The firm’s latest research explains the transformative impact of artificial intelligence (AI) and machine learning (ML) integration in integrated casino resorts. The blueprint delves into the strategies for reshaping guest experiences and operational efficiency, navigating the dynamic landscape of the gaming industry with precision and innovation.
TORONTO, Feb. 22, 2024/PRNewswire/ – The integrated casino industry is on the brink of a transformative era, driven by the exponential evolution of artificial intelligence (AI) and machine learning (ML). These technologies promise to address various industry-wide challenges, from streamlining business operations to delivering unparalleled guest experiences. However, embracing these technologies requires a strategic approach and alignment between IT and business objectives. To assist technology leaders in building a roadmap to navigate these complexities, Info-Tech Research Group has published its latest research, AI/ML Use Case Library for Integrated Casino Resorts. This comprehensive research provides industry leaders with insights and strategies needed to harness AI and ML effectively, transforming both the gaming and hospitality sectors.
“Integrated casinos are experiencing unprecedented change and disruption in this new era. The industry requires a digital strategy to guide AI and ML transformation,” says Elizabeth Silva, senior research analyst at Info-Tech Research Group. “Gaming and integrated resorts business and technology leaders must work together to map out tactical and actionable plans to support an organization’s strategic goals and reach exponential IT status. An effective AI and ML transformation plan executed within the next one to two years can define the next one to two decades.”
Info-Tech’s research highlights the critical challenges of modernization within the gaming and hospitality industry, particularly emphasizing the need for compelling business cases to justify the significant investments AI and ML entail. The frequent delays and budget overruns of AI and ML initiatives can often result in project failures. This underscores the critical importance of strategic planning and resource allocation in navigating the complexities of modernization within the industry.
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