Pooja Pillai is an entertainment journalist with Asian Media Group, where she covers cinema, pop culture, internet trends, and the politics of representation. Her work spans interviews, cultural features, and social commentary across digital platforms.
She began her reporting career as a news anchor, scripting and presenting stories for a regional newsroom. With a background in journalism and media studies, she has since built a body of work exploring how entertainment intersects with social and cultural shifts, particularly through a South Indian lens.
She brings both newsroom rigour and narrative curiosity to her work, and believes the best stories don’t just inform — they reveal what we didn’t know we needed to hear.
Shots were fired at Kap’s Café in Surrey, Canada, owned by comedian Kapil Sharma, just days after its opening.
Khalistani extremist Harjit Singh Laddi, linked to banned group BKI, claimed responsibility.
The motive cited was an old comedy segment from The Kapil Sharma Show that allegedly mocked Nihang Sikhs.
No injuries were reported; Canadian authorities are investigating the incident.
Comedian Kapil Sharma’s recently launched Kap’s Café in Surrey, British Columbia, was the target of a shooting in the early hours of 10 July. Though no one was harmed, the property sustained significant damage. A known Khalistani extremist, Harjit Singh Laddi, has claimed responsibility for the attack, citing perceived religious disrespect on The Kapil Sharma Show.
Kap’s Cafe in Surrey was struck by gunfire late at night with staff still insideInstagram/thekapscafe_
Shooter linked to Khalistani group Babbar Khalsa International
Harjit Singh Laddi, a wanted terrorist on India’s National Investigation Agency (NIA) list, said he and another operative, Toofan Singh, were behind the shooting. Laddi is associated with the banned organisation Babbar Khalsa International (BKI), which the Canadian government recognises as a terrorist group.
In a social media statement, Laddi said the attack was a reaction to a past comedy sketch where a character wore traditional Nihang Sikh attire while delivering humorous lines. “These were considered offensive and hurt religious sentiments,” he wrote. “No spiritual identity should be ridiculed under the pretext of comedy.”
Laddi also claimed the Sikh community had reached out to Sharma’s team seeking an apology but received no response.
Kaps Cafe Instagram Story Instagram Screengrab/thekapscafe_
Café issues emotional statement, vows to stay open
Kap’s Café, operated by Sharma’s wife Ginni Chatrath, had only opened on 4 July. Following the attack, the café released a statement on Instagram expressing heartbreak over the violence but reinforced their commitment to the community.
“We opened Kap’s Café with hopes of bringing warmth, community, and joy through delicious coffee and friendly conversation. To have violence intersect with that dream is heartbreaking,” read the post. “We are processing this shock, but we are not giving up.” The message ended with a note of gratitude to supporters and a promise to continue operating: “Let’s stand firm against violence and ensure Kap’s Café remains a place of warmth and community… see you soon, under better skies.”
Kaps Cafe Instagram Story Instagram Screengrab/thekapscafe_
According to Surrey Police, officers responded to reports of gunfire at the 8400 block of 120 Street around 1:50 am on July 10. Bullet damage was found on the cafe’s exterior while staff were still inside. No injuries were reported.
While no arrests have been made, Khalistani extremist Harjit Singh Laddi publicly claimed responsibility for the shooting in a social media post. Police have not officially confirmed his involvement. Authorities continue to investigate potential links to terrorism, organised crime, or extortion, and are also examining whether this incident may be connected to other recent threats involving Indian-origin individuals in Canada.
The shooting comes amid already strained relations between India and Canada over Khalistani separatist activities. In 2023, the killing of Sikh separatist Hardeep Singh Nijjar in Surrey led to diplomatic fallout after Canada alleged Indian involvement.
Harjit Singh Laddi, believed to be residing in Germany, is accused of masterminding multiple violent acts in Punjab, including the April 2024 killing of VHP leader Vikas Prabhakar. Indian authorities have placed a reward of £8,630 (₹10 lakh) for information leading to his arrest.
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.
By clicking the 'Subscribe’, you agree to receive our newsletter, marketing communications and industry
partners/sponsors sharing promotional product information via email and print communication from Garavi Gujarat
Publications Ltd and subsidiaries. You have the right to withdraw your consent at any time by clicking the
unsubscribe link in our emails. We will use your email address to personalize our communications and send you
relevant offers. Your data will be stored up to 30 days after unsubscribing.
Contact us at data@amg.biz to see how we manage and store your data.