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 Liverpool and England goalkeeper David James says lockdown has given him plenty of time to indulge in his passion for art and also plot a move into management.
The 49-year-old, capped 53 times, cut his managerial teeth with Kerala Blasters in south India, but now believes it is time to look closer to home.
James, whose father is Jamaican, is impressed by the Premier League's support of the Black Lives Matter movement and England forward Raheem Sterling's comments about under-representation in coaching roles amongst the BAME community, although as a lover of statistics, he admits the situation is complicated.
"Solely looking at Raheem's comments, I think someone has to be looking into opportunities that are available," James told Reuters.
"It's not just saying there are 92 clubs and 92 jobs available, so there should be X amount of positions available for Black or Asian coaches. The question is how many qualified coaches from that community are there?
"The British population, it's something like 15 or 20 percent non-white. So, like for like in football, would you expect around 15 or 20 in coaching positions in football?
"I'm not sure the data exists but how many qualified coaches are there to fill those roles? Out of those how many actually go for those positions?
"I'm a Pro Licence holder and I'm now considering looking for jobs with regards to management in English football, whereas I haven't in the past. I might be one of those statistics that hadn't applied for something."
RIGHT PLAN
James was a player/coach at Icelandic club IBV Vestmannaeyjar under former Portsmouth team mate Hermann Hreidarsson and obtained his UEFA A Licence during a spell on the coaching staff at Luton Town.
He then managed Kerala Blasters in 2018.
"I've been offered jobs in Asia but now I fancy putting myself forward for a job in England because my world has changed. COVID has given me time to think about things.
"We need to formulate what the right plan is going forward. But in any industry you want the best people in the job, irrespective of background."
James, who made 572 Premier League appearances in spells with Liverpool, Aston Villa, West Ham United, Manchester City, and Portsmouth, says he is happy the momentum behind Black Lives Matter has continued in England.
"The difficulty with the BLM issue is that there are a lot of voices, lots of people have different values as to what it means," James said. "Changing is a process, it doesn't get done in five minutes. What I like about the Premier League is they didn't just stop after two weeks."
James is full of praise for Liverpool manager Juergen Klopp who has just delivered their first league title for 30 years.
"He's transformed the way the club is run. When I've been to Melwood (training ground) since he's been there, everyone from the kitchen staff to the coaches and players... (are) on the same page. There's a sense of equality I didn't experience when I was there."
When not planning his return into football, James has used his artistic talents to create a pin design for #PinYourThanks https://www.pinyourthanks.org-- an initiative allowing people across the UK to give thanks for the work of NHS and frontline staff during the pandemic.
James' pin design features an eyeball with the rainbow colours that have become synonymous with the times.
"I've a couple of sisters working in the NHS, my mum was a nurse, my dad worked for the ambulance brigade so it's really close to me. It's a privilege to be asked to design something," James said. "I have put a forgot-me-not in the middle of the pupil. Because it's not just about Covid, it's forever."
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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