A MUSICAL secret weapon in Bollywood across the past decade has been Arko Pravo Mukherjee and his explosive ability to deliver hit tracks that connect with cross-generational listeners.
The singer, songwriter and musician has skillfully balanced film work in diverse languages with standalone singles that have entertained many millions around the world, since making his debut with the Jism 2 soundtrack in 2012. His big successes include monster hit Teri Mitti from Kesari, which has been viewed over a billion times on YouTube.
Eastern Eye caught up with Arko Pravo Mukherjee to discuss his action-packed nine-year journey, upcoming songs, inspirations, future hopes and how lockdown has changed him.
What first connected you to music?
From very early years, I was deeply interested in literature. I think poetry connected me to song writing and consecutively to music.
How do you look back on your music career?
Well, it's my ninth year professionally as a musician. Honestly, compared to the stalwarts, it’s just the beginning, but I look back with gratitude, nostalgia and most importantly with a memory of things I have learnt so far.
Which of your songs are closest to your heart?
Abhi Abhi from Jism 2 as it was my first song in films. Also, Allah Waariyan (Yaariyan), Tere Sang Yaara (Rustom), Saathi Re (Kapoor & Sons), Dariya (Baar Baar Dekho), Nazm Nazm (Bareilly Ki Barfi), Jogi (Shaadi Mein Zaroor Aana), of course, Teri Mitti (Kesari) and Shei Tumi from Bengali film Parineeta.
Did you expect Teri Mitti to become a huge hit?
The whole team was hopeful because Akki sir (Akshay Kumar), KJo (Karan Johar), our entire team at Dharma, director Anurag Singh and my entire music team, at different stages and often multiple times, would get emotional and their throats would choke. I suppose the most truthful judgement is the honest first reaction of a listener. Having said that, a National Award and over a billion views on YouTube were beyond our expectations.
Are you able to tell if a song will be a hit in the studio?
No, I can’t! I can only tell if I like it. In recent times the songs I can’t bear to listen to are often big hits.
Does a successful song put pressure on you for subsequent projects?
Yes, it does! Your value, expectations and the faith of people go up. But that’s a good thing. It’s a big reward for any artist.
Does the fact that you can sing really well help you while composing?
Yes, for sure. It’s a common joke in my team and among colleagues how I am the busiest demo singer. Because I sing all my compositions first before all the singers and musicians
come in, and we go ahead.
Which of your unreleased songs are you most excited about?
I am excited about Watan (Satyamev Jayate 2), Tum Ho (Mission Majnu), O Des Mere (Bhuj: The Pride of India) and the single Raja with Kanika and Ash King.
Has lockdown changed you creatively?
Yes, it has reminded me of an oft-forgotten virtue – patience. It has also given me a chance to tabulate my early years of work, catch up on documentaries and research for two elaborate upcoming albums.
Who would you love to work with?
For films by (directors) Shoojit Sircar and Imtiaz Ali. In terms of artists, musicians Gurdas Maan, Abida Parveen, Adele, Coldplay and many more.
Who is your own musical hero?
U2 and Bruce Springsteen. Both are deep, unique and touch my heart even when listening for the millionth time.
What music dominates your playlist?
Country music.
If you could master something new in music, what would it be?
I would like to get better at what I do instead of learning something new. Hence as a songwriter.
What inspires you?
It could be a wide range of things, including a person, a film, mother nature, nostalgia, history or even an incident.
Do you think labels are giving enough chances to upcoming independent singers?
Yes, labels are keen at the moment to sign new singers. Because some established singers are now capable of producing, marketing and doing everything for a big release, so they are a direct competition to labels. Hence, it is a great time for new singers.
How do you feel that your songs are loved by so many?
I feel truly grateful as I am aware of the talent our country has in music and literature.
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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