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TCS Sports Sponsorships: Blending Sports Technology and Sustainability
Highlights
- Sustainability and performance don’t have to be a trade-off in elite sports or business.
- Generative AI (GenAI) can help bring both together in a balanced way by enabling better data mining and decision-making.
- Collaboration will be vital to helping AI flourish as an enabler of greater sustainability across industries.
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AI unlocks sustainability
Sports and businesses alike have a great opportunity to become more sustainable or to reach extremely high levels of performance. Doing both together, however, is challenging.
This is how the scene was set at our roundtable event titled ‘On track to sustainability: Harnessing AI in sports and business’, held at the 2024 London E-Prix in July. It brought together leaders from across industries to focus on the role of AI in reducing environmental footprints.
Rather than viewing sustainability and performance as a trade-off, participants were encouraged to consider how GenAI can help bring both together in a balanced way
Enabling better decision-making
AI is changing and improving how we make decisions.
GenAI has many implications in terms of the use cases currently being developed, the impact it will have on business and jobs, and the challenges it can pose to governance. However, one of the greatest advantages is its impact on decision-making.
When it comes to the E-Prix, the difference between the top performers isn’t necessarily about skill levels—it is often decision-making that determines the winners and losers.
AI is a fundamental differentiator that can help you make the right choices at every level of the organisation. If you harness the technology to make better decisions, they become exponential rather than just incremental.
While there are countless opportunities for businesses to harness the power of AI, its greatest value may be in helping organisations make sense of all the data they already hold but cannot exploit.
For example, a lot of sustainability reporting models focus on the past. AI can turn this perspective around and help companies plan and optimise their pathway to the future. With the right inputs, it could help them create roadmaps that account for their medium- to long-term carbon emission reduction goals.
Improving reporting and forecasting with AI
The industries represented by the roundtable participants are replete with examples of how AI tools can improve reporting and forecasting.
In the energy sector, AI is seen as an essential tool to predict shifts in demand patterns, as electricity grids become more diversified and distributed thanks to the transition to renewables. Not only will this help make the best possible use of low-carbon sources, but it can also help with energy trading, ensuring that consumers get the right amount of electricity at the right time and the best price.
Similarly, in the insurance sector, AI could help combine a multitude of datasets from diverse sources to monitor the carbon footprint not only within the organisation but also among those it insures.
AI-enabled models are also set to affect healthcare and sports medicine, one participant highlighted, with the technology being used to create digital twins of human organs such as the heart. These models could be used to fine-tune the training regimens for athletes and enable surgeons to practise on an actual model of a person’s heart ahead of performing an operation.
Avoiding data swamps
With all the potential that AI brings toward striking the balance between enhancing performance and becoming more sustainable, industry leaders also pointed out that it must not be viewed as a panacea—AI and data alone will not be able to fix things.
Participants from the automotive industry cautioned that simply storing all possible data and running AI on it would not yield meaningful results—it would amount to creating a ‘data swamp’. Before unleashing AI tools on data, the first step should be to fix issues and establish what data should actually be stored.
This is crucial toward limiting the organisation’s carbon footprint, as more data storage means more carbon getting expended. This is one reason why the IT sector itself has an exponentially rising energy use and carbon footprint.
Harnessing AI across industries and stakeholders
Like many other questions surrounding AI, the sustainability challenge calls for a joint approach, not only across industries but also with regulators and policy-makers. Only a collaborative effort will enable the creation of harmonised standards and solutions to help AI flourish in its support of the green transition.
In closing the roundtable, participants considered AI in the context of balancing performance and sustainability.
They concluded that getting both right is an ongoing battle that requires continued financial, political, and practical investment. They agreed that only through collective responsibility will we set the right path and exceed expectations.
Harnessing AI across industries and stakeholders
Like many other questions surrounding AI, the sustainability challenge calls for a joint approach, not only across industries but also with regulators and policy-makers. Only a collaborative effort will enable the creation of harmonised standards and solutions to help AI flourish in its support of the green transition.
In closing the roundtable, participants considered AI in the context of balancing performance and sustainability.
They concluded that getting both right is an ongoing battle that requires continued financial, political, and practical investment. They agreed that only through collective responsibility will we set the right path and exceed expectations.
AI is a fundamental differentiator that can help you make the right choices at every level of the organisation. If you harness the technology to make better decisions, they become exponential rather than just incremental.