J.D. Vance and his wife Usha Vance attend an election night event at the West Palm Beach Convention Center in West Palm Beach, Florida, on November 6, 2024. (Photo by JIM WATSON/AFP via Getty Images)
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.
FORMER US president Donald Trump praised his choice for vice president, JD Vance, during a jubilant speech in Florida on Wednesday (6).
During the speech, he was particularly keen to highlight Vance's fighting spirit.
"Our next vice president is quite the fighter," Trump told his supporters. "Whenever I ask him to face our critics on television, he jumps at the chance. He'll go straight onto CNN or MSNBC and take them head-on."
Trump made sure to mention Vance's wife Usha, describing her as "absolutely remarkable and beautiful".
Usha, who comes from an Indian background and works as a lawyer in San Francisco, has been a steady supporter of her husband throughout the campaign.
At just 40 years old, Vance is set to become America's youngest-ever vice president.
Speaking at the rally, he thanked Trump and promised to help rebuild the American economy.
He said, "We've just seen the biggest political comeback ever in this country. With president Trump leading the way, we'll create the strongest economic recovery America has ever had."
He's stirred up quite a bit of controversy lately, particularly with his remarks about immigration and women's rights.
The making of America's next vice president
Born James Donald Bowman in Middletown, Ohio, JD Vance's life story reflects a remarkable journey through America's heartland. Born to parents of Scottish descent, Don and Bev Bowman, young James' early life was marked by significant changes. After his parents divorced, his mother changed his middle name to David, and he later adopted her maiden name, Vance.
JD Vance (R-OH) (R) and his wife Usha Vance (L) fill out their ballots with their children at a polling place on November 5, 2024 in Cincinnati, Ohio. (Photo by Stephen Maturen/Getty Images)
Raised primarily by his maternal grandparents due to his mother's struggles with substance abuse, Vance's grandmother "Mamaw" played a crucial role in his upbringing. Despite the challenges of growing up in Ohio's Rust Belt, where once-prosperous manufacturing towns were declining, Vance found his path forward through education and military service.
After finishing at Middletown High School in 2003, Vance joined the US Marine Corps. His four-year service included a six-month deployment in Iraq, an experience that profoundly shaped him.
Following his military service, Vance pursued higher education with remarkable success. He earned a bachelor's degree in political science and philosophy from Ohio State University in 2009, followed by a law degree from Yale in 2013.
Vance shot to fame with his 2016 memoir "Hillbilly Elegy", which became a bestseller and was later adapted into a Netflix film. The book chronicled his journey from a challenging childhood in Ohio to the halls of Yale, resonating with readers nationwide.
Donald Trump, in announcing Vance as his running mate, specifically praised the book for championing America's working class.
Vance entered politics and won election as Ohio's junior senator in 2022, taking office in January 2023.
Indian American pride
Usha, 38, could become the first Indian American second lady. She would be the first Hindu spouse of a vice president, succeeding second gentleman Doug Emhoff, who is the first Jewish spouse of a vice president, according to The New York Post.
The daughter of Indian immigrants, Usha grew up in a San Diego suburb. Friends from her childhood described her as a leader and a bookworm.
As of 2014, she was a registered Democrat. Usha is a graduate of Yale Law School and works as a civil litigation attorney at Munger, Tolles & Olson LLP. She has clerked for Supreme Court Chief Justice John Roberts and Justice Brett Kavanaugh while he was a judge on the US Court of Appeals for the DC Circuit.
Usha and Vance met at Yale Law School. The Vances married in 2014 in Kentucky and were blessed by a Hindu priest at a separate event. They have three children: sons Ewan and Vivek, and a daughter named Mirabel.
In a joint interview with her husband few months ago, Usha said she was reluctant to gain greater public exposure.
Reflecting on JD Vance's successful 2022 Senate campaign, she described it as "an adventure" but added, "I'm not raring to change anything about our lives right now." She expressed her support for her husband, saying, "I believe in JD and I really love him, and so we'll just sort of see what happens with our life."
Vance mentioned that his wife is "not a Christian" but is "very supportive" of his deepening faith. Addressing the challenges of an interfaith marriage, Usha said, “There are a lot of things that we just agree on, especially when it comes to family life, how to raise our kids. And so I think the answer really is, we just talk a lot.”
Before law school, Usha earned a bachelor's degree in history from Yale and a Master of Philosophy degree from the University of Cambridge.
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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