Whether it is dud decisions, awful acting, nepotism, terrible writing, sloppy direction, an actor in his late 50s playing a hero in his 20s, or misguided marketing, there is a lot that can be logically blamed for a Bollywood film flopping.
But in Hindi cinema – where logic is often missing – many in the industry still believe the spelling of titles and star names can determine a film’s fate. Yes, you read that correctly. They think a few extra letters can magically make all the difference.
This was perfectly illustrated by the recently released The Bhootnii – with an extra ‘i’, because why not?
Originally titled The Bhootni, the horror comedy was renamed on the sacred advice of a spiritual leader named Ayush Gupta, who presumably read the stars, lit some incense, and declared that adding an “i” would turn it into a box office smash.
Unfortunately for producer and lead actor Sanjay Dutt, the audience disagreed – and that too in spectacular fashion.
Despite horror comedies being popular in Hindi cinema right now, this flop film failed miserably. The extra “i” made absolutely no difference – but that did not stop a press release from being proudly issued, celebrating the spelling change.
The Bhootnii
The trend of stuffing film titles with extra letters has now been going on for decades – which is why so many titles look spectacularly silly. Spoiler alert: instead of becoming box office sensations, most of these films have sunk without a trace.
And it is not just film titles – stars themselves have tried tweaking their names in hopes of changing their luck. Kareena Kapoor briefly flirted with being Kariena. Vivek Oberoi attempted to save his sinking career by becoming Viveik, but that did nothing to slow the fall.
Ayushmann Khurrana, Rajkummar Rao, Manoj Bajpayee and Riteish Deshmukh are just some of the many actors who have changed the spelling of their names.
Currently, Abhishek Bachchan is trying to revive his fortunes by adding an extra ‘A’, now appearing as “Abhishek A Bachchan” – including in this week’s big Bollywood release Housefull 5. Somehow, a spelling change seems to have taken priority over finding strong scripts with well-written characters and actual commercial appeal.
While Bachchan is adding an ‘A’, Ajay Devgan has done the opposite – dropping one. His credit now reads “Ajay Devgn”, but that has not stopped a string of flops from piling up and outweighing his successes.
Instead of rearranging letters like a Scrabble addict, filmmakers and stars would be better off focusing on strong scripts, better acting, and films that audiences actually want to see. They should swap spelling gymnastics for spellbinding stories – or perhaps get inspired by Karan Johar.
The producer-director was once a loyal follower of the ‘K’ cult – with films like Kuch Kuch Hota Hai, Kabhi Khushi Kabhie Gham, Kal Ho Naa Ho and Kabhi Alvida Naa Kehna. But after watching the acclaimed Lage Raho Munna Bhai, which brilliantly mocked numerology, he had a change of heart and ditched the superstition. He went on to become one of Bollywood’s most powerful producers.
Those still clinging to spelling stunts should take a long, hard look at disasters like The Bhootnii, which failed so spectacularly.
And let’s be honest – if numerology really worked in Bollywood, every fortune teller in Mumbai would be producing weekly blockbusters. The harsh truth is that this obsession with extra letters is just a flimsy band-aid over a gaping creative wound.
With Bollywood going through its worst phase in history, more insiders are foolishly turning to numerology and extra vowels, rather than investing in strong writing, bold ideas and original content.
Throwing in an extra letter or renaming your hero is not the answer. Better films are.
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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