Popular Indian singer discusses her enthralling journey and recent song Dil Mera
By Asjad NazirAug 10, 2024
IT WAS perhaps inevitable that popular Indian playback singer Antara Mitra would pursue a career in music.
Growing up in Maslandapur, a small town near Kolkata in east India, her earliest memories are connected to music because of her father.
“The very first thing that connected me to music is my father. He's a music teacher and runs a music academy. So, he's the one who introduced me to music,” recalled Mitra.
That early learning from her music maestro father pushed Mitra towards a professional singing career filled with hits, including record-breaking Bengali song Baby Jaan, much loved Bollywood track Gerua and the massively popular Kesariya from Brahmastra.
Mitra is grateful for her journey so far and said: “My journey as a singer has been very fortunate and filled with blessings. I never expected music to become my profession. I always saw it as a strong passion. I'm thankful to god that it's now my profession, too.”
The in-demand singer first came to prominence as a fresh-faced hopeful on Indian Idol 2. Although she didn’t win the popular reality TV show, she finished in the top five and that inspired her to move to Mumbai and pursue a professional career.
She fondly reflected on her Indian Idol stint and recalled: “My memories of Indian Idol are very fuzzy, because what was happening at that time was so unbelievable and strange that I can't really describe it. Looking back, all I remember is a girl from a small village who wanted to sing on a reality show and ended up in the top five. The whole story seems unreal and strange to me.”
Mitra moved to Mumbai and took part in music reality show Junoon – Kuchh Kar Dikhaane Ka. Although she didn’t win, it gave the hardworking singer further confidence to pursue her lifelong singing dream.
Her talent was quickly recognised by top music directors. She sang for high-profile films such as Jab We Met, Raajneeti, Golmaal 3, Dil Toh Baccha Hai Ji and R…Rajkumar.
Mitra got her global breakthrough with 2015 Bollywood blockbuster Dilwale.
Her duets with Arijit Singh - Gerua and Janam Janam - became global hits.
She said, “I've had the privilege of singing some incredible duets, and each collaboration has been unique and memorable in its own way. However, the duets I particularly enjoyed were Gerua and Janam Janam with Arijit Singh. It was a fantastic experience blending our voices and emotions to create beautiful musical moments.”
Mitra has since done many memorable collaborations in different languages with A-list singers and top music directors.
Mitra’s recently released romantic number Dil Mera
“Collaborating with talented artists brings a special energy and creativity to the studio, and I cherish every opportunity to harmonise and connect with fellow musicians through music,” she said.
Despite several hit songs, the naturally gifted singer confessed that one remains close to her heart. “Out of all the songs I've sung, Dil Hi Toh Hai, written by Gulzar, is very special to me,” she revealed.
Asked if she was surprised by the success of any of her songs, Mitra said, “When Saree Ke Fall Sa (R…Rajkumar) became a big hit, I was surprised – because, initially, I didn't think the line ‘saree ke falsa’ would make sense to people. This particular line wouldn't translate well or be understood. But surprisingly, people did understand what it meant.”
Mitra’s repertoire of film songs also includes singles, and she adopts a different approach, depending on the genre.
“Yes, my approach varies between film songs and standalone singles. For film songs, I focus on portraying the emotions and narrative of a specific character or storyline, collaborating closely with the composer and director to achieve the desired cinematic impact.
“Standalone singles provide me with creative freedom to explore diverse themes and musical styles that resonate with me personally, (and I) often collaborate with other artists to create unique and engaging music. Both formats allow me to showcase different aspects of my artistry and I'm grateful for it.”
Mitra’s recently released romantic number Dil Mera, captures the painful story of betrayed love.
It was released on the music label, Bajao Records, founded by popular singer Kanika Kapoor. Mitra said about Dil Mera, “The inspiration came from a deeply personal experience or emotion that resonated with me. Collaborating with talented composers and lyricists also played a significant role in shaping the song, as we worked together to bring our creative visions to life.”
Although she does dance numbers well, Mitra is at her best with heartfelt, slower numbers. She said, “I try to connect deeply with the lyrics and story of the song. This helps me bring genuine emotion into my voice. It's all about feeling the music and letting those emotions flow naturally when I sing.”
Not surprisingly, Mitra has also made a name for herself on the live circuit and regularly enthrals audiences with her performances on stage.
“Live performances allow me to connect directly with my audience. It's an amazing feeling to see and feel their reactions in real time. It's always an unforgettable experience,” she said.
Mitra wants to carry on singing a wide variety of songs in diverse languages.
She added, “If I could master something new in music, I would love to delve deeper into the intricacies of music production and arrangement. Understanding the technical aspects of sound engineering, mixing, and mastering would not only enhance my overall understanding of music, but also allow me to have greater creative control over my recordings.”
The popular music star revealed the late legendary singer, Lata Mangeshkar, was her greatest music hero. “She has been an icon in the Indian music industry for decades, known for her unparalleled voice, versatility, and timeless melodies. Lataji's dedication to her craft, impeccable singing technique, and ability to convey deep emotions through her songs have always inspired me. She has set a benchmark in playback singing that few can match, and her influence on generations of singers, including myself, is profound.”
AI can make thousands of podcast episodes every week with very few people.
Making an AI podcast episode costs almost nothing and can make money fast.
Small podcasters cannot get noticed. It is hard for them to earn.
Advertisements go to AI shows. Human shows get ignored.
Listeners do not mind AI. Some like it.
A company can now publish thousands of podcasts a week with almost no people. That fact alone should wake up anyone who makes money from talking into a mic.
The company now turns out roughly 3,000 episodes a week with a team of eight. Each episode costs about £0.75 (₹88.64) to make. With as few as 20 listens, an episode can cover its cost. That single line explains why the rest of this story is happening.
When AI takes over podcasts human creators are struggling to keep up iStock
The math that changes the game
Podcasting used to be slow and hands-on. Hosts booked guests, edited interviews, and hunted sponsors. Now, the fixed costs, including writing, voice, and editing, can be automated. Once that system is running, adding another episode barely costs anything; it is just another file pushed through the same machine.
To see how that changes the landscape, look at the scale we are talking about. By September 2025, there were already well over 4.52 million podcasts worldwide. In just three months, close to half a million new shows joined the pile. It has become a crowded marketplace worth roughly £32 billion (₹3.74 trillion), most of it fuelled by advertising money.
That combination of a huge market plus near-zero marginal costs creates a simple incentive: flood the directories with niche shows. Even tiny audiences become profitable.
What mass production looks like
These AI shows are not replacements for every human program. They are different products. Producers use generative models to write scripts, synthesise voice tracks, add music, and publish automatically. Topics are hyper-niche: pollen counts in a mid-sized city, daily stock micro-summaries, or a five-minute briefing on a single plant species. The episodes are short, frequent, and tailored to narrow advertiser categories.
That model works because advertisers can target tiny audiences. If an antihistamine maker can reach fifty people looking up pollen data in one town, that can still be worth paying for. Multiply that by thousands of micro-topics, and the revenue math stacks up.
How mass-produced AI podcasts are drowning out real human voicesiStock
Where human creators lose
Podcasting has always been fragile for independent creators. Most shows never break even. Discoverability is hard. Promotion costs money. Now, add AI fleets pushing volume, and the problem worsens.
Platforms surface content through algorithms. If those algorithms reward frequency, freshness, or sheer inventory, AI producers gain an advantage. Human shows that take weeks to produce with high-quality narrative, interviews, or even investigative pieces get buried.
Advertisers chasing cheap reach will be tempted by mass AI networks. That will push down the effective CPMs (cost per thousand listens) for many categories. Small hosts who relied on a few branded reads or listener donations will see the pool shrink.
What listeners get and what they lose
Not every listener cares if a host is synthetic. Some care only about the utility: a quick sports update, a commute briefing, or a how-to snippet. For those use cases, AI can be fine, or even better, because it is faster, cheaper, and always on.
But the thing is, a lot of podcast value comes from human quirks. The long-form interview, the offbeat joke, the voice that makes you feel known—those are hard to fake. Studies and industry voices already show 52% of consumers feel less engaged with content. The result is a split audience: one side tolerates or prefers automated, functional audio; the other side pays to keep human voices alive.
When cheap AI shows flood the market small creators lose their edgeiStock
Legal and ethical damage control
Mass AI podcasting raises immediate legal and ethical questions.
Copyright — Models trained on protected audio and text can reproduce or riff on copyrighted works.
Impersonation — Synthetic voices can mirror public figures, which risks deception.
Misinformation — Automated scripts without fact-checking can spread errors at scale.
Transparency — Few platforms force disclosure that an episode is AI-generated.
If regulators force tighter rules, the tiny profit margin on each episode could disappear. That would make the mass-production model unprofitable overnight. Alternatively, platforms could impose labelling and remove low-quality feeds. Either outcome would reshape the calculus.
How the industry can respond through practical moves
The ecosystem will not collapse overnight.
Label AI episodes clearly.
Use discovery algorithms that reward engagement, not volume.
Create paywalls, memberships, or time-listened metrics.
Use AI tools to help humans, not replace them.
Industry standards on IP and voice consent are needed to reduce legal exposure. Platforms and advertisers hold most of the cards here. They can choose to favour volume or to protect quality. Their choice will decide many creators’ fates.
Three short scenarios, then the point
Flooded and cheap — Platforms favour volume. Ads chase cheap reach. Many independent shows vanish, and audio becomes a sea of similar, useful, but forgettable feeds.
Regulated and curated — Disclosure rules and smarter discovery reward listener engagement. Human shows survive, and AI fills utility roles.
Hybrid balance — Creators use AI tools to speed up workflows while keeping control over voice and facts. New business models emerge that pay for depth.
All three are plausible. The industry will move towards the one that matches where platforms and advertisers put their money.
Can human podcasters survive the flood of robot-made showsiStock
New rules, old craft
Machines can mass-produce audio faster and cheaper than people. That does not make them better storytellers. It makes them efficient at delivering information. If you are a creator, your defence is simple: make content machines cannot copy easily. Tell stories that require curiosity, risk, restraint, and relationships. Build listeners who will pay for that difference.
If you are a platform or advertiser, your choice is also simple: do you reward noise or signal? Reward signal, and you keep what made podcasting special. Reward noise, and you get scale and a thinner, cheaper industry in return. Either way, the next few years will decide whether podcasting stays a human medium with tools or becomes a tool-driven medium with a few human highlights. The soundscape is changing. If human creators want to survive, they need to focus on the one thing machines do not buy: trust.
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