Man City held to draw by Inter, PSG win late in Champions League
City, who have won all four of their Premier League games this season, were unable to break down Inter in a repeat of the 2023 final, which City won. (Photo: Getty Images)
By EasternEyeSep 19, 2024
MANCHESTER City drew 0-0 against Inter Milan in their opening Champions League match on Wednesday. Meanwhile, Paris Saint-Germain secured a last-minute win over debutants Girona.
City, who have won all four of their Premier League games this season, were unable to break down Inter in a repeat of the 2023 final, which City won. Kevin De Bruyne was substituted at half-time due to injury, and Phil Foden had City's best opportunity, but his shot was saved by Inter goalkeeper Yann Sommer. Erling Haaland, who was seeking his 100th goal for the club, was kept quiet.
"It was a very intense game against a strong opponent. We knew what was coming; they are a top team as well, and they are used to winning, so we were not going to have an easy job," City defender Ruben Dias told TNT Sports.
Henrikh Mkhitaryan had a chance to win the game for Inter but missed 15 minutes from the end. City extended their unbeaten run in the competition to 24 matches, just one short of the record set by Manchester United between 2007 and 2009. This was only the second time in 42 home Champions League games under Pep Guardiola that City failed to score.
"Our plan was to show that we're not scared to play here," Inter midfielder Hakan Calhanoglu said.
PSG, facing Girona, seemed to be heading for a draw until a goalkeeping error by Paulo Gazzaniga allowed Nuno Mendes’ cross to slip through in the 90th minute, giving the French champions a 1-0 victory.
"It was a difficult game; they're a team that plays well with the ball," Mendes told Canal Plus. "I was surprised by the goal. The goalkeeper was there and it got through."
In other matches, Borussia Dortmund, last season's runners-up, won 3-0 at Club Brugge thanks to two goals from Jamie Gittens, who came off the bench. Serhou Guirassy added a penalty in stoppage time.
Celtic began their campaign with a 5-1 win over Slovan Bratislava, marking their first victory in an opening Champions League game in 13 attempts. Liam Scales, Kyogo Furuhashi, Daizen Maeda, and Adam Idah scored for Celtic, while Kevin Wimmer pulled one back for the visitors.
"It's a fantastic night," Celtic captain Callum McGregor told TNT Sports. "I hope the supporters enjoyed it because the managers and players did. This is the next level for the group in terms of growth and development."
Bologna drew 0-0 with Shakhtar Donetsk in their first-ever Champions League match. Lukasz Skorupski saved a penalty from Shakhtar's Georgiy Sudakov early in the game.
Sparta Prague defeated Red Bull Salzburg 3-0 with goals from Kaan Kairinen, Victor Olatunji, and Qazim Laci, securing their first win in the competition proper since 2003.
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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