Purpose: The purpose of this study is to map the body of scholarly literature at the intersection of artificial intelligence (AI), analytics and sports and thereafter, leverage the insights generated to chart guideposts for future research. Design/methodology/approach: The study carries out systematic literature review (SLR). Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) protocol is leveraged to identify 204 journal articles pertaining to utilization of AI and analytics in sports published during 2002 to 2024. We follow it up with extraction of the latent topics from sampled articles by leveraging the topic modelling technique of BERTopic. Findings: The study identifies the following as predominant areas of extant research on usage of AI and analytics in sports: performance modelling, physical and mental health, social media sentiment analysis, and tactical tracking. Each extracted topic is further examined in terms of its relative prominence, representative studies, and key term associations. Drawing on these insights, the study delineates promising avenues for future inquiry. Research limitations/implications: The study offers insights to academicians and sports administrators on transformational impact of AI and analytics in sports. Originality/value: The study introduces BERTopic as a novel approach for extracting latent structures in sports research, thereby advancing both scholarly understanding and the methodological toolkit of the field.

I recently visited with the CIO of a Fortune 500 company. He was touting the advances they had made in IT and corporate culture regarding the use of artificial intelligence and analytics, but he had one major concern: How do you fuse AI and analytics into the rest of your transactional line of business IT infrastructure? It hasn't been that way in his enterprise. His IT organization had started its analytics initiative with an internal Hadoop group that was responsible for processing big data internally. Meanwhile other departments in IT supported transactional data processing on an assortment of mainframes and servers in the data center. Regular IT and the Hadoop groups were somewhat siloed from each other because the parallel processing and storage management needs for big data and AI were notably different than what they were for transactional data and processing management.

Dr Anastasia Griva is exploring real-world phenomena in the AI and business analytics space, looking to answer questions that are important to society. Dr Anastasia Griva received her PhD in business analytics from the Athens University of Economics and Business three years ago. This was an industry-funded PhD and she worked closely with the retail sector, while establishing two AI and analytics start-ups. But academia was her dream and so she joined the University of Galway as a post-doc researcher. She applied successfully for a Marie Skłodowska-Curie fellowship through Lero, the Science Foundation Ireland research centre for software. After this, she obtained her first academic position as a lecturer, and she is now the programme director for the MSc in business analytics at the University of Galway.

WNS, a leading provider of global Business Process Management (BPM) solutions, announced that it has been recognized as a'Leader' in AI and Analytics, and Social Media for CX Services in the ISG Provider Lens 2022 Global Contact Center Customer Experience Services report. WNS' leadership position in AI and Analytics has been attributed to WNS Triange (the company's Data, analytics and AI practice); proprietary technology ecosystem and strategic partnerships; and WNS EXPIRIUS, a proprietary framework that enables clients to optimize analytics-driven, intelligent omni-channel conversations with customers. WNS' 'Leader' position in Social Media CX Services is driven by its robust social media practice capable of handling up to 85 million online conversations at 85 percent accuracy; a comprehensive social media product suite for everything from social listening to advanced analytics; and WNS EXPIRIUS Social, which leverages intelligent automation to deliver heightened customer experience. "We are delighted to be chosen as'Leader' across Social Media, AI and Analytics for Customer Experience – two areas where WNS has made considerable strategic investments over the past several years. Our robust CX practice is built on a foundation of intelligent analytics, Artificial Intelligence and automation to address the entire customer engagement journey. Our clients leverage WNS' advanced digital solutions to create unique experiences that drive new revenue streams and deep customer loyalty," said Keshav R. Murugesh, Group CEO, WNS.

I often get asked to define the differences between BI (business intelligence), AI (artificial intelligence) and analytics. For many organizations, there seems to be so much overlap that it's difficult to know where one technology ends and the other begins -- or even whether these technologies can be used concurrently. Business intelligence is a broad category of information management, analysis and reporting that operates on both structured and unstructured data. BI can yield insights for organizations about their markets, the "fit" of their products and services in these markets, and the effectiveness of their internal operations, too. The business intelligence toolkit is far-reaching.

The events and strain of the past two years have seen many socioeconomic challenges exacerbated. While the solutions are complex and daunting, AI and analytics can play a critical role in accelerating and delivering success. Leaders across government and industry have been empowered by trusted data to make rapid, cost-effective, and accurate decisions. For the year ahead, we've identified five social, economic, and political challenges that AI and analytics are poised to improve. The bipartisan Infrastructure Bill provides $550 billion to improve America's infrastructure over five years, impacting everything from bridges and roads to the nation's broadband, water, and energy systems.

Dista Sales, our sales productivity platform, helps improve sales productivity and enhances lead conversion rate. Our system offers area definition and analysis of potential leads in a specific area. It provides analytics and insights on your customers, conversion metrics, agent performance, etc. Dista's AI-based recommendation helps business leaders make strategic decisions related to expansion. Dista Sales offers resource planning forecasts based on past data and ML-based engines. Custom reporting and dashboarding help them get instant reports for better decision-making.

A newly released whitepaper on the future of banking has found that AI and analytics will play a "central role" in the future of worldwide banking. The'Bank of the Future' paper- released by Mambu and Google Cloud – said that'ubiquitous banking' will likely be the next stage of digital finance as consumers continue to demand constant, personalised digital financial services after the pandemic. AI and analytics will form a major part of this next stage the data suggested, helping to drive significant growth opportunities as customers further desire speed, convenience and instant access to information, goods and services. Strong focus must be placed on'customer-centric strategy' the paper suggests, creating products and services built around and for customers. This strategy should be to embed AI tech to "hyper-personalise the user experience".

When it comes to digital transformation, the Covid crisis has provided important lessons for business leaders. Among the most compelling lessons is the potential data analytics and artificial intelligence brings to the table. "Launching a direct-to-consumer business was always on our roadmap, but we certainly hadn't planned on launching it in 30 days in the middle of a pandemic," says Michael Lindsey, chief growth officer at Frito-Lay. "The pandemic inspired our teams to move faster that we would have dreamed possible." The crisis accelerated the adoption of analytics and AI, and this momentum will continue into the 2020s, surveys show. Fifty-two percent of companies accelerated their AI adoption plans because of the Covid crisis, a study by PwC finds.

Artificial Intelligence (AI) has moved from "when will we do it?" AI passed some important tests during the pandemic, says David Tareen, director of AI and analytics at SAS. "The pandemic put AI and chatbots in place to answer a flood of pandemic-related questions. Computer vision supported social distancing efforts. Machine learning models have become indispensable for modeling the effects of the reopening process." But the future upside of AI is still considerable.