In today's rapidly evolving business landscape, AI strategies are quickly becoming the cornerstone of digital transformation. However, in the current rush to keep up with competitors, hypes and buzzwords, how many of these strategies will really succeed? How many will be written off as a huge waste of resource and money? Before you go any further, maybe it is time to think again.
In today's environment it is not enough to collect data and generate analytics - the most ambitious enterprises are assembling a "data flywheel", where data is turned into operational decisions, followed by action which in turn generates more data, feeding and accelerating the flywheel.
With the proliferation of data touchpoints and advanced analytics capabilities through the help of Gen AI, businesses now have unprecedented opportunities to establish holistic personalised loyalty experiences for their customers. Leveraging customer data, like such, can drive long-term returns however can soon lead to precarious compliance territory.
Meet in an informal roundtable with peers from your industry to discuss some of the hottest trends and industry-specific challenges.
In the age of AI and ML, data quality has become more critical than ever. As AI models consume vast amounts of data, it is imperative that your data inputs are of the highest quality to make the most of new AI tools. AI-powered observability tools are revolutionising the ability to monitor and maintain the health of your data from the moment it’s gathered to the point of analysis.
Speed “Data-ing” - Meet new delegates and learn about their current data challenges and successes.
Moving the company along the data maturity curve, fast and cost effectively, is a goal that unites CDOs across all industries. While every venture will be faced with its own set of legacy challenges, budget restraints, structural and cultural hurdles, hear the reasons for the successes and failures of others, can help fast track your journey.
Eat lunch and discuss some of the most exciting and controversial data trends you’ve heard about recently by joining the dedicated data gossip corner.
As the UK Government maintains its ‘wait and see’ approach to AI regulation, forward thinking organisations are seizing the opportunity to jump the gun and shape their own AI governance frameworks. In 2025, taking a proactive stance is more crucial than ever, with AI technologies rapidly evolving and becoming increasingly embedded in business operations. While the UK’s regulatory landscape remains fluid, global standards are emerging, led by the EU’s AI Act. Organisations that wait for UK-specific regulations risk falling behind international competitors and may face challenges when UK regulation catches up.
Data silos are the likely result, following a merger or acquisition. The constant evolution of your organisational structure can leave your data team grappling with ever-increasing data volumes and complexity, requiring an updated data management strategy, one which fosters collaboration and efficiency. For many, tailored Data Mesh architecture addresses this challenge. Discover how a Data Mesh Architecture is revolutionising data management, breaking down traditional silos that can result from organisational restructuring.
In 2025, the data modern data stack, once categorised by a collection of specialised, best-of-breed tools, is facing new challenges and opportunities. On one side, we see the rise of all-in-one platforms promising seamless integration and simplified management. On the other, specialised vendors continue to innovate, offering cutting-edge solutions for specific data needs. This evolution raises the question for data leaders: Should you opt for integrated platforms that offer end-to-end solutions, or continue building your stack with specialised tools?
Given the disputed and variable responsibilities of a CDO and the growing pressure for ‘Data’ to merge into other business functions, proving your value and effectiveness is imperative to strategic success and gaining favour in the boardroom. Discuss best practices for establishing KPIs that are suitable to both your business objectives and data strategy, as well as how to set motivating and measurable KPIs to quantify your impact on the bottom line.
Meet in an informal roundtable with peers from your industry to discuss some of the hottest trends and industry-specific challenges.
As data volumes continue to grow exponentially, so does energy consumption associated with the storing, processing and transmitting of data. CDOs are uniquely positioned to drive sustainable data practices within their organisation’s data management and report on their green impact. Should CDOs lead the charge for environmental responsibility within their organisations? What measures can be taken by Senior Data Leaders to reduce the carbon footprint of data management?