done to avoid any issues with its implementation and utilization? Join us in this engaging keynote as we delve into the new era of digitalization and explore how Generative AI plays a pivotal role in driving innovation within enterprises.

Key Discussion Points:

- Unveiling the fundamentals of Generative AI and its transformative potential for enterprise advancement.

- Discover " leveraging Generative AI to foster innovation, fuel growth, and gain a competitive edge.

- Assessing your enterprise's preparedness for embracing Generative AI and determining the necessary steps for successful adoption.

- Key factors to consider when implementing Generative AI solutions within your enterprise, including data requirements, infrastructure, and scalability.

To accelerate the adoption of AI, CDOs must proficiently employ data management strategies and technologies that optimize efficiency, reduce expenses, and facilitate a seamless integration across multi-cloud and hybrid environments. What are some of the initial challenges that will be faced in the early stages of adoption and implementation? and how can they be easily overcome? Join us in this session as we explore the strategies and technologies that data leaders should embrace to achieve effective data management with the help of Artificial Intelligence.

Key Talking Points:

- How best to build a comprehensive data management strategy that includes data governance, metadata management, and data lineage?

- Leveraging AI and machine learning to automate and streamline data management processes.

- Creating a data platform that supports multi-cloud and hybrid environments.

- Implementing cost-effective storage solutions that balance performance and cost.

- How to masterfully manage this transition so as to keep your colleagues and employees minds at ease.