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With a power-packed line-up across 2 theatres focusing on data management strategies, data quality & global compliance, hyperautomation, Adaptive ML, Generative AI and Alaas, the Summit will address emerging data & AI challenges and how businesses can create results. 

Topics that will be covered include:

Generative and Conversational AI: A vast array of innovative uses and applications

Harnessing new technologies to innovate businesses efficiencies is the top priority amongst enterprise leaders. This track will explore the applications of generative and conversational Ai - the processing and understanding of large amounts of text, generation of text based on input, and the abilities to provide accurate and informative responses to a wide range of topics. 

AIaaS: Implement & Scale at a fraction of the cost.

Artificial Intelligence as a Service will play a growing role in society's technical infrastructure, enabling, facilitating, and underpinning functionality in many applications. AIaaS providers therefore hold significant power at this infrastructural level. This track analyses the challenges & responsibilities for customers & providers in these complex, networked, dynamic processing environments. 

Training Data Complexities: understanding and producing insights from increasingly complex datasets.

Analyzing large data sets can be challenging due to the complexity of the data and the need to use multiple technologies to process it. Additionally, data projects often require advanced analytics techniques to uncover insights from the data, which can further add to the complexity. This track is dedicated to exploring the strategies, tools, skills and roles needed for creating successful teams. 

Adaptive AI: Enabling new ways of doing business

Unlike traditional AI systems, Adaptive AI can revise its own code to adjust for real-world changes that weren't known or foreseen when the code was first written. Organizations that build adaptability and resilience into design in this way can react more quickly and effectively to disruptions. This track provides guidance on how adaptive systems will enable new ways of doing business.   

AI Governance: Facilitate innovation whilst safeguarding trust

As organizations scale their use of AI, they increasingly need to do so in a responsible and governed manner. This is driven by many complementary forces: brand reputation, anticipated regulations, social justice etc. This track addresses how to implement AI governance to all parts of businesses in a trusted way. 

Hyperautomation: Operating with increased efficiency to succeed in today’s economy.

Hyperautomation builds a connection between systems and operations with structured and unstructured data, simplifying data analysis and enabling faster decision making. From Data sharing to real-time information access & productivity - we will analyse how hyperautomation ensures that every intelligent

Data Management: Unlocking the potential of data as a driver for organizational success.

In today’s digital economy, companies have access to more data than ever before. This data creates a foundation of intelligence for important business decisions. This track provides guidance for businesses on how to ensure employees have the right data for decision-making, improve visibility, reliability, security, and scalability.    

Data Mesh: Decentralised architecture for the win

Data Mesh is a ‘socio-technical’ approach that requires changes to the organization across all three dimensions of people, process and technology. This track explores how it can help organizations to better manage and access their data and provide flexibility and autonomy for data owners. 

 Data Sharing: Gain perspective across new insights 

Many organizations inhibit access to data, preserve data silos and discourage data sharing. This undermines the efforts to maximize business and social value from one of an organisations key assets, it’s data. This track analyzes why data sharing is a business necessity for organizations to accelerate their digital business model. 

Data Strategy: Manage & deploy data as a business asset.

Aligning data strategy with business strategy is essential for organizations to stay relevant, competitive, and innovative amidst constant change. This track explores how an organization can acquire, manage, store, share, and use its data in order to achieve its business objectives.   

Data Quality: The better the data, the better the outcomes

Bad data can have significant business consequences for companies. Poor-quality data is often pegged as the source of operational snafus, inaccurate analytics and ill-conceived business strategies. This track analyzes how measuring data quality levels can help organizations identify data errors that need to be resolved and assess whether the data in their IT systems is fit to serve its intended purpose. 

Data Sovereignty: Defining how data can be compliantly & securely collected, stored, and used.

The effort to protect data as a new strategic asset is creating a clear need for sovereign clouds to secure and use data sensibly - organisations want all the benefits of cloud but also need to meet the rapidly growing and changing data privacy laws. As these laws impact business operations, organizations are seeking better ways to comply with data sovereignty laws and mitigate compliance risks. This track addresses why data privacy protection is more important than ever, and companies must ensure their customers and employees’ sensitive data is safe wherever that data is stored, shared and used.