The State of AI-Generated Podcasts: Industry Perspectives, Audience Reception, and Podcasters’ Concerns

With over four million shows, the podcasting industry offers a wide range of content. However, recent advances in artificial intelligence have led to a sudden surge in AI-generated podcasts. This development raises some important questions. When millions of podcasts by real people already exist, what new value can AI-generated podcasts bring? Why are large tech companies investing so heavily in this space? Are they attempting to fill a genuine gap in the market? AI tools have become instrumental in helping creators simplify their workflow and produce high-quality content. However, allowing AI to take full control of podcast production marks a significant shift. This report aims to explore these developments in depth. It examines the different perspectives across the podcasting ecosystem and evaluates the potential impacts of AI-generated content on all key stakeholders.

I. Introduction
II. Reception by Listeners
III. Perspectives of Original Podcasters
IV. Technological Advancement
V. Policies by Podcasting Platforms
VII. Approach of Podcast Networks
VIII. Future Outlook and Predictions

I. Introduction

The podcasting industry attracts a diverse and loyal global audience. This established ecosystem offers an opportunity to experiment with new forms of audio content, including podcasts generated by AI. In recent years, significant advancements have been made in speech synthesis and large language models (LLMs). Modern AI voice technologies are now capable of producing natural-sounding, expressive, and contextually aware voices.¹² These developments have significantly lowered the barriers to creating AI-generated audio content. Given these shifts, I believe it is important to take a closer look at the current state of AI-generated podcasts in 2025. This analysis explores critical questions around listener reception, the positions of major podcasting platforms, the perspectives of traditional podcasters, and the strategies employed by podcast networks. It also examines the overall benefits and challenges posed by this emerging technology, and offers insights into the trends likely to shape the future of podcasting.

II. Reception by Listeners

Understanding how listeners react to AI-generated podcasts is crucial for predicting the future impact of this technology. Although academic research on this topic is still limited, early studies and surveys indicate that many podcast listeners prefer human hosts over AI voices.

A survey involving nearly 3,000 individuals revealed that a majority favors human hosts, even if AI voices sound polished and natural. However, the same study found that about one-third of Millennials, one-quarter of Gen Z, and 37% of general podcast listeners do prefer AI-generated content.³ Additionally, Audacy’s Innovation Tracker showed that people are more than twice as likely to trust a human voice (55%) compared to AI-generated content (23%).⁴ Another study conducted in a university setting explored students’ experiences with AI-generated podcasts as educational tools. The findings suggested that students found podcasts beneficial for everyday learning, but reported that AI-generated podcasts often lack emotional engagement and can create a disconnect compared to human-hosted educational podcasts.⁵

An alternative perspective is also worth considering. Some studies suggest that users favor AI-generated content until they are informed that it was created by AI. When participants in surveys were informed that the content they were evaluating was AI-generated, they generally develop a bias against it, perceiving it as less authentic or trustworthy.⁶⁷⁸ In one study with nearly 2,000 participants, researchers randomly labeled headlines as AI-generated. This labeling resulted in reduced credibility, regardless of the content’s accuracy or whether it was actually created by humans. This finding highlights a strong psychological bias against AI-generated content as less credible.⁹

Some users also feel there is a compelling use case for AI-generated on-demand podcasts. As one Reddit user explained: “Where I see this going is not an explosion of published content, but the ability to make on-demand, bespoke content live. I will always listen to human-generated podcasts, but if I had the option to listen to a pretty good sounding podcast about a VERY niche topic I’m interested in but nobody else is covering… yeah, that sounds awesome. But, that wouldn’t be me wading through a sea of crap to find the one diamond. That would be me pressing a button and asking for a topic”.¹⁰ While anecdotal, this comment illustrates how some listeners value the immediacy and niche customization.

III. Perspectives of Original Podcasters

Podcasters largely view AI-generated content with skepticism and concern. A common worry is that these podcasts are often plagiarized or low-quality content, created for quick ad revenue, adding little to the industry.¹¹ AI-generated podcasts may oversaturate the already crowded podcasting space with low-effort, repetitive content. This could make it harder for original creators to gain visibility.¹² The strength of podcasting lies in the genuine connection between the podcaster and the listener. AI-generated content might dilute this personal touch that listeners value.¹³

Podcasters also raise concerns about the quality and accuracy of AI-generated podcasts.¹⁴ Issues like hallucinations,¹⁵ unnatural or robotic language, repetitive content, and a lack of nuanced understanding of complex topics are quite common. An experiment with AI-generated podcasts has revealed structural flaws, mediocre content, and a general lack of engagement.¹⁶

Podcasters, like many other professionals, are concerned about how AI might affect jobs in their field. Editors, voice actors, and even podcasters worry that as AI tools become more advanced, opportunities for human professionals could diminish, leading to job losses and a fundamental shift in how content is created.¹⁷¹⁸

To adapt to the rise of AI, many podcasters are taking a proactive approach. One of these strategies involves using AI itself as a tool to simplify and speed up their production process.¹⁹ These tools are being utilized to streamline time-consuming tasks such as transcription, audio editing (including noise reduction and level balancing), generating show notes, and even creating promotional content for social media.²⁰ However, podcasters often point out that these tools may save time, but they are not always dependable. A manual review is usually necessary to ensure the final output meets their quality standards.²¹²² Apart from using AI tools, some podcasters are also focusing on what sets them apart: genuine human connection, honest storytelling, and building niche communities around shared interests.²³

IV. Technological Advancement

Many tech companies and startups have made significant progress in developing technologies to create AI-generated podcasts. Some cutting-edge tools, such as Notebook LM, have taken the industry by surprise. In this section, we will explore key technological and strategic advancements made by these companies.

1. Google

Google is actively developing AI technologies to facilitate the creation and consumption of AI-generated, podcast-like audio content. NotebookLM, developed by Google Labs, is a prominent tool in this effort. The “Audio Overview” feature of NotebookLM can transform documents into podcast-style audio discussions.²⁴

NotebookLM was never designed to compete with traditional podcasts. Instead, it aims to serve niche use cases. These are situations where the potential audience is so small that producing an actual podcast would not be economically viable. The tool enables users to get a personalized audio to consume complex content in a conversational, accessible format.²⁵ Despite its narrow initial focus, the feature quickly gained popularity.

Google is now constantly improving NotebookLM with new features,²⁶ Collaborating with spotify to generate “Spotify Wrapped”,²⁷ and testing new experimental AI features.²⁸ In addition to NotebookLM, google is also experimenting with a similar technology called Illuminate to generate podcasts.²⁹

2. Microsoft

In 2025, Microsoft introduced a bespoke podcast feature in its Copilot AI, similar to Google’s NotebookLM.³⁰. However, initial evaluations found the output lacking a natural tone and depth.³¹

Apart from Microsoft’s significant investments in OpenAI, the company has also recruited former DeepMind scientists.³² DeepMind, which was acquired by Google, was instrumental in developing Google’s “Audio Overviews” feature.³³ This strategic move underscores Microsoft’s commitment to advancing AI agents, particularly in enhancing Copilot’s functionalities.

3. Others

Podcastfy is an open source python package. This can transform web pages, PDFs, text, and images into engaging, multilingual audio conversations using generative AI.³⁴ It is an open source and customizable alternative to Google’s NotebookLM Audio overview.³⁵

Wondercraft is an AI-driven audio production and editing platform. enables users to generate bespoke podcasts from text input. It also supports importing audio from NotebookLM, allowing users to edit the content using its integrated audio editor.³⁶

ElevenLabs, an another startup specializing in AI voice generation, has developed a technology similar to NotebookLM called “GenFM Podcasts”. This can also generate podcasts from any PDFs, articles or e-books.³⁷ They have also announced a partnership with Deutsche Telekom to power AI-driven podcasting in Magenta App.³⁸

Rask AI is an AI-powered video and audio localization and dubbing platform. Podcast creators use it to translate their shows for global audience. It uses technologies like voice cloning and text-to-speech to preserve original tone.³⁹

V. Policies by Podcasting Platforms

It is important for us to understand how podcasting platforms are proactively developing policies to manage AI-generated content on their platforms. This also gives us insight into how these companies perceive AI-generated content.

1. Apple Podcasts

Apple Podcasts has an explicit policy concerning the use of AI in podcast creation. They have two dedicated sections in their “Content and Subscription Guidelines”. First section specifically addresses “Artificial Intelligence (AI) Transparency,” stating that creators who use AI to generate a “material portion” of their podcast’s audio are required to prominently disclose this information. This disclosure must be included both within the audio and in the metadata associated with the episode or the entire show. Second section prohibits the “Misleading Use of AI”. Examples provided includes using AI to fabricate news stories or to manipulate audio clips to present false narratives.⁴⁰

2. YouTube

YouTube requires AI content disclosure if the content is realistic, meaning a viewer could easily mistake it for a real person, place or event.⁴¹ This includes altered footage or fabricated scenes. Disclosure is generally not required for clearly unrealistic content.

3. Spotify

Spotify prohibits the distribution of AI-generated audio or visual content that includes edited recordings which misrepresent the original meaning or context, thereby posing a risk of harm to the speaker or others. It also prohibits synthetic media that falsely portrays someone in harmful or illegal situations, such as fabricated crimes or sexual content.⁴²

4. Podcast Hosts

I checked a few podcast hosts like Libsyn,⁴³ Buzzsprout, ⁴⁴ Podbean,⁴⁵, transistor, ⁴⁶ Simplecast, ⁴⁷ etc. However, I could not find any explicit mention of policy regarding AI generated podcasts, except for Buzzsprout, which states that Buzzsprout Ads are not allowed for podcasts that utilize AI generated content.⁴⁸

VII. Approach of Podcast Networks

Podcast networks are increasingly experimenting with and integrating AI technologies to expand their global reach and boost advertising revenue. Here is an overview of the some steps taken by major podcast networks. This will also help us understand their future strategies and directions.

Spotify has Initiated an AI voice translation pilot to translate podcast episodes into multiple languages while retaining the original voices.⁴⁹ They have also collaborated with Google’s NotebookLM to offer the Spotify Wrapped experience as a custom AI-generated podcast.⁵⁰ Additionally, Spotify is exploring the use of deepfake podcast ads that mimic podcasters’ voices with their permission, though the company states that nothing has been confirmed yet. ⁵¹⁵²

iHeartMedia has launched “Daily Dad Jokes,” an AI-generated stand-up comedy show.⁵³ Additionally, the company is using Veritone’s synthetic voice technology to translate and produce podcasts in new languages, aiming to reach broader markets.⁵⁴

PodcastOne partnered with Rask AI to launch the podcast “Bad Bad Thing” in Spanish, demonstrating the use of AI for content localization.⁵⁵

NPR’s Planet Money experimented with AI by creating an episode using AI tools, exploring the capabilities and limitations of AI in storytelling.⁵⁶

CADA (Australia) aired a show hosted by an AI-generated persona named “Thy” for several months without disclosing its artificial nature, sparking discussions on transparency and ethics in AI usage.⁵⁷

VIII. Future Outlook and Predictions

1. Podcasters

Podcasters’ concerns are valid. Right now, there are no strong rules around how AI-generated content should be labeled or managed. Apple Podcasts is the only major platform with a clear disclosure policy. Spotify and Google only have rules to prevent obvious misuse. And among hosting platforms, only Buzzsprout has an explicit policy against monetizing AI-generated podcasts. That’s a pretty big gap. Additionally, with over 4 million podcasts out there and no great way to search or explore new shows, it’s already hard for creators to get discovered. Adding more AI-generated content to the mix doesn’t help.

Podcasters may be the most affected, but they also have some powerful tools at their disposal. AI can help speed up production, such as editing, transcription, generating show notes, or making social media clips. With the right setup, creators can produce high-quality content without needing a big team or a lot of money.

2. Listeners

Even though most of the listeners still prefer human-hosted podcasts, AI-generated podcasts are constantly finding an audience. Some listeners, especially younger ones, are open to AI voices, and there’s a growing use case for personalized, on-demand content. As from NotebookLM or the Reddit user mentioned, it is not about competing with the real podcasts, but about getting a decent, customized podcast on a very specific topic that no one else is covering. That’s something human podcasters just can’t scale to.

One area where AI podcasts are likely to take off is education. Many research papers suggest that podcasts can be useful for consuming complex content. With AI, they can convert research papers, notes, articles, or discussions into easy-to-understand conversational podcasts and listen to them while commuting or doing chores.

3. Technology Advancement

Synthetic voices are getting more realistic every year. They are still not hyper-realistic, but they are close. Startups and major tech companies are investing heavily to make them better, so it is only a matter of time before they sound natural in most situations.

4. Podcast Networks

Podcast networks seem to sense this as a business opportunity. Some of them are already using AI to translate existing shows into different languages while keeping the original host’s voice. That way, they can enter new markets with proven content. Networks are also experimenting with AI-generated ads and even fully AI-created shows. If the cost is low and the revenue potential is high, they are likely to continue in that direction.

5. Accuracy Concerns

There is a concern with AI-generated podcasts. Listeners can create their own on-demand podcasts with provided text, PDFs, etc. It is assumed that the podcast is generated based on the provided content, so it must be true. However, AI models can hallucinate, or their outputs can be biased depending on the companies that built them. That’s why transparency and editorial review are going to be more important than ever.

In the end, AI won’t replace podcasting. It will just change how it works. Human hosts will still be essential for storytelling, interviews, and building listener trust. But AI will play a growing role in education, accessibility, and niche content that would otherwise never be made. The challenge for creators and platforms will be to find the right balance and create the right policies.