They both are "blonde and mavericks" in their own way, says British star Matt Smith, who plays royalty in the upcoming fantasy drama series "House of the Dragon" after portraying Prince Philip in the acclaimed show "The Crown".
But there is a difference between Prince Philip and Daemon Targaryen; the latter is fictional as he exists in celebrated American author George R R Martin's book "Fire & Blood" which serves as the source material for "House of the Dragon".
"They're both princes, blonde and mavericks to a certain degree. Playing someone from history who is real, there's a different type of pressure that comes with that, but you've got a whole load of material.
"It's a very interesting process because once you're trying to create something that feels like them. It's not an imitation and you want to do something that feels like it's unique to you," the 39-year-old actor said in a virtual roundtable interview, also attended by PTI.
"House of the Dragon" follows the history of House Targaryen set 300 years before the events narrated in "Game of Thrones", the epic fantasy series which ended its eight-season run in 2019.
Smith plays Daemon, the heir presumptive to the Iron Throne, second in line after his older brother Viserys I Targaryen (played by Paddy Considine).
While he had a lot of source material to fall back on to prepare for both the roles, the actor said one faces a different kind of pressure when playing a real-life character like the late Prince Philip.
With Daemon again, there was a lot of source material, he added.
"Both the characters allowed for a lot of scope and have an energy of defiance about them, which is again quite similar. But, they are wonderful processes to be part of. I'm really proud I got to play Prince Philip. I thought he was a total rockstar," Smith said.
"Game of Thrones", an adaptation of Martin's book "A Song of Ice and Fire", had many fan favourite characters such as Jon Snow (Kit Harington), Arya Stark (Maisie Williams), Cersei Lannister (Lena Headey), Sansa Stark (Sophie Turner), and Tyrion Lannister (Peter Dinklage) to name a few.
According to Smith, the audiences will have to make up their mind if Daemon will be one of the people to root for.
The Emmy-nominated actor described his character as a man who is "complicated and not just one thing".
"He's quite loyal. He has a set of values he really sticks by. They're just different from other people's values. There's more to him than meets the eye and there's a degree of more sensitivity and fragility than perhaps you've seen thus far."
Daemon's complexities really the actor to the part, he said.
"At any point you never really know what he's going to think, what he's going to do, which is one of the things that as an actor I found quite attractive because it allows for a certain amount of instinct to come into play," he added.
In the trailer of the show, the audience sees King Viserys I (Considine) torn between choosing his younger brother Daemon (Smith) and his firstborn child Rhaenyra Targaryen (Emma D'Arcy) to rule the continent of Westeros, home to the Seven Kingdoms.
What also makes "House of the Dragon" something to look forward to is the dynamics between Daemon and his niece Rhaenyra, who expects to become the first queen regnant of the Seven Kingdoms.
Besides his brother King Viserys I, Smith said Daemon only has respect for Rhaenyra, with whom he converses in a secret language which is "a mixture of Latin and Arabic".
"She's his niece and there is a very deep connection within the family. His admiration, love, and mild obsession with his older brother is sort of reflected in his relationship with his niece. She's one of the few people that he treats with utter respect and reverence in the kingdom alongside his brother. Everybody else is up for grabs," he added.
Smith, who watched "Game of Thrones" when it was being aired, said, "House of the Dragon" is an original endeavour.
"'Thrones' was in the north, in the south and in the east, and there are lots of different elements to it. Whereas, this focuses on the world of Westeros and one family. Our story is slightly different. It's a more localised, focused family drama. There's a new set of brilliant actors who are going to emerge who audiences are going to fall in love with. The characters are really vivid," he added.
The actor said the world of the show would feel familiar to the parent series, but it will also feel original.
"The same deceit, backstabbing, war, love, lust, passion, rage, all of that stuff that made 'Thrones' interesting is alive in 'House of the Dragon'," he said.
Ryan Condal is attached as the showrunner on "House of the Dragon" along with Emmy winner Miguel Sapochnik, who helmed "Game of Thrones" episodes such as "The Battle of Bastards" and "The Winds of Winter".
Sapochnik has directed the pilot and additional episodes in the show.
Also starring Olivia Cooke, Steve Toussaint, Eve Best, Fabien Frankel, Sonoya Mizuno, and Rhys Ifans, "House of the Dragon" will start streaming in India on Disney+ Hotstar from August 22.
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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