By Divyajot Ahluwalia, founder and director, wTVision Solutions.

Cricket is a sport built on technique, patience and the interpretation of raw data to shape tactics and long-term strategy. This layered complexity is what appeals most to the players and seasoned followers of the game. However, this calibre of patience and depth cannot be expected from a generation that co-exists with a digital world that is faster, more agile and quicker with information. Growing up in a media environment transformed by visual clarity and instant context, Gen Z is often less willing to invest time in understanding the nuances of a sport like cricket unless it is presented clearly and intuitively. 

This is a challenging task for broadcasters who do not just cover the game, but also educate Gen Z by simplifying play sequences and the consequences of the overflow of the game. The wide array of formats present in cricket have intricate distinctions where the same statistics carry very different meanings making it a multifaceted challenge. A strike rate of 100 in Test cricket communicates restraint and control, whereas the same number in T20 may signal inefficiency. This context needs to be clearly displayed so it doesn’t confuse viewers, rather it informs them. 

The advent of artificial intelligence has altered the visual idiom through which cricket is read. There are primarily five roles in bridging the gap between the sport’s complexity and Gen Z’s viewing expectations. 

1. Going deeper into the game

AI provides broadcasters with the freedom to delve deeper into the game and find meanings that are seldom understood. Computer vision-based systems will aid deeper collection of data, including player position tracking spatial behaviour. Analysis beyond traditional scorecards are pushed into granular insights around movement, intent and positioning. As a result, big data is poised to acquire greater consequence in cricket, as predictive models mature alongside the growing volumes of AI-derived data.

2. Contextual storytelling

The second role is to find contextual stories by sifting through the massive amounts of data being generated by each ball. The scope of matching AI-generated storytelling, with or without graphical visualisation will be a constant struggle for statisticians in the coming period. The manual interpretation of large datasets will become inefficient because AI systems surface patterns, trends and narratives in real-time. 

3. Production standardisation

AI further steadies the unevenness of production quality, allowing narratives from less televised matches to approach the visual coherence of marquee broadcasts. AI will soon be able to generate and trigger contextually driven graphics visualisation, aware of the specific statistics to be displayed when required. The expansion of automation is resulting in production rooms becoming more AI driven, which reduces the dependency on larger teams, directors, producers, operators, and in some cases eliminates certain roles altogether. 

4. Broadcast for one 

Cricket remains one of the largest broadcast properties, yet it is now experienced at the level of the individual viewer. Gen Z primarily watches the game on personal devices, where engagement is defined by autonomy, control and selective attention. Broadcast, once built as a uniform feed for a collective audience, now also functions as a personal interface. The viewer is no longer limited to receiving a single, standardised presentation, but engages with the game through preferred players, key moments and relevant informational layers. This creates a broadcast environment where scale and individuality coexist. Cricket continues to operate as a shared cultural spectacle, but its point of experience now sits firmly with the individual viewer.

5. Richer visualisation for Gen Z

The final role centres around the visualisation of the game, where AI models are already able to contextually convert a widescreen video feed to vertical, dramatically improving the mobile viewing experience and aiding Gen Z adoption. As data volumes grow, fully virtualised figures may come to enact live play, allowing a child to experience a cricket match through familiar animated characters. AI-driven virtual camera moves will become a reality and cheap enough for mass adoption, while generative AI will enhance storytelling around technique and strategy. Personalised statistics and graphics delivered on mobile and edge devices will further tailor the viewing experience to individual preferences.

Put together, these changes point to a future where AI does not make cricket simpler by taking depth away, but by helping audiences follow it more easily. For Gen Z, understanding the game will depend less on what they already know and more on how clearly context and consequence are shown on screen. Cricket will keep its depth, but open itself to more viewers.