Indian flavours have gained immense popularity, to the extent that foreign food bloggers now share these enticing tastes on Instagram. Among them, a British food blogger has taken it upon himself to explore the diverse regional cuisines of India.
Going by the name @plantfuture on Instagram, Jake Dryan has devoted his profile to immersing himself in Indian cuisine and experimenting with various recipes.
A resident of London, Dryan, a renowned chef, has garnered widespread attention through his endeavour to delve into different regional recipes as part of a weekly series that covers the culinary traditions of various Indian states.
His Instagram page showcases his gastronomic journey, where he states his ambition of creating dishes from every Indian state.
With 13 states already covered, Dryan started the weekly series in August last year and has since showcased the flavours of the states of Gujarat, Punjab, Rajasthan, Maharashtra, Andhra Pradesh, Telangana, and Kerala.
As the plant-based food movement gains momentum, more individuals are recognising the benefits it offers, not only for the environment but also for our physical health.
As the momentum of the plant-based food movement grows, more individuals are recognizing its environmental and health benefits. Indian cuisine, with its abundant vegetarian and vegan options, has found a special place in the hearts of cooks worldwide. Dryan, a true connoisseur, embodies this affinity.
In one of his Instagram videos, he confesses that if he were to pick a favourite cuisine, it would undoubtedly be Indian. His love affair with Indian food began at a tender age, when he would visit his Gujarati friends' homes and savour the family's authentic cooking.
Dryan has set forth on a remarkable mission to prepare dishes from all 29 Indian states. Along the way, he has treated his audience to an array of culinary delights, including the delectable dubki wale aloo from Uttar Pradesh, mouthwatering aloo tikki chaat, tantalising Banarsi tamatar ki chaat, zesty chithranna (lemon rice), delightful Mysore bonda, comforting Bisibele bath, aromatic Methi theplas, tempting Misal pav, flavourful veg biryani, luscious semiya payasam, and refreshing pannakam, a traditional South Indian drink.
Dryan showcases his culinary creations through captivating videos on his official Instagram handle. In no time, his videos have amassed millions of views and garnered thousands of likes. Indian food enthusiasts rejoice in Dryan's regional masterpieces, expressing their admiration and gratitude in the comments section of his posts.
"You are an amazing chef! A westerner who has already explored and adored our cuisine by passionately learning, cooking, and cherishing our food," praises one viewer.
Another suggests, "You should consider opening a restaurant in India."
Dryan's videos have sparked enthusiasm and appreciation among viewers, who celebrate the fact that his content sheds light on the vastness and diversity of Indian cuisine beyond popular stereotypes.
“The best part about the videos is that it shows the world that Indian food is much more than Tikka masala, butter chicken and naan and vegetarian food is much more than peas and lettuce” exclaims an excited commenter.
To many Indians, Dryan has become an inspiration, igniting admiration for his passion and dedication in exploring different cuisines.
“I just love your passion for food and for going that extra mile to try out different cuisines. By sharing this, you are increasing the respect and love for Indian food. Thank you for making these videos” expresses a grateful viewer.
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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