International
Kani Kusruti wins IMDb Breakout Star award, reflects on career and characters
MUMBAI: When talent meets authenticity, the world takes notice. Acclaimed actor Kani Kusruti has been honoured with the prestigious IMDb Breakout Star STARmeter Award. Recognising her remarkable rise on the Popular Indian Celebrities list, the award cements her status as a performer on the brink of global recognition. The list, derived from the page views of 250 million monthly visitors on IMDb, has a track record of predicting breakout stars.
In an exclusive conversation with IMDb, Kusruti shared her experiences, reflecting on her most relatable roles, the challenges of embodying characters, and the life lessons that have shaped her journey.
Discussing her roles as Prabha in All We Imagine as Light and Anila in Girls Will Be Girls, Kani revealed how the two characters affected her differently.
“When I read Anila, I honestly did not understand her. It took a while for me to get into the character, but I felt because it took a while to get into character, it also took a time to get out of the character. After the film shooting also, sometimes I think, ‘What if Anila is in this situation, how would she react?’ Some of her physical aspects lingered with me more,” Kusruti admitted.
She described Prabha as familiar, “I understand Prabha. I know many women like that, so immediately when I read it, I understood her. But I don’t even want to be like her… The only difference is, Prabha I knew immediately. The moment I read, I knew her, I understood who she is, or I know people like her. Anila I did not know. Only after the film was released, many people I know were like, ‘Hey, you know my mom is like this,’ and even people whom I don’t know would write to me, and I’m like, ‘Where are these people? How did I never observe people like these?’”
When asked about the toughest part of being an actor, Kusruti highlighted the nuances of becoming someone else.
“As an actor, of course the most challenging is to really be someone else. It’s not like you become that person, that you lose your mind, but to talk differently, to use different rhythms when you are speaking, how you are sitting. So all the physical attributes of another person, which has to come so naturally to you that it’s seamless, I need a little time to prepare for that,” she explained. She added that starting without enough preparation is particularly challenging, “It is only after 3-4 days or a week that you discover the person.”
Kusruti shared that her journey into acting was unplanned, “I did not become an actor because I had passion for acting from childhood. It was an accident; I happen to be an actor. I was more of a lover of science… I never placed myself to be an artist. I am a trained actor, so I have been in a theatre school. I will send myself to workshops to check how my craft is turning into and try to have rigorous practice.”
Instead of direct advice, Kusruit credits her growth to observing others, “No teacher has sat with me, or no director has told me this is one piece of advice, but it’s observing them—how they have turned into amazing human beings—that has kind of moved me with certain individuals.”
With her performances in All We Imagine as Light and Girls Will Be Girls, Kusruti has proven her ability to embody complex characters. As she continues to evolve as an actor, fans eagerly await her next move.
To watch Kusruti’s exclusive IMDb interview, visit the video link: IMDb Video.
LOS ANGELES: Acting has never been an easy profession, but in recent years, it has acquired a new existential anxiety. Artificial intelligence can now mimic faces, clone voices and, in theory at least, speak any language it is fed. The fear that actors may soon be replaced by algorithms no longer belongs exclusively to science fiction. And yet, despite the rise of digital inauthenticity, some performers remain stubbornly resistant to replacement. The reason is not celebrity, nor even talent. It is language.
On paper, this should not be a problem. AI can translate. It can imitate accents. It can string together grammatically correct sentences in dozens of languages. But acting, inconveniently, is not about grammatical correctness. It is about meaning, and meaning is where AI still falters.
Machine translation offers a cautionary tale. Google Translate, now powered by neural AI, has improved markedly since its debut in 2006. It can manage menus, emails and airport signage with impressive efficiency. What it struggles with, however, are the moments that matter most: idioms, metaphors, irony, and cultural shorthand. Ask it to translate a joke, a threat disguised as politeness, or a line heavy with emotional subtext, and it begins to unravel. Acting lives precisely in those gaps.
This matters because film language is rarely literal. Scripts, particularly in independent cinema, rely on figurative speech and symbolism to convey what characters cannot say outright. Pedro Almodóvar’s Volver is a useful example. The film’s recurring use of red operates on multiple levels: grief, desire, repression, liberation, and memory. These meanings are inseparable from the Spanish cultural context and emotional cadence. A translation may convey the words, but not the weight they carry. An AI-generated performance might replicate the sound, but not the sense.
This is where multilingual actors gain their edge. Performers such as Penélope Cruz and SofÃa Vergara do not simply switch between languages; they move between cultural logics. Their fluency allows them to inhabit characters without flattening them for international consumption. Language, for them, is not an accessory but a structuring force.
Beyond European cinema, this becomes even more pronounced. Languages such as Hindi, Arabic and Mandarin are spoken by hundreds of millions of people and underpin vast cinematic traditions. As global audiences grow more interconnected, the demand for authenticity increases rather than diminishes. Viewers can tell when a performance has been filtered through approximation. Subtle errors, misplaced emphasis, and an unnatural rhythm break the illusion.
There is also a practical dimension. Multilingualism expands opportunity. SofÃa Vergara has spoken openly about how learning English enabled her to work beyond Colombia and access Hollywood roles. But this movement is not a one-way export of talent into English-speaking cinema. Multilingual actors carry stories, styles and sensibilities back with them, enriching multiple industries at once.
Cinema has always thrived on such hybridity. Denzel Washington’s performances, for instance, draw on the cultural realities of growing up African American in the United States, while also reflecting stylistic influences from classic Hollywood and Westerns. His work demonstrates how identity and influence intersect on screen. Multilingual actors extend this intersection further, embodying multiple cultural frameworks simultaneously.
At times, linguistic authenticity is not merely artistic but ethical. Films that confront historical trauma, such as Schindler’s List, rely on language to anchor their moral seriousness. When Jewish actors perform in German, the choice is not incidental. Language becomes a site of memory and confrontation. It is difficult to imagine an automated voice carrying that responsibility without hollowing it out.
This is why claims that AI heralds the death of language miss the point. Language is not just a delivery system for information. It is a repository of history, humour, power and pain. Fluency is not only about knowing what to say, but when to hesitate, when to understate, and when to let silence do the work. These are not technical problems waiting to be solved; they are human instincts shaped by lived experience.
AI may one day improve its grasp of metaphor and nuance. It may even learn to sound convincing. But acting is not about sounding convincing; it is about being convincing. Until algorithms can acquire memory, cultural inheritance and emotional intuition, multilingual actors will remain irreplaceable. AI may learn to speak. But it cannot yet learn to mean.
In an industry increasingly tempted by shortcuts, language remains stubbornly resistant to automation. And for actors who can move between worlds, linguistic, cultural, and emotional, that resistance is not a weakness, but a quiet, enduring advantage.
