Rob Greenlee

Podcast Host Platforms are Becoming the New Media Operating Layer

After months of New Media Show conversations with leaders across podcast hosting, creator media, analytics, advertising, video, and AI, a pattern is getting difficult to ignore.

By Rob Greenlee, CEO/Founder, Trust Factor Lab and Trust Creator Community at M3Linked.com, Host of NewMediaShow.com

Rob Greenlee, 2017 Podcast Hall of Famer, Chair and Host of NewMediaShow.com and Founder of Trust Factor Lab I have spent more than two decades helping podcast creators of all sizes and hosting platforms like Libsyn, Spreaker, and PodcastOne grow and evolve.

For much of that history, the basic job was straightforward. Store the media file. Generate an RSS feed. Distribute the show. Count the downloads. Keep everything running reliably, and the podcaster was happy.

Creators and media companies are trying to manage a more complicated media landscape in 2026.

A single conversation recording can become a full YouTube episode, an audio podcast, Spotify video, Apple Podcasts video, multiple short clips, social posts, newsletter content, community discussion, advertising inventory, and searchable source material for AI systems.

The show may still begin with a microphone, lights, and potentially a camera. What happens around that show has become a much larger media operation. That is why I believe we are in a moving structural change in podcast and creator media technology:

The podcast host platform of old is evolving into a new media-creator operating layer.

And eventually, I believe the most valuable part of that layer may be the intelligence it produces.

This conclusion did not come from watching a single company or a single product launch.

It has become clearer to me through a series of conversations on the New Media Show with people building different parts of this changing market.

They do not all agree on what comes next. That is precisely what makes the pattern interesting.

We have already outgrown the old definition of hosting

When I spoke with Libsyn CEO Brendan Monaghan on New Media Show Episode 660, we spent considerable time asking what a podcast hosting company should become.

The episode opened with a simple observation:

“Podcast episode hosting used to be simple.”

The conversation quickly moved beyond file storage and RSS into monetization, analytics, video, AI-assisted workflows, distribution, measurement, and audience growth. The episode framed modern hosting as a broader creator-platform problem. (New Media Show Libsyn Interview)

That is significant coming from Libsyn.

Libsyn helped establish the commercial podcast hosting category. I also spent several years there as a VP, so I understand how central reliable hosting, RSS distribution, and measurement have been to the business.

But creators are now asking technology providers to solve problems that barely existed when the hosting category was created.

– How do I publish to multiple video and audio platforms in a single upload?

– How do I understand performance when the audience and counting methods are fragmented?

– How do I make better creative and audience-attraction decisions based on that data?

– How do I monetize across those surfaces and make technology simpler and speed up the process?

– How much of this work can software tools or AI take off your production team’s plate?

– Those are no longer edge questions; they increasingly define the publishing product the market wants and needs.

The audience has stopped caring about delivery methods

One of my favorite observations from Leo Laporte during Episode 672 was captured in the published episode notes:

“Most viewers or listeners do not care how a show is technically delivered.”

They care whether they can find it, whether it is worth their time, and whether they trust the people making it. (New Media Show Interview with Leo Laporte)

The above sounds obvious, but it has enormous implications.

Our industry still spends a great deal of energy defining media through its distribution technology.

People move between YouTube, Apple Podcasts, Spotify, social feeds, streaming television, newsletters and communities. They may encounter the same personality or show in several of those places without giving much thought to the underlying delivery technology.

Leo and I discussed how audio and video are increasingly part of the same overall media experience while measurement remains fragmented between platforms. (New Media Show interview with Leo Laporte)

That fragmentation creates an opportunity for improvement in the new media and creator space, including podcasting.

The more places a show travels, the more valuable a system becomes for understanding what is happening across all of them.

We need to measure the show, not just the file

My conversation with Listener.com founder Casey Adams on Episode 673 took this directly into measurement.

The central question was:

“How do you measure the true value of a show when the audience is no longer in one place?” (New Media Show interview with Casey Adams)

A podcast episode today may generate an RSS listen, a Spotify stream, a YouTube view, short-form consumption, newsletter engagement, and a sponsor interaction.

Each platform measures behavior differently.

Casey’s concept of an “episode cluster” is useful because it treats all the content generated around an episode as connected, rather than pretending that the audio file represents the entire media product. (New Media Show interview with Casey Adams)

I think that idea points toward something larger. The next generation of creator analytics cannot simply show a data analytics dashboard.

It has to help answer:

What happened?

Why did it happen?

What should I do differently next time?

The above last question changes everything.

Once the platform starts helping the creator make the next decision, analytics begins turning into intelligence.

Rox Codes said the quiet part out loud

My July conversation with Flightcast CEO and co-founder Rox Codes made this transition particularly clear.

Rox came into podcast hosting from a YouTube creator and growth mindset. Flightcast did not begin with the assumptions of the traditional audio hosting industry.

During the conversation, we explored publishing, YouTube strategy, video, titles, thumbnails, retention, experimentation, monetization, AI analytics, and the growing amount of technical complexity being pushed onto creators.

Near the end of the episode, Rox made the underlying market change explicit:

Basic hosting has become a commodity. (New Media Show interview with Rox Codes)

The comment above deserves more attention than it received.

If reliable hosting becomes expected infrastructure, where does future value move?

Rox’s answer points toward growth, analytics, experimentation, distribution, monetization support, and creator intelligence.

Flightcast is already building around unified publishing and analytics, AI-supported analysis, and the idea that creator software should help people understand what is working via deeply analyzing results data and testing rather than simply reporting numbers. (New Media Show interview with Rox Codes)

During that conversation, I even asked whether Flightcast is becoming a creator operating system.

I keep coming back to that question and potential opportunity. Because I don’t think this shift will be limited to Flightcast, but it may be leading this upgrade revolution.

I think it describes where a meaningful part of the platform market is heading.

The creator is becoming the media company

There is another piece of this transformation that technology companies cannot ignore.

The economic unit itself is changing.

On Episode 676, Steve Wilson of Daylight Media and QCODE discussed a creator-first media structure in which the creator maintains the audience relationship, while companies provide infrastructure, distribution, monetization, audience development, and other support for that relationship. (New Media Show interview with Steve Wilson)

The episode ultimately reached a bigger conclusion:

A successful show can be the center of a much larger media business built around the audience.

That can include long-form audio, video, clips, subscriptions, communities, events, products, and additional intellectual property. (New Media Show interview with Steve Wilson)

Dan Granger of Oxford Road added the advertiser perspective in Episode 677.

The episode described how:

“A trusted personality can carry an audience across podcasts, YouTube, livestreams, newsletters, social platforms, communities, events, and direct business relationships.” (New Media Show interview with Dan Granger)

Advertising systems, however, still frequently purchase and measure these channels separately.

That creates another gap waiting to be solved.

The creators increasingly operate as one media brand.

The technology and measurement systems still often don’t see all media products.

Those realities are colliding.

Podcasting is becoming one lane inside a larger creator media system

Sam Sethi, CEO of TrueFans and co-host of Podnews Weekly Review, and I explored another version of the same shift on Episode 671.

The episode made the point that podcasting can no longer think only in terms of:

“feeds, files, downloads, and ad impressions.” (New Media Show interview with Sam Sethi)

Creators are building businesses around video, memberships, newsletters, events, merchandise, premium content, and direct relationships with their audiences.

That does not diminish podcasting. I believe it increases the show’s strategic value.

Long-form or Shorter-form podcast and video conversations, whether in horizontal or vertical video, can become an unusually powerful source of material because a single strong piece of intellectual property can feed many different audience experiences.

The show becomes the core. The distribution expands around it.

The media technology needs to understand the whole system.

I think we are moving through three generations

This is how I currently see the evolution.

Generation One: Podcast Hosting

Media file → RSS → Podcast apps → Downloads

The host’s primary responsibility was infrastructure.

Reliability mattered enormously.

Generation Two: Creator Platform

Audio + Video → Distribution → Monetization → Analytics → Creator tools

We are already well into this stage.

Traditional hosts have expanded. New entrants are arriving. YouTube and Spotify have changed creator expectations. Video has become much more important. AI is being inserted throughout production and publishing workflows.

Generation Three: Media Operating and Intelligence Layer

Content → Distribution → Audience behavior → Intelligence → Creative decisions → Monetization → Audience relationship

This is where things become much more interesting. The platform does more than distribute the show. It begins helping the media operator understand the business around the show.

What topics create discovery?

Which guests expand the audience?

Which titles produce curiosity without damaging trust?

Which thumbnails work with which audience?

Where do viewers drop?

Which clips bring people into long-form content?

Which platforms produce casual reach versus loyal audiences?

Which sponsor relationships actually work?

Which older episodes should surface again because current events have made them relevant?

What should the creator make next?

That is a fundamentally different value proposition from hosting an MP3.

The host may become invisible while the intelligence becomes valuable

There is some irony here.

The better these systems become, the less creators may need to understand the underlying infrastructure.

Rox Codes of Flightcast made this point during our Flightcast conversation while discussing acronyms such as RSS and HLS, as well as technical migration requirements. The software should handle much of that complexity for the creator. (New Media Show interview with Rox Codes)

Leo Laporte, TWiT.TV essentially made the same point from the audience’s side. People care about getting the show they want, not the mechanics used to deliver it. (New Media Show interview with Leo Laporte)

That means the infrastructure can increasingly disappear into the background. What becomes visible is the value created above it.

I suspect that by 2030, asking a platform how many shows it “hosts” may tell us much less about its strategic value than it does today.

Better questions may be:

– How much audience growth does the platform help create?

– How much friction does it remove?

– How much revenue moves through it?

– How much useful audience intelligence does it return?

– How effectively does it help creators make better decisions?

– How much control do creators retain over their media, identity, and relationships?

Can the creators trust the intelligence the system is giving them?

AI makes the trust question unavoidable

This is where the next phase becomes more complicated.

AI can already analyze transcripts, suggest titles, identify clips, summarize analytics, and surface patterns across large catalogs.

It will become much better at those jobs.

Eventually these systems may recommend topics, guests, formats, publishing schedules, monetization strategies, and creative direction.

At that point, the platform is influencing the media itself.

That raises questions our industry should begin addressing now.

What data shaped the recommendation?

Whose incentives are represented?

Is the platform optimizing for creator growth, audience value, advertising revenue, or its own engagement?

Can creators understand why a recommendation was made?

What happens when every creator receives similar optimization advice?

Where does human editorial judgment remain essential?

And how much creative independence are we willing to trade for performance?

My conversations with Leo Laporte, Rox Codes, Casey Adams, Steve Wilson, Dan Granger, and others keep returning to different versions of the same human issue.

Data matters. AI matters. Distribution matters.

But media ultimately succeeds because someone earns another person’s attention and gives them a reason to return to consume more.

Trust sits inside that relationship.

We have been heading toward this longer than it appears

None of this began in 2026.

Back in June 2022, Todd Cochrane, Buzzsprout’s Alban Brooke, and I were already discussing YouTube, distribution, and the growing tension between open podcasting and more controlled platform ecosystems on the New Media Show. (New Media Show interview with Alban Brooke in 2022)

Todd Cochrane and I spent years debating RSS, platform control, video, advertising, creator independence, and what happens when large technology companies push podcasting in directions the original architecture never anticipated.

The technologies have changed. The underlying question has remained remarkably persistent:

Who controls the relationship between the creator and the audience?

I believe the next version of that question is: Who controls the intelligence around that relationship?

That may turn out to be the most important platform battles of the next decade.

The next podcast/creator OS platform may barely look like a podcast host

I do not think podcast hosting disappears.

RSS does not suddenly become irrelevant.

Audio does not stop mattering because video is growing.

Reliable infrastructure remains essential.

But infrastructure alone is becoming less differentiated.

The larger opportunity is developing around the show-in-it conversion to being a media company.

Publishing. Distribution. Audience understanding. Cross-platform measurement.

Creative optimization. Monetization. Catalog intelligence. AI assistance. Creator ownership.

Human trust.

Those capabilities are beginning to connect with creators and audience communities.

When they do, calling the resulting product a “podcast host” may sound increasingly inadequate.

We will call it a creator operating system, a media operating platform, an intelligence layer, or something rather early and less defined.

The terminology is less important than the shift underneath it.

For 20 years, podcast technology has helped creators publish, distribute, and monetize.

The next-generation creator media OS companies will increasingly help them understand what should be made, what happened after they made it, analyze the results, and decide what to do next.

That is a much larger and more valuable services business. And I believe the race to own that layer has already started.

Rob Greenlee is a longtime new media executive, Podcast Hall of Fame inductee, and host of the New Media Show. His work focuses on the evolution of podcasting, video, creator-led media, AI, and human trust in emerging media systems.

AI Disclosure: AI tools were used to assist with organizing and editing this article’s research. The thesis, editorial perspective, final judgment, and responsibility for the published version remain mine and my New Media Show guests’.

Liquid Content Era Enables Creators To Become Trusted Media Brands

by Rob Greenlee, CEO/Founder, Trust Factor Lab and Trust Creator Community at M3Linked.com, Host of NewMediaShow.com & Spoken Human

Podcasting’s New Liquid Content Era has growing potential to turn audio and video creators into Trusted Media Brands.

Let’s stop pretending podcasting is still just an audio strategy.

It isn’t.

We are in a major reshuffle right now. The old boundaries around what a podcast is, how it gets discovered, and how creators build momentum are extending fast. What once felt fixed is becoming far more fluid and complicated. That is why I see this as podcasting’s new liquid era, where creators are becoming more than just podcasters.

Many are becoming trusted, personified, or human-centric media brands.

That shift did not happen overnight, but the major platform moves made it impossible to ignore. YouTube pushed podcasting deeper into its video ecosystem. Spotify reinforced video publishing and monetization. Apple pushed even further with a new video podcast experience via HLS streaming inside Apple Podcasts.

“That matters because it signals something bigger than a feature update.“

YouTube changed creator behavior. Spotify and Netflix reinforced the business case.

“Apple Podcasts has now validated that video podcasting via HLS is much closer to the center of gravity in podcasting. None of that means audio stopped mattering. Audio still fits some of the most valuable moments in people’s lives. It still works while driving, walking, working out, commuting, and doing everything else that makes spoken-word media so powerful. Audio still matters deeply.”

Video is not replacing audio in every context, but it is clearly driving much of the momentum, experimentation, audience behavior, and acquisition deals right now. That is why I do not think the smartest framing anymore is audio-first versus video-first.

The smarter framing is to trust first and to focus on content liquidity.
Because in a liquid content era, formats can move. Platforms do change. User behavior does shift. Discovery pathways evolve. But trust is what survives the reshuffle.

That is where new media creators need to up their game.

The goal is not just to publish an audio
The goal is not just to post a video version
The goal is not just to be present on another of many platforms
The real opportunity is to become a trusted media personality brand
That means your show is no longer just an RSS feed. It is a relationship. It has a recognizable point of view or change mission that matters to humans. It is also a repeatable format. It is a body of communications people can follow across audio, video, clips, livestreams, newsletters, search, and community.

And now there is another layer that matters more every month: AI algorithmic content scoring and sharing discovery in LLM’s.

The next phase of creator growth is not only about ranking in traditional search or getting picked up by AI platform algorithms.

To be discoverable inside AI answers, conversational search, and recommendation systems.

“If your content is clear, trusted, well-structured, and consistently published, it has a much better chance of being found, surfaced, and revisited across this new landscape.”

That is also why owned audience relationships are becoming so important.

The next strategic layer for creators is not just public content. It is building private, premium, interactive communities that they control.

Not just followers on rented platforms.
Not just subscribers inside someone else’s ecosystem.
Not just passive audience reach.

“Building spaces where creators own the direct relationship with their audience. Membership communities. Premium groups. Mastermind environments. Private creator circles. Direct audience ecosystems are built around trust, participation, and recurring value.”

Because when a creator builds that kind of community, they are not just publishing content anymore. They are creating a meeting place for direct connections. That is an ongoing experience. The creator is building loyalty, feedback loops, and a deeper business relationship that is far more durable than a view count or a download-and-view number on a large consumption platform the creator does not control the access pathways to.

That changes the economics, too.

Public content can drive awareness
Video can drive discovery
Audio can deepen a habit.

A private community can drive retention, monetization, and direct audience relationships.

That is a much stronger model than relying entirely on platforms you do not control.

And now we need to talk about what comes next.
I believe hybrid human-and-AI creator brands will become a real part of this landscape. Not fake creators replacing people. Not synthetic noise with no soul. I mean human creators extending their voice, expertise, archives, and availability through AI clones that are built the right way.

Done badly, that becomes creepy, misleading, and disposable.
Done well, it becomes powerful.

“A trust-first AI clone should not pretend to be a human when it is not. It should be clearly disclosed. It should reflect the creator’s actual values, body of work, and knowledge. It should be built from authentic source material. It should help audiences access ideas, archives, recommendations, and next steps in ways that extend the human-creator brand rather than diluting it.”

A creator’s human voice remains the center. The human relationship remains the anchor.

But AI can extend availability, responsiveness, discovery, education, and continuity.

In other words, the future is not human or AI, but both. It is trusted human brands with carefully built AI extensions.

Only works if trust comes first. If audiences feel tricked, manipulated, or confused, the brand loses value. But if the AI layer is transparent, useful, aligned, and grounded in the creator’s real voice and expertise, it can become an extension of the relationship rather than a replacement for it.

That is why I think the creators who win in the next chapter will be the ones who know how to build trust across multiple surfaces:

Public platforms
Audio feeds
Video channels
AI discovery layers
Private premium communities and eventually, trust-first AI versions of their own brand.

That is the shift.

We are moving from content creators to trust builders
From podcasters to media brands
From single-format publishing to format flexibility
From a rented reach to an owned relationship
From static content libraries to intelligent, discoverable creator ecosystems
That is not the end of podcasting
That is, podcasting is becoming bigger than its original container.

And from my perspective, that is the real opportunity for creators, experts, and brands right now. In a world where more content will be created by more people and more machines than ever before, trust becomes the filter. Trust becomes the signal.

Trust becomes the value. The question now is not whether you are only a podcaster.

“The question now is whether you are building something people trust enough to follow, join more deeply in a community, and eventually interact with you and your brand.”

“The path is built on a trust-first approach: clear disclosure, authentic source material, useful value for the audience, and strong alignment with the human creator’s real voice and expertise.”

What opportunity is there now for creators?

To become trusted media brands that use public platforms for reach, video for discovery, audio for habit, private communities for ownership, and trust-first AI extensions for scalable audience support.

About the Author
Rob Greenlee is a 2017 Podcast Hall of Fame inductee and Chair, a global new-media leader who bridges podcasting’s human roots and its AI-driven future. As founder of Trust Factor Lab and host of the “New Media Show” and “Spoken Human”, Rob helps creators start, grow, monetize, and future-proof their content. He’s held leadership roles at Microsoft, Spreaker, Libsyn, StreamYard, and PodcastOne, and serves as Chairperson of the Podcast Hall of Fame. Learn more at RobGreenlee.com and join the Trust Factor Lab Creator/Podcast Services.

Personal note: I used AI tools to help organize this article and hand-edited it; the views, clarifications, responsibility, and industry perspective are mine. I have been working in podcasting and platform adoption for more than two decades, and this article reflects my own position. The original word choice was mine, and so is the clarification.

Don’t Fear AI Content and Start Leading with Labeling Standards that Retain Human Trust

by Rob Greenlee, CEO/Founder, Trust Factor Lab and Trust Creator Community at M3Linked.com, Host of NewMediaShow.com & Spoken Human

I have been in this medium long enough to watch it evolve through every major shift, from RSS and portable listening to smartphones, streaming platforms, video, dynamic ad insertion, and now AI-assisted media creation.

Every time real change hits podcasting, some part of the industry reacts as if the medium itself is under attack. That reaction is understandable. But fear is not a strategy. It never has been.

What is happening now with AI-generated podcasts, cloned human voices, and AI-assisted publishing is no longer some fringe experiment. It is becoming part of how media will be created, scaled, distributed, discovered, and monetized. Pretending it is not happening, or trying to shame the entire category out of existence, is not leadership. It is avoidance.

“I understand why many creators feel threatened. There are already irresponsible uses of AI in media and podcasting. We are seeing low-quality synthetic shows, questionable voice cloning, automated content pushed live without real editorial judgment, and content factories producing more noise than value. That deserves criticism. That deserves scrutiny. That deserves standards.”

But condemning all AI-generated podcast content simply because some people use it poorly is short-sighted.

The industry also needs to be honest about something else. Not all human-created content is good either.

“A lot of human-created podcast content has always been weak, repetitive, poorly positioned, or disconnected from what audiences actually want. Low quality did not arrive with AI. Human creators have been making forgettable content for years. So the dividing line is not human versus AI. The real dividing line is between valuable and worthless, trusted and deceptive, and intentional and careless“.

That is the conversation we should be having.

AI-generated podcast show creation is already contributing to new content growth at a time when growth among human-only creators has slowed and, for the past two or so years, flatlined in RSS-based podcasting.

Many human creators are burning out, publishing less, or shifting their energy toward video, social platforms, and private communities. AI-assisted creation is starting to fill part of that gap.

And yes, whether people like it or not, AI will create popular shows. I believe we are already seeing many signs of that.

Audiences do not reward content simply because it was made entirely by a human. They reward content that is useful, compelling, entertaining, emotionally resonant, and worth coming back to. That may make some people uncomfortable, but discomfort does not change the market’s direction.

“This does not mean all AI content is good. It means the industry needs to get much smarter about what good looks like and how trust is maintained as synthetic and human-led media continue to blend together.”

That belief sits at the center of what I am building with Trust Factor Lab.

—————————————————————————————–

The mission of Trust Factor Lab is grounded in a simple truth: building a brand is not about being seen; it is about earning trust. In a media environment increasingly filled with synthetic content, AI-generated voices, and automated publishing, the long-term winners will not be the loudest creators or the fastest content factories. The winners will be the people and companies that know how to turn trust into measurable growth through authentic storytelling, strong production standards, smart distribution, and AI-assisted workflows that protect the human voice rather than eroding its integrity.

That same philosophy drives the Trust Creator Community at M3Linked.

The purpose of that community is to help creators, leaders, and brands build trust-first media businesses in a world where human-made and AI-assisted content increasingly coexist. It is a place to develop the skills, standards, and mindset needed to grow without losing credibility. It is a place to learn how to use AI strategically without losing touch with the audience. Most importantly, it is built around the belief that trust is not a vague or soft concept. It is the foundation of audience growth, loyalty, monetization, and long-term relevance.

This is also why I believe being reflexively anti-AI may be a long-term mistake for podcasting and new media.

The better path is not blind acceptance. It is responsible leadership.

In recent episodes of New Media Show, I have been exploring this issue from several angles. In conversations with Jeanine Wright, we discussed AI-generated hosts, synthetic personalities, disclosure, and whether trust may transfer to AI voices.

In my discussion with Justin Jackson, we examined the growing reality of synthetic creators and cloned human media as part of a broader shift in the creator economy.

In another conversation with Dave Jackson, we touched on why live content may become even more valuable as proof of life in an increasingly synthetic media-filled world.

And in discussions with Arielle Nissenblatt, the focus kept returning to a simple truth that still matters in any era: if a show is not clearly positioned, consistently valuable, and genuinely recommendable, no amount of technology will create lasting trust.

“An important point is that AI may make content creation faster. It may make show generation easier. It may create breakout hits. But none of that removes the need for audience trust, clear positioning, differentiation, and a real reason for people to care”.

Trust still decides what connects and adds lasting value for humans, the second-level consumers of any AI or human-created content.

AI will be the first consumer of any human- or AI-created content, evaluating whether it is worthy of human consumption.

“That is why the podcasting industry needs to move quickly toward AI best practices. We need standards around consent and licensing for cloned voices and likenesses. We need norms around disclosure in show descriptions, metadata, and listening environments. We need stronger editorial standards for AI-assisted episodes, especially in news, education, health, finance, and expert commentary. We need clearer definitions of what qualifies as responsible AI-assisted publishing versus synthetic spam. And we need platforms, advertisers, and creators to have a more honest conversation about how trust should affect monetization”.

Most importantly, we need leaders in podcasting to stop treating this as someone else’s problem. This is our problem. It is also our opportunity.

Podcasting has always been one of the most intimate media formats in the world. It is built on voice, trust, authenticity, and relationship. That gives this medium a unique opportunity to help define how AI-generated spoken content should evolve responsibly. If podcasting does not lead this conversation, others will. And they may care far less about trust, disclosure, creator protection, and audience respect than we should.

I am not arguing for blind acceptance of everything AI brings.

I am arguing for a mature, strategic, trust-centered response to a technology that is already reshaping the media landscape. That means being tough on bad actors, clear about ethical boundaries, and proactive in establishing standards before harmful habits become normalized.

How AI Creators, Agents, and Human Operators Build Trust

If AI-generated creators, cloned human voices, and agent-driven media systems are going to earn public trust, they cannot rely on novelty alone. They need clear rights-based operating and disclosure principles.

First, they need disclosure (ShouldIDisclose.AI).

Audiences should know when a show, segment, voice, or script is AI-assisted or fully AI-generated. Hidden AI is where suspicion grows fastest.

Second, there is a need for consent and ownership of rights (Royall.ai).

No cloned voice or likeness should be used without explicit permission. Human creators should control how their cloned identity is trained, where it appears, and what kinds of content it can be used for.

Third, as of today, they still need human editorial direction and oversight.

Even when AI generates a first draft, human judgment should still approve the final output, especially when the content includes facts, advice, analysis, or sensitive public claims. AI can accelerate production, but accountability still needs to be human-led.

Fourth, they need consistent content value and integrity.

Whether content is human-created or AI-assisted, it still has to be worth the audience’s time. Audiences may tolerate new workflows, but they will not remain loyal to useless, low-integrity content.

Fifth, they need a stable identity and consistent human-like trust behavior.

AI creators and agents need a recognizable point of view, clear standards, and consistency over time. Trust grows when audiences understand what a creator stands for and what to expect.

Sixth, they need an explainable, transparent, human-understandable process.

Audiences do not need a technical white paper, but they should always be provided a path to understand trust-building basics. Is the show human-led and labeled human? Is it a licensed and disclosed clone? Is it built from approved source material? That clarity matters.

Seventh, they need visible correction and accountability.

AI systems will make mistakes, though likely fewer in the future. Trust grows when creators and operators correct those mistakes clearly and quickly, rather than hiding behind the technology.

Eighth, they need respect for emotional boundaries.

Synthetic hosts and cloned creators should never manipulate audiences by making inaccurate claims and trying to scam humans by confusing simulation with a deeper human bond than what really exists. Engagement should not come from emotionally human-like behavior that leads to deception.

Ninth, they need aligned incentives with integrity.

If a synthetic show/host is obviously designed only to flood feeds, maximize ad inventory, or game recommendation systems, audiences will sense that. Trust holds when audience benefit and creator integrity remain central.

Tenth, they need real human feedback loops.

The more AI-driven the content production process becomes, the more important it is to maintain authentic ways for audiences to question, respond to, and influence the content’s direction.

The Standard in New Media and Podcasting That Matters

The podcasting industry should not be known for panicking about AI.

It should be known for shaping the responsible use of AI in a medium where human trust matters more than ever.

The real challenge now is not whether AI-assisted or cloned human content should exist. It will.

The real challenge is whether we will build it in ways that strengthen human connection, preserve creators’ integrity, and create more value for audiences, rather than undermining all three.

That is why we are building the Trust Creator Community at M3Linked.

And that is the larger conversation the podcasting industry needs to have right now. Not a panic-driven conversation. A leadership-driven one.

The Word “Podcast” Is Owned by the Audience Now

By Rob Greenlee

For years, the podcast industry has argued over what a podcast really is.

Is it an RSS feed?
Is it an audio file?
Is it a downloadable media enclosure?
Is it open distribution?
Is it something in Apple Podcasts?

Those definitions still matter, especially to those of us who helped build and protect the open podcasting ecosystem. RSS matters. Creator control matters. Portability matters. Ownership matters.

But here is the uncomfortable truth: The word podcast is no longer owned by the industry. It is now owned by the audience.

The audience does not care nearly as much about the delivery technology as we do. They say they “watched a podcast on YouTube,” “followed a podcast on Spotify,” “saw a podcast clip on TikTok,” or “listened to a podcast in the car.”

They are not thinking about RSS, hosting platforms, download measurement, API delivery, or whether the file was streamed or downloaded.

They are thinking about the show. That is the shift.

To the public, a podcast is increasingly a recurring show with a host, a point of view, a topic, a relationship, and a familiar format. It may be audio. It may be a video. It may be clipped, streamed, summarized, searched, or recommended by an AI system.

This is where the old industry definition starts to break down.

The podcast industry can argue that YouTube shows are not “real podcasts.” But if millions of people call them podcasts, watch them as podcasts, and advertisers buy them as podcasts, then the market is already redefining the word.

That does not mean open podcasting is dead. It means open podcasting has to compete within a much larger media environment.

The danger is obvious. Platforms want to shape the meaning of podcasting around their own business models.

YouTube wants podcasts to look and behave like YouTube.
Spotify wants podcasts inside Spotify.
Apple wants podcasts inside Apple Podcasts.
Social platforms want clips.
AI platforms want structured metadata knowledge and summarized answers.

Each platform pulls the word in its own direction. But the audience is the real force behind the change.

Words follow behavior. Television is no longer just a living room device. Radio is no longer just a local tower.

Podcasting is no longer just an RSS audio file. It is becoming a broader show format.

That means new media creators need to stop building only for the old definition of a podcast and start building for how audiences actually consume media now.

The show is the center.
The RSS feed is infrastructure.
The website is the home base.
YouTube and Spotify are discovery and consumption engines.
Social clips are attention triggers.
Email and community are direct relationships.
AI search is becoming the next discovery layer.

This is the new podcast stack. The biggest mistake would be to fight the audience over the word. The smarter move is to protect the open foundation while accepting the expanded meaning.

Podcasting’s future will not be won by telling people they are using an incorrect term. It will be won by building trusted shows that work across audio, video, social, search, AI, and community.

The word podcast may have started as a technical, open, but narrow standard distribution term. But today, it means something much bigger. It means a trusted show people choose based on what the platform it is consumed on calls it; if a production looks and sounds like a podcast, then that is what they will think it is in their lives.

And that definition now belongs to the audience.