New Delhi: As millions stay glued to their screens nearly every evening for over two months to watch the Indian Premier League, a boundary is clipped, packaged and pushed out to millions within seconds.
The same moment appears across formats: a vertical video tracking the ball on mobile, a short highlight in multiple languages, or a player-specific reel tailored for different platforms almost simultaneously.
As artificial intelligence advances, it also starts impacting sports broadcasts. With a tournament like the IPL running for weeks, involving over 70 matches, multiple feeds and millions of viewers, AI allows that ecosystem to function at unreal speed.
From building promos across languages, powering voice and scripting variations, to breaking live matches into key moments in real time and distributing them simultaneously, AI is being integrated seamlessly. What once took minutes, sometimes longer, now happens almost instantly.
Some of the most followed sports and broadcasters globally have openly embraced the use of AI. But what is it like in India – with cricket – unarguably the biggest sport in the country and Star Sports and JioStar, the top broadcasters of the sport—and why must it remain different from how it is used in other sports?
“Four or five years ago, most of this was largely manual, with AI playing a very small role. Today, it sits across multiple parts of the pipeline,” said Prashant Khanna, head of JioStar’s Sports and Live Experiences Production Technology and Services.
“For us, AI initially crept through logging, tagging and automated highlights. Today, it’s embedded across the entire chain, from live clipping and metadata enrichment to post-production and personalised distribution.”
“In promos, especially voice in English and Hindi, it’s now almost entirely AI-assisted. In graphics and language workflows, it’s roughly in the 40–50% range. That includes things like generation, translation and versioning.”
Multilingual workflows have scaled sharply. Scripts, captions and commentary are translated and adapted across languages with unprecedented speed without needing to be rebuilt from scratch.
Visual elements like player illustrations, broadcast graphics and statistics, which earlier required long and rigorous production cycles, are now generated far more quickly. In cricket, the use of AI is aimed to improve efficiency and scale, but not alter the core experience. It is embedded deeply in workflows yet remains largely invisible in the final output.
While efficiency is important, accessibility and experience also matter. During the IPL, AI is used to build a vertical video player that automatically tracks the ball for mobile viewers to enhance consumption on smaller screens.
It is also used in sign-language feeds to adjust the interpreter’s size when graphics appear, ensuring nothing important is blocked. Key moments, short clips and player-based highlights are broken almost instantly and distributed in parallel.
As a result, the content output has expanded, with multiple versions now being created in parallel across formats, languages and platforms, and multilingual consumption has thrived.
Recently, UFC President and CEO Dana White dismissed criticism of AI-generated promotional material, fans resisted the soulless visuals and the erosion of human storytelling. The reaction echoed earlier skepticism when the National Basketball Association introduced its AI-powered “Coach Nat” initiative in 2022.
From the NBA’s use of AI in highlights and officiating support to Amazon’s Prime Insights features on NFL broadcasts, artificial intelligence is now firmly embedded in global sports production.
But in cricket production, the difference lies in how visibly it is used.Cricket and its broadcasters seem to be leaning into AI where fans are least likely to notice it.
AI in cricket needs to be subtle
“If you can tell it’s AI, we aren’t doing our job well,” he added. At JioStar, for instance, AI is being used to automatically log and tag vast archives, clip highlights in real time, power multilingual feeds by converting commentary into regional languages and optimise content distribution across platforms and devices.
“The real value is distribution intelligence — getting the right content to the right fan faster across 20-plus feeds,” Khanna said.
But most of this remains invisible to the viewer. Fans appear to resist when AI tries to replace the human layer of storytelling rather than support it.
“Sport is built on emotion, context and instinct,” he said. “AI powers scale and speed, but judgment and accountability remain human-managed.”
While long-term trajectory could move from AI-assisted workflows to more AI-led systems, the emphasis, at least in cricket, remains on control frameworks and human supervision, regardless of how much AI is integrated.
“Editorial oversight and attribution are non-negotiable guardrails,” he said. “The audience shouldn’t see AI,” Khanna said. “They should just feel a better experience.”
When the use of AI is less about enhancing sport, backlash occurs when it is flattened instead. Cricket’s direction is clear. AI should make broadcasts faster, smarter and more accessible without ever becoming the main character. Other sports may not care if fans notice, cricket believes that they shouldn’t.