Indian batting great Sachin Tendulkar has little doubt that Ben Stokes will lead England from the front in the opening Test against West Indies, with his "controlled aggression" and infectious energy aiding him the most.
Tendulkar spoke about stand-in English skipper Stokes while previewing the three-Test series, which starts in Southampton on Wednesday, with West Indies legend Brian Lara on online platform 100mb. The match marks the resumption of international cricket amid the COVID-19 pandemic.
To a question from Lara about Stokes, Tendulkar said, "He is someone who is going to lead from the front, we have seen that on a number of occasions. He is aggressive, positive and when he has to be slightly defensive he is prepared to do that for the team.
"I always feel controlled aggression produces results and so far whatever I have seen, the aggression has been there but it is controlled. So this is what I think of Ben Stokes."
It is the first time Stokes is leading England having not captained even a first-class team in his career. Regular skipper Joe Root has opted out of the game to attend the birth of his second child
Tendulkar said, "For Ben Stokes from what he has been through in the recent past to where he is today it is a total transformation and it can happen only to someone who is mentally strong.
"When I first looked at him a few years ago, I could see his body language it was so positive and vibrant and that energy is infectious.
"I felt that he was one of those players where in time to come you look back and say Ben stokes, (Andrew) Flintoff, Ian Botham these are the leading all-rounders who played for England. I really rate him highly and his impact on the field is a major one."
On his part, Lara said, besides Jason Holder's captaincy, batting will hold the key for West Indies against a fine England seam attack, and reminded the likes of Shai Hope to take a cue from Tendulkar's epic 241 at the SCG and few of his own knocks in English conditions.
"You don't necessarily have to dominate each bowler. If you are batting on 70-80 and somebody is giving you trouble you back off.
Continuing, Lara told his one-time biggest rival: "You know that as well Sachin, in terms of that great innings you played in Sydney, it was not about a particular bowler getting you out but it was a particular shot getting you out, and you stopped yourself from playing it and you were able to score in other areas. So it's a similar sort of approach."
The Prince of Trinidad, who played some fine knocks in England, recalled his approach to batting there.
"I remembered a lot of innings I have played in the past, with Chanderpaul or Jimmy Adams. Those partnerships were so, so important in getting me to where I got to, getting the team the runs that were required.
"So again, with all the challenges that the West Indies team is going to face with the bat, partnerships are important, rotating the strike, making sure that you keep the bowlers' best deliveries out and punish the bad ones.
"Putting runs of the on the board will be key for the West Indies," Lara said.
He also remembered his duels with the great Glenn McGrath and cited them as example to help the current team.
"A good example would be Australia, playing against Australia and I would be on 78 or maybe 114 and McGrath comes back for a spell.
"I know he is going to bowl six overs-seven overs, so I don't need to take any great risk if the other guys at the other end are giving me the opportunity to score," Lara said.
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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