Actress Aneesha Joshi played a pivotal part in season 5 of the popular American medical drama series The Resident, created by Amy Holden Jones, and won raves for her performance.
What made her experience even more memorable was the fact that she got to share the screen space with her real sister on the show.
“I am lucky enough to share the screen with my sister for the very first time! Working with Anuja on building Leela and Padma’s storyline is a joy and truly inspiring as an actor,” she tells Eastern Eye in an interview. Read on…
I have to begin by asking how you have been spending time with so many restrictions being lifted up, and how has shooting on sets changed?
For me personally, strict restrictions being lifted and being fully vaccinated (with a booster) has certainly eased my feelings of fear surrounding this new strange world we all live in. It’s important to remember that we aren’t quite at the end yet, so I do my best to keep myself healthy and minimize the risk of exposure to not only protect myself but those who surround me as well.
Shooting with Covid-19 protocols in place is quite a unique experience. There are definitely social distancing precautions being taken whenever possible and masks are mandatory while occupying enclosed spaces on units. I am so amazed at how productivity has not halted despite so many rules and regulations in place! As the adage goes: the show must go on, and it truly does- safely of course.
Would you like to share your experience from the sets of Fox's new show?
My experience working on The Resident has been nothing short of a dream. This show is so compelling, entertaining and has such a talented cast and crew. Not to mention, I am lucky enough to share the screen with my sister for the very first time! Working with Anuja on building Leela and Padma’s storyline is a joy and truly inspiring as an actor. It feels as if I am in complete sync with her emotionally and creatively. Coming to work on The Resident, every day has been such a joy, and I truly feel like I am learning so much on the job by just absorbing and observing my surroundings. I want to thank Amy Holden Jones, Rob Corn, and the entire production team for taking this chance on my addition to the cast and allowing me to express myself as Padma so freely.
How did you develop an interest in acting? How did you discover your passion for it?
Growing up, I was always involved in performing arts. I regularly participated in school plays, learned music and singing, and studied dance quite intensively. I studied Ballet, Jazz, Latin Ballroom, Kathak, Bharatnatyam, and Kuchipudi. Throughout my intensive arts education, I always felt strongly that Kuchipudi was not just dancing, but a form of acting. Each individual piece in Kuchipudi tells a detailed and beautiful story of an avatar, deity, or devotee. There are so many epic stories in Hindu mythology, and Kuchipudi allows for the communication of those stories through intricate dance movements as well as Abhinaya, facial expressions. I believe that my Kuchipudi training is what opened up my eyes to the possibility of pursuing acting professionally!
What is your driving force? Like what is that one thing that motivates you to do better and better?
One of my biggest driving forces is quite honestly the fear of stagnation. I'm a curious person by nature, and I'm always looking for new ways to expand my mind and my creativity. I am a hard worker and believe that there’s no limit to what is within reach, as long as we don’t stop moving towards the goal.
If you weren't an actor, which other profession you would've taken up? And why?
This is a tough question! I have so many different interests. I studied IR and Economics with a concentration in East Asian markets during undergrad, so I feel a corporate job that ties in my creative and analytical side would have been my next choice apart from acting. A marketing consultant for a Shanghainese firm that does a lot of Business in the west? Either that or a chef. Depends on the day!
Quite honestly, I love so many of the new generation talents we have today. I particularly feel that Siddhant Chaturvedi has an undeniable camera presence and a very bright future ahead of him.
A film you wish you were a part of?
Anything directed by Zoya Akhtar, she is such a beautiful, talented and intelligent storyteller. I particularly loved Dil Dhadakne Do!
A genre you would love to try?
Comedy! I feel like it’s one of the most difficult genres to master.
If you had to do a biopic on someone's life, who'd that be?
My own? One day maybe!
Your favorite film?
This is such an impossible question to answer, there are way too many! If I had to choose one at random, maybe it would be Aladdin? I can rewatch it over and over.
An actor you would love to work with?
I would love to do a proper Bollywood masala movie with the one and only Varun Dhawan, no one quite does it like him!
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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