From transforming marketing strategies to delivering thrilling and engaging digital fan experiences, find out how sports organisations can adjust to a digital-first future. Explore what’s possible now and how the AI ladder can help you develop the enterprise capabilities required to bring technology-driven initiatives to life. The world is undergoing tremendous change that impacts all industries, and the sports ecosystem is no different. The current health crisis caused training sessions, matches and sports competitions to be postponed or even cancelled entirely, disrupting all the stakeholders in the industry and leaving fans everywhere disconnected from the teams and the sportspeople they love. Now, organisations are left to navigate the implications of these extreme measures, while planning for a future that may look very different from the past. When technology meets sport Sport, in all its forms, is driven by – and produces, in turn – copious amounts of data. Purposefully exploiting that abundance of data can enable sports…

This session will demystify AI by translating abstract concepts into specific technology capabilities and using real world examples to illustrate the power of AI.

Artificial Intelligence (AI) is top of mind for leading corporations these days – 96.4% of top executives reported earlier this year that AI was the number one disruptive technology that they were investing in, up from 68.9% just two years ago. In addition, 80% of these executives identified AI as the most impactful disruptive technology, up from 46.6% two years earlier. Yet, for many organizations, Artificial Intelligence remains a mystery. For specialists, AI implies a very specific connotation in terms of intelligence demonstrated by machines, in contrast to the more common usage of AI which encompasses all varieties of machine assisted learning, most notably machine learning, deep learning, and natural language. For the sake of this discussion, we will assume the broadest definition of AI.

If you read the tech press, you'll hear that artificial intelligence (AI) is all the rage these days. And whether or not they are doing it well, everyone is saying that they're engaging in AI. One thing is certain: organizations across industries are running fast to be a part of the AI revolution. In this two-part series, I'll examine what's driving this rapid pace of adoption, and why some companies are seeing far more success than others. In part one, I'll discuss some of the needs inherent in creating an AI solution.

The first automobile was driven down the streets of Detroit in 1890. It would take another 30 years before Henry Ford streamlined production and made cars available to the mass market. The obvious lesson: sometimes technology has a long gestation period, before we can scale it for everyday use. But, digging a bit deeper, there is a more profound lesson. Over the first hundred years of the self-propelled vehicle, essential building blocks were established – standard components like the combustion engine, steering wheel, and axel.