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.
AUSTRALIA bundled out India for 109 and batted resolutely to reach 156 for four in reply, giving the home side a taste of their own medicine on a raging turner in Indore on Wednesday (1).
On a track where the ball spun viciously from the first session, Matt Kuhnemann (5-16) and Nathan Lyon (3-35) engineered India's spectacular collapse in 33.2 overs.
Usman Khawaja then showed how to master those conditions as he made 60 and raised 96 runs for the second wicket with Marnus Labuschagne to put Australia ahead.
The visitors, who are 2-0 behind in the four-test series for the Border-Gavaskar Trophy, finished the frenetic opening day 47 runs ahead with six wickets in hand.
Peter Handcomb was batting on seven at the close with Cameron Green on six at the other end.
"I just started playing with my plans and trying to score when I saw a scoring opportunity and respected the good ball when it was there," Khawaja said of his batting approach.
"It's not rocket science to be honest. It was nice to get out there and get a partnership with Marnus."
Beaten inside three days both in Nagpur and Delhi, Australia persisted with a three-pronged spin attack but had to make a couple of changes to their battered squad.
Stand-in skipper Steve Smith introduced spin after five overs of pace bowling by Mitchell Starc and Green, both of whom returned from finger injuries to play their first match of the series.
Regular skipper Pat Cummins is back home to be with his ailing mother, while opener David Warner has returned having fractured his elbow in Delhi.
India captain Rohit Sharma was left to rue his decision to bat first and he himself could have been dismissed twice in the first over from Starc, but Australia did not challenge those on-field decisions.
It did not really matter though once the spinners took over.
Kuhnemann removed Rohit (12) stumped and, in his next over, cut short Shubman Gill's (21) promising knock to unhinge India.
Lyon then joined the party, dismissing Cheteshwar Pujara and Ravindra Jadeja in his successive overs and India slumped to 45-5 after a frenetic opening hour.
Virat Kohli (22) gamely hung on for a while but once Todd Murphy trapped him lbw, wickets started tumbling and India eventually wilted half an hour into the second session.
After the innings break, India predictably began with spin from both ends and Travis Head (nine) fell lbw to Ravindra Jadeja (4-63) in the second over of the innings.
Labuschagne, who made 31, combined with Khawaja to steady the innings and had luck on his side too.
The batsman was yet to open his account when he dragged the ball onto his stumps but bowler Jadeja was found to have over-stepped.
This was the third time in the series that Jadeja's penchant to bowl no-balls cost him a wicket.
Labuschagne got another reprieve later when India opted against reviewing an lbw decision against him and replays subsequently confirmed the batter would have been dismissed had they done so.
Jadeja eventually removed Labuschagne just before Australia drew level and went on to pick the crucial wickets of Khawaja and Smith (26).
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.