Pramod Thomas is a senior correspondent with Asian Media Group since 2020, bringing 19 years of journalism experience across business, politics, sports, communities, and international relations. His career spans both traditional and digital media platforms, with eight years specifically focused on digital journalism. This blend of experience positions him well to navigate the evolving media landscape and deliver content across various formats. He has worked with national and international media organisations, giving him a broad perspective on global news trends and reporting standards.
ROHAN BOPANNA's worn out knees have not stopped him from climbing the world doubles rankings and the 43-year-old Indian became the oldest player to reach number one after making the Australian Open semi-finals with Matthew Ebden on Wednesday.
Bopanna and Australian Ebden beat Argentine pair Maximo Gonzalez and Andres Molteni 6-4 7-6(5) to ensure that the evergreen Indian would top the rankings once they are updated following the year's first Grand Slam on Monday (22).
Ebden will become world number two having played three more tournaments than Bopanna during the ranking period.
It marked the latest milestone for Bopanna, who became the oldest ATP Masters 1000 champion when he won the Indian Wells doubles crown with Ebden last year and followed it up by becoming the oldest to win a match at the ATP Finals.
Bopanna, who hails from the south Indian state of Karnataka and often jokes that the coffee from his plantation in Coorg was behind his success, said that focusing on his recovery and optimising training had contributed to his longevity.
"The real focus was on that, not to really go out there and run on the treadmill or lift weights," Bopanna told reporters. "That wasn't something I wanted to do when I hired my physio from Belgium last year.
"I told her specifically what I needed, because I have no cartilage in my knees. It's completely worn out.
"I said, no matter what happens, even if the days we're practising and I'm not 100 per cent fit, that's fine. I want to feel 100 per cent fit during these matches. That's the commitment I'd made when I decided to play with Matt."
Bopanna and Ebden were without partners at the end of 2022 but have gelled well since joining forces, winning titles in Doha and Indian Wells and reaching the finals at Rotterdam, Madrid, the US Open, Shanghai and Paris.
They also reached the title clash in Adelaide this year, falling to Joe Salisbury and Rajeev Ram - the latter holding the previous record for the oldest doubles number one at 38 when he got there two years ago.
Bopanna said his mental strength had played a big role in ensuring his partnership with Ebden succeeded.
"I think that's something I've always had when I take up a challenge," said Bopanna.
"I try to persevere in it and bring in that will power. I think that's what has helped us as a team a lot."
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.