Rarely has a topic rocketed from obscurity to everyday discussion point as fast as generative AI has. Only going mainstream in late 2022, it has captured the attention of not just the data science and artificial intelligence communities, but the world at large. With that attention has come a lot of hysterical discussion about how it will ruin society, equally unrealistic discussions of how it will transform everything, and a mix of both facts and misinformation all around.

This talk will provide some sober and realistic discussions about what generative AI is, how it is being misunderstood, the strengths and pitfalls that it has, and how it might realistically change our world both in the near future and the long term. After the talk, attendees will walk away with a better feel for what is real and what’s hype, as well as tangible ideas for how generative AI can play a role in both their personal and professional lives.

According to KPMG Capital, 99% of businesses consider data and web analytics to be important to their organizations, yet 85% of executives struggle to analyse and interpret their existing data. Analytics are the foundation for a differentiated customer experience and more meaningful engagement. What begins with using data to understand the customer, then deriving actionable insight from that data to achieve top-line growth and provide a consistent brand experience across all customer touchpoints, is a top priority for many organizations.

Expanding the pool of people who can analyse and develop meaningful business action from data is therefore critical to gain a competitive edge. Data democratisation as a goal has been hampered by silo issues, fears around data quality and access to skills to analyse it properly. That said, if done properly it will enable different functions to make better decisions and collaborate more effectively.

Critical to success is creating a culture where people want to take control of their own data destinies and how can IT be an enabler given the critical questions of governance.

Data and analytics are part of every business decision around digital transformation and is now widely recognized as arguably the most important strategic asset of an organization. CDOs, CAOs and D&A leaders know that the key to success in this digital age is data. To capitalize on the true potential of data at our fingertips, organizations must fundamentally change how they view and use data. Transforming the view of D&A from what was typically considered a support function, to a strategic growth asset and core business competency requires data leaders to innovate to match the pace of digital transformation. How do D&A leaders quantify and prove the ROI of data initiatives in the context of business value? How can data leaders drive change while bridging the gap between business and technology?

Scaling and operationalizing AI, ML, and Data Science are critical to driving value and impacting how decisions within the business are made. It is vital for CDOs and D&A leaders to establish the technology trends, organizational requirements, skill development and talent required for successful deployment. How can we set ourselves up for success and develop a transformative vision for AI, enable enterprise-wide AI strategies, and use AI as a strategic differentiator? In enterprise AI, there is a gap between what is possible and what is expected a disconnect that is hurting implementation. While the ultimate goal for AI adoption is a more efficient organization, sometimes the gap between the possible and the achievable is too big. Sometimes, the technology is ready to deliver, but the infrastructure and quality of data are not there yet.

Data democratization will catapult companies to new heights of performance, if done right. The ultimate goal is to have anybody use data, at any time, to make decisions with no barriers to access or understanding (Bernard Marr). Businesses that wish to benefit from data democratization will have to create it intentionally. This means an organizational investment must be made in terms of budget, software & tools, and team training. So how do we get there? Expanding the pool of people who can analyse and develop meaningful business action from data is critical to gain a competitive edge for your business. Data democratization as a goal has been hampered by silo issues, fears around data quality, and access to skills to analyse it properly. That said, if done properly it will enable different functions to make better decisions and collaborate more effectively. Critical to success is creating a culture where people want to take control of their own data destinies and how can it be an enabler given the critical questions of governance. Businesses armed with the right tools and understanding are succeeding today because their employees are armed with the knowledge necessary to make smart decisions and provide better customer experiences. The transition to a more democratized view of data should not be a binary choice—fully centralized or decentralized. Data democratization must be viewed as a full continuum of options between those extremes. The ideal solution is found by monitoring for a ‘goldilocks’ state for data democratization (not too much and not too little) and engaging in the culture and process changes inside a company that makes it possible.

Digital transformation has become a popular term in recent years. Many industries and businesses are pursuing this transformation to address various disruptions or to strive for aggressive growth. Data analytics and digitization are often at the core of these transformations. While the goals and journeys may differ for each company, the common thread is the importance of analytics. The value of analytics has been proven in various areas, such as pricing, supply chain, marketing, and finance. However, only a few companies have fully embraced the concept of enterprise-level analytics to address their problem or opportunity statements. I believe that every company has the potential to establish enterprise analytics teams, which can create a consistent decision engine and foster innovation at a scale.

The strategic narrative of enterprise analytics is of scale, sustainability, speed, and innovation. In this discussion, you will hear a perspective for companies aspiring to adopt analytics-driven transformation.

Cloud platforms have revolutionized the world of analytics, but many companies still face challenges in transferring their most valuable and comprehensive data, that is stored in enterprise systems, to these cutting-edge cloud data environments. In this session, you will discover how to conquer typical obstacles to freeing up your enterprise data and learn how integrating this data can improve analytics, refine financial and regulatory reporting, streamline operations, and enhance the customer experience.

With the growing demand for data and analytics, companies are responding with increased investment and elevation of the data and analytics function within their organization. While many companies are enjoying success, others struggle to find traction on their data-driven journey. In this session, we'll discuss the common success factors of data-driven organizations.

With the rapid advancement of technology, the amount of data available to organizations has increased dramatically, making it more important than ever to understand how to effectively use data to improve customer engagement and experience. According to recent studies, using data analytics to drive customer engagement can result in significant benefits for businesses. For example:

•Companies that prioritize customer experience have seen a 15% increase in revenue compared to those that do not (Forrester)
•75% of consumers are more likely to purchase from a company that provides personalized experiences (Epsilon)
•Companies that use data to drive decision-making are 6 times more likely to retain customers (Forbes)

Our panellists will share their insights on how to turn data into actionable insights, and how to use those insights to personalize customer experiences and drive engagement. We will also discuss the latest trends, tools, and techniques for using data to drive customer engagement.