The win: My biggest achievement happened in September 2007 when I won the iconic Sony TV show dance competition Boogie Woogie Senior International Champion title, after winning the Senior UK Champion title earlier that year. This entire experience was extra special as I was the first male winner in the UK and won on the basis of presenting classical dance to Shankar Mahadevan’s song Breathless and Man Mohini from the film Hum Dil
De Chuke Sanam.
Audience vote: During the regional finals of the Boogie Woogie competition I was given the audience vote to go straight to the UK Finals, as well as the judge’s selection. This was a real confidence booster as there were up to 750 people in the auditorium and to know I got a majority of votes was really encouraging.
Dancing in Chidambaram: Every bharatanatyam dancer’s dream, including mine, is to visit the magnificent Chidambaram Temple attributed to Lord Nataraja, the king of dance. I visited the temple on various trips to India, but was also given the opportunity to perform in front of the deity inside the temple. The surreal experience enabled me to feel such a magnetic connection to the deity.
Bharatanatyam arangetram: In February 2010 I performed my arangetram (solo bharatanatyam debut concert), where I danced a full repertoire of pieces in front of an invited audience of friends, family, distinguished members of the community and the Indian dance fraternity. Even though it was snowing, everyone we invited turned up to a full house performance, giving me a standing ovation at the end.
Amazing opera: An amazing moment in life where I was invited to be a part of the premiere of Pandit Ravi Shankar’s first and only opera Sukanya, in collaboration with conductor David Murphy. It was such a joy and really surreal to perform alongside the London Philharmonic Orchestra at the Royal Opera House with live operatic music with Raviji’s score.
NYC gaga intensive: In summer 2018, I visited New York for the first time to attend acclaimed dancer and choreographer Ohad Naharin’s much sought-after course, the gaga intensive. Thanks to a professional development grant from Arts Council England, I was able to experience learning from incredible dancers from Ohad’s company, teaching
his style of movement, research and methodology during an intense one week. I was able to learn and experience New York and also catch two very prominent dance festivals, where I witnessed performances from dance companies from around the world.
The gap year: After completing my A Levels, I travelled to India for my gap year before university to take my bharatanatyam training to a more advanced level with one of my teacher’s gurus, the legendary Dhananjayans at their academy in Chennai. Even though I was alone for the first time, couldn’t speak Tamil and wasn’t really aware of South Indian customs, I knew my love for bharatanatyam was immense and so I fit perfectly into the dance classes. Living in Chennai for 10 months really opened my eyes to how this metropolis works and its magic. I made friends with dance students from all over the world and these associations still exist.
Receiving the travelling fellowship: I was awarded a fellowship to travel to India for an advance study in bharatanatyam by Milapfest, an Indian arts development trust based in Liverpool. I was a regular attendee of their annual dance India summer workshops in Manchester and the award meant so much to me.
Dance India: The most influential experience of my summer holidays as an adolescent teenager was attending the annual International Summer Schools of Indian Dance. I attended my first summer school in 2005 and consecutively for the next four years, I kept going back for more. It was a wonderful opportunity were I got to learn from several gurus of bharatanatyam dance; The Dhananjayans, Professor CV Chandrasekhar, Leela Samson, Priyadarsini Govind, Shijith Nambiar and Parvathy Menon. I also got to watch other forms of Indian classical dance such as kuchipudi, kathak and odissi. I made lifelong friends with so many other dance students.
First UK tour: In 2008, I was a part of Phizzical Production’s UK tour of their production What You Fancy. It was such a great experience as we got to perform fun and energetic Bollywood dance sequences, as well as bond as cast members while travelling throughout the UK and experience amazing new venues. I was director Samir Bhamra’s personal radio as he called me because I made non-stop conversations in the car.
Hiten Mistry is a bharatanatyam dancer and choreographer based in Leicester. He is also the artistic director of Bharatanatyam Leicester. Visit www.bharatanatyamleicester.com
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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