At Sunrise Radio, Lit provided the first break to many young people who later found jobs with the organisations like BBC Asian Network
By Amit RoyJul 01, 2023
WARM tributes have been paid to Avtar Singh Lit, who challenged the broadcasting rules of his day when he set up Sunrise Radio in 1989 and was unfairly labelled a “pirate” by the authorities. His death on Tuesday (27) in his 70s was announced by the station which described him as a “pioneer” in the field of Asian radio. “We are incredibly proud of his legacy which has given much joy and opportunity to so many.
Avtar is survived by his mother, five children – Surjit (51), Tony (50), Bobby (49), Serena (24), and Robbie (19) – and his five grandchildren. He was
a much-beloved son, father, and grandfather,” it added.
Lit was born in Punjab, came to Britain in 1962, and, according to his CV in Jasbir Singh Sachar’s Asian Who’s Who went to secondary school in Kent before entering the Royal Navy College in Chatham. He dabbled, sometimes controversially, in a variety of businesses, and got involved in the management of Sunrise Radio. But he always maintained his real love was broadcasting. And it was at Sunrise Radio that he provided the first break to many young people who later found jobs with the BBC Asian Network.
He was a familiar and flamboyant figure in Southall, entertained frequently at the spacious home he bought in Osterley, and drove around in a Rolls-Royce with a personalised number plate. He presented a phone-in programme on Sunrise for many years and was not afraid to wade into the complex Punjabi politics of Southall. He also had a large stock of entertaining anecdotes.
On a trip to India, he said he was offended when a visa officer at the British High Commission in Delhi refused to give clearance to someone Lit was trying to sponsor for a visit to the UK. True or not, Lit said he reprimanded the officer: “You talk big for someone on £20,000 a year.”
Lit was not prepared to leave the matter without further intervention. Discovering the officer was due to fly to the UK on home leave, Lit claimed he had a quiet word with a contact in the airline concerned, with the result “the man was off-loaded before the flight took off for London”.
Lit had a love-hate relationship with Piara Singh Khabra, who was Virendra Sharma’s predecessor as the Labour MP for Southall. Lit stood unsuccessfully as an independent parliamentary candidate against Khabra in 2001, but maintained cordial relations with the MP until his death in 2007.
“He used to come home for dinner,” said Lit. “He had a wicked sense of humour and we did laugh together. He was the last of the old-style, first-generation community leaders. He helped to develop the Indian Workers’ Association. He packed the membership of the local Labour party and gained control.”
In the by-election in 2007, triggered by Khabra’s death, Lit’s son Tony, stood as the Tory candidate with his father’s blessing. He came third with 8,230 votes (22.5 per cent) against Sharma’s winning 15,188 (41.3 per cent).
Lit was not above amusing himself by causing mischief, as he admitted he did in 1995 when many Hindus in the UK, India and elsewhere believed their deities were drinking milk. Lit said in the Sunrise Radio washroom, he had chanced across an old report in an Indian newspaper of a deity drinking milk in a temple. He decided to recreate the phenomenon in Southall.
“So, coming out from the washroom, I summoned Ravi Sharma, a former priest and now a very famous broadcaster, to my office,” Lit later confided to Eastern Eye. “Within three minutes of his arrival in my office, Ravi was chasing the priest at Lady Margaret Road Mandir in Southall and, having got through to him on the telephone, the priest was requested to offer milk to the gods while we stayed on the telephone. A few minutes later the priest reported God was drinking the milk.
“I dispatched a reporter from the newsroom along with Ravi Sharma to go to the mandir [temple] and report back to me once they verified the gods were drinking milk. And they did, so I wrote up the script and sent it to my newsroom to carry it as the last item on the 2pm news.
“I did pause before I instructed the news department to carry it because I knew what was likely to happen across Britain in the next three or four hours in
the Hindu and Sikh community. By 3pm it became top story on Sunrise News. By 4pm Southall shops ran out of milk and long queues started to form outside the mandir. By 4.30pm Sunrise Radio start receiving phone calls from other mandirs in the UK and Europe as they jumped on the bandwagon that their gods were also drinking milk. No self-respecting priest or a committee member of a mandir wanted to be left behind.
“By 5pm, queues were getting longer outside the mandirs and the milk shortage was getting greater in west London and shopkeepers had cottoned on and upped the prices. “BBC, ITV and Sky News dispatched their outside broadcast units to broadcast live from outside Sunrise Radio and the mandir. The following day, Fleet Street descended on Southall and the story dominated the news across the world for the next 72 hours. On the Sunday, David Frost’s programme went live from Southall. The rest is history.”
Lit laughed as he said: “On reflection, I think that we need more such miracles in the UK.”
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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