Executive Summit

ChatGPT has grabbed headlines, caused competitors to scramble, been embraced by innovators and banned by some organisations and countries. It is just the latest example of a near decade-long technology trend called Generative AI which can augment human capabilities by creating realistic content, such as text, images, audio and much more. It can also be used to generate synthetic data that represents the original data and can eliminate privacy concerns, augment AI training data and mitigate bias. This session will explore the practical applications of generative AI to enable your organisation to stay ahead of the competition and drive innovation.

Join Brian Burke (Research Vice President, Gartner) to discuss:

• Explore how generative AI is a fundamentally different approach to AI, extending AI models from classification to generation and enabling machine creativity
• Expose the practical applications of generative AI which are making breakthroughs in product design, operational processes, and business models
• Envision how your organisation can be an early adopter of generative AI to drive innovation in your industry

Gaps in the use of data and analytics grow wider as organisations continue to struggle with how to translate data insights into impact. Organisational culture, data literacy, and effective data and analytics communication are essential for CDAOs to support business leaders and their organisations to leverage the true value of information assets.

In this session, We’ll discuss:

• Creating impactful data literacy training for the enterprise
• Developing a strong data and analytics communications strategy
• Utilising frameworks and common language around what it means to be data-informed

Causal decision-making is the process of identifying the causal relationships between variables and using that information to make more informed decisions. By leveraging Causal AI, businesses can analyse complex data sets and uncover the underlying causal relationships that drive their business outcomes. This talk will explore the importance of causal decision-making for enterprises and how it can enable domain experts to make the best decisions for their businesses.

In this session, Darko Matovski (PhD & CEO, causaLens) and Jonathan Saunders (Chief Data Officer, Direct Line Group) will share:

• Real-world examples of businesses that have successfully implemented Causal AI, enhancing their decision-making processes
• Gain a greater understanding of how advanced AI technologies can be used to enhance decision-making processes & drive better business outcomes
• How AI can be leveraged to create opportunities for business growth

With data regulations and governance evolving both within region and cross-country , how can you best restore a free flow of data across borders quickly and efficiently while complying with a complex matrix of requirements? Juggling regulations for multiple regions can be challenging for large multinational organisations.

Join this boardroom to discuss:

• The challenges and risks to data centralisation due to increasing complexity in localisation, and privacy requirements
• The limitations of existing data tools that are not built to overcome these issues
• Approaches to solving expanding data localisation problems and the impacts on data governance

If Artificial Intelligence is mainstream and the cornerstone of digital transformation, why do so many projects fail? Proper foundations help avoid common pitfalls and get AI into production in a way that creates market differentiation and business value. Join us to fast-forward your transformation journey and learn how to avoid common challenges that prevent AI initiatives from moving out of the lab to going live at scale.

In this Executive Boardrooms Matt Armstrong-Barnes, Chief Technology Officer for Artificial Intelligence at Hewlett Packard Enterprise will discuss:

• The common challenges organisations face on the AI journey
• How to avoid them, make more progress and accelerate the benefits AI can bring
• How to put the foundations in place for the next phase, AI at scale

The role of the CDAO is still relatively new and what an executive can do beyond this is even newer. How this role is evolving, the fight to remain relevant and grow in prestige and what the future holds beyond being a CDAO is uncertain. There is no set path for a CDAO to walk, but rather a plethora of opportunities. This session will ask key questions, like what is the CXO step beyond CDAO? Should they aim to be a COO or how many of you have non-executive director positions?

Join this panel to explore:

• Discussing key factors that can enhance the prestige and value of the CDAO
• The importance (or lack thereof) of having a clear roadmap for the CDAO
• The shifting responsibilities of the CDAO over the next five to ten years

Concerns around AI ethics are increasing as AI comes into the mainstream. There is a greater need for transparency, accountability, and auditability in AI models. Organisations need to work towards responsible AI adoption to build customer and stakeholder trust.

New regulations will hit the UK and EU as early as 2024. There are likely to be differences in how these rules will be governed and enforced across the EU member states, and with many other countries developing their own frameworks, what will this mean for the organisations’ operations and performance? Yet, self-policing ahead of regulation is necessary as organisations’ success and reputation depend on doing the right thing.

Join SAS to learn more about:

• Building fairness and equity into every AI model from the start
• Ethical frameworks in place incorporating privacy, respect, transparency and consent to allow enterprises to innovate quickly and responsibly whilst preparing for upcoming regulations
• The importance of data science practices to identify potential bias at a much earlier stage and therefore reduce operational, financial and emotional risk
• Best practices for leveraging AI technologies with a human-centric and ethics-lead approach

Data is the primary asset for organisations driving innovation. Converting data into actionable insights is a team effort and all employees must play a role to advance organisational objectives. Data and analytics leaders are tasked with creating a data literacy programme that streamlines and propels enterprise agility.

Join this roundtable discussion to discover how to:

• Identify skill gaps that prevent organisations from achieving critical business objectives and maximising technology investments
• Design scalable training programs that build organisation-wide data literacy and a data-driven culture through applied learning, without impacting your cost centre
• Increase team engagement and retention, alongside attracting a diverse talent pool that allows organisations to better represent and serve their customers

Multiple attempts to create value from data have been labelled “democratisation”: business intelligence in the 1990s, self-service analytics in the 2000s, and (citizen) data science in the 2010s. Yet progress on their common goal, putting more hands-on data outside central teams, has been wildly uneven. Cynical observers even note the same problem being “solved” over and over without understanding why earlier attempts failed. The current generative AI revolution has led, once again, to the same pronouncements, so what would make things different this time? Can AI help us escape the paradox of so-called structured data remaining impenetrable to domain experts? And how can data leaders avoid being left behind as business teams embrace AI faster than central teams can govern it?

You will leave this session, having discussed:

• What is different (if anything) about this moment vs prior waves of hype/progress
• Where your peers are realising value today from AI
• How to use current hype to accelerate value-driven adoption of AI