AI/ML Use Case Library for Sports & Entertainment
Leverage AI/ML to address operational challenges and improve experiences.
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×- Sports & Entertainment organizations are challenged with inefficient business operations and are uncertain how to effectively address them.
- Determining relevant use cases for the Sports & Entertainment industry can be difficult and time-consuming.
- There is a limited understanding of how AI and ML can impact the business and how they can provide significant value.
Our Advice
Critical Insight
Leverage best-in-class AI/ML use cases to accelerate innovation and improve operational efficiency, fan experiences, and data-driven decision making.
Impact and Result
Pull inspiration from a curated collection of best-in-class AI/ML use cases to accelerate the initiative ideation process.
- Concepts can often be helpful in designing transformation roadmaps, despite different implementation methods.
- Our analysis offers additional guidance on ROI guidelines, primary sources of value, and more.
- Pulling best practices from anonymized use cases increases the odds of successful value capture.
AI/ML Use Case Library for Sports & Entertainment Research & Tools
1. AI/ML Use Case Library for Sports & Entertainment Deck – A guide to leveraging AI/ML to address operational challenges and improve experiences.
Leverage a robust set of AI/ML use cases to identify potential initiatives that can accelerate value creation. Use cases cover a range of technologies and capabilities and include insight into sources of value and implementation feasibility.
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AI/ML Use Case Library for Sports & Entertainment
Leverage AI and ML to address operational challenges and improve experiences.
Analyst Perspective
Define the organization's AI/ML transformation
The Sports & Entertainment industry is experiencing unprecedented change and disruption due to rapid development of artificial intelligence (AI) and machine learning (ML). In this new era, Sports & Entertainment organizations require a digital strategy to guide their AI and ML transformation journey.
With that aspiration in place, Sports & Entertainment business and technology leaders must work together to map out tactical and actionable plans to support an organization's strategic goals. An effective AI and ML transformation plan executed within the next one to two years can define the next one to two decades.
Sports & Entertainment must balance the need for digital technology investment with affordable service. At Info-Tech, our goal is to help leaders accelerate the identification and development of tactical AI and ML transformation initiatives to enable your digital transformation.
Elizabeth Silva
Research Analyst, Gaming, Hospitality, Sports & Entertainment Industry
Info-Tech Research Group
Executive Summary
Your Challenge | Common Obstacles | Info-Tech's Approach |
Sports & Entertainment organizations are challenged with inefficient business operations and are uncertain how to effectively address them. Determining relevant use cases for the Sports & Entertainment industry can be difficult and time-consuming. There is little understanding of how AI and ML can impact the business or how they can provide significant value. |
Adopting new technology requires a strategic approach and alignment between IT and the business to develop value. AI and ML are significant investments for smaller organizations with limited resources which will require a comprehensive business case. Many AI and ML initiatives are often delayed and over budget, leading to unsuccessful projects. Identifying industry-leading best practices can be helpful in driving early ideation sessions if the business is available for it. |
Pull inspiration from a curated collection of best-in-class AI and ML use cases to drive the initiative ideation process.
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Info-Tech Insight
Leverage best-in-class AI and ML use cases to foster innovation and improve operational efficiency, fan experiences, and data-driven decision making.
Gen AI is an innovation in machine learning
Generative AI (Gen AI)
A form of ML where a Gen AI platform can respond to prompts by generating new outputs based on training data. Depending on its foundational model, a Gen AI platform will provide different modalities and resulting use case applications.
Machine Learning (ML)
An approach to implementing AI where the system is instructed to search for patterns in a dataset and then make predictions based on that set. This way, the system iteratively “learns” to provide more accurate content over time (think of Google's search recommendations).
Artificial Intelligence (AI)
A field of computer science that focuses on building systems to imitate human behavior. Not all AI systems have learning behavior, as many operate on preset rules (e.g. customer service chatbots).
Info-Tech Insight
Many vendors have jumped on Gen AI as the latest marketing buzzword. When vendors claim to offer Gen AI functionality, pin down what exactly is generative about it. The solution must be able to generate new outputs – not just predictive ones.
Diverse AI capabilities can drive value
Sports & Entertainment should consider a wide range of AI capabilities as Gen AI continues to evolve.
Primary AI capabilities being adopted in global business
Source: McKinsey & Company, 2022
Sports & Entertainment organizations can differentiate themselves using their vast and diverse data to unlock the value of AI.
Main objectives of AI adoption within organizations
Source: Scale, 2023
North America is estimated to have the largest market share in global generative AI for sports at 48.2%
Source: Market Research, 2023
AI and ML have significant fan experience benefits
1. Intuitive and simplified fan engagement for more immersive fan experiences. Streamline fan interactions using AI to analyze large amounts of fan data to generate insights and personalized content, improving service quality and anticipating fan needs.
2. Implementation can be delivered through multiple channels to enable seamless experiences. AI tools can enhance the omnichannel experience, delivering consistency across every touchpoint by considering the digital data footprint each fan leaves behind in every engagement.
3. Enhanced convenience and accessibility for all fans reducing friction points. As consumer demand for quick service intensifies, AI offers a valuable solution, producing relevant information with better accuracy and minimized response times.
4. Cater to digital natives' needs and wants in a digital-first world. Digital natives, born between 1997 and 2012, fully embrace technology and are eager to incorporate AI and ML into their daily lives. Organizations can benefit by plugging AI into fan interactions.
48% of technology leaders plan to use AI to create highly personalized experiences.
Source: Oracle, n.d.
45% Increased spend-per-customer with AI.
Source: Oracle, n.d.
There is broad AI applicability for employees & players
1. Productivity enhancement. Reduce manual effort and repetitive tasks to save time and costs that could be spent on other important processes including fan interactions.
2. Democratized data analytics. Employees and coaches can improve self-reliance by incorporating these into daily workflows, creating tangible value within their applications and improving practicability.
3. Employee empowerment. AI enhances training for employees and players which decreases performance gaps. This will also yield more relevant results, allowing them to make better decisions in a fraction of the time.
4. Embrace digital transformation. Drive new low-cost, high-volume, data-driven business models. There is clear evidence of applicable use cases that can support interactions between fans, players, and employees.
Info-Tech's approach and team can help irrespective of where you are in your digital journey
Measure the value of this document
Document objective
Highlight best-in-class use cases to spur the initiative planning and ideation process.
Measuring your success against that objective
There are multiple qualitative and quantitative, direct and indirect metrics with which you can measure the progress of your initiative pipeline's development. Some examples of this are:
- Increased initiative pipeline value
- Number of capabilities impacted by initiative pipeline
- Enhanced understanding of initiatives' impact aligned to organizational capability map
- Better understanding of which sources of value are being addressed or under-addressed in the organization's initiative pipeline
See How to Establish Your Transformation Infrastructure from the Digital Transformation Center for more details
SECTION 1
AI/ML Use Case Library Methodology
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×About Info-Tech
Info-Tech Research Group is the world’s fastest-growing information technology research and advisory company, proudly serving over 30,000 IT professionals.
We produce unbiased and highly relevant research to help CIOs and IT leaders make strategic, timely, and well-informed decisions. We partner closely with IT teams to provide everything they need, from actionable tools to analyst guidance, ensuring they deliver measurable results for their organizations.
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A blueprint is designed to be a roadmap, containing a methodology and the tools and templates you need to solve your IT problems.
Each blueprint can be accompanied by a Guided Implementation that provides you access to our world-class analysts to help you get through the project.
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Unlock Sample ResearchAuthor
Elizabeth Silva
Contributors
- Asheesh Kinra, CIO, Baltimore Ravens
- Okpara Young, Director of IT, Houston Rockets
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Search Code: 102610
Last Revised: August 22, 2023
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